Managerial Discretion, Business Strategy, And The Quality Of: Fill & Download for Free

A sales person must be able tell a "story" ..... by this, i mean create a visual image or scene for your client that they can see as a result of purchasing your product/service!I wrote an article recently for LinkedIn that talked about using data for storytelling...if you can use facts to build your story then you are on solid ground!two more pieces of advice I would like to offer... have your customers needs & objectives front of mind when selling!Be Honest, to the client & yourself....if you build a trusted relationship then the rewards will come!!Happy Selling!!!THE POWER OF DATA VIA STORYTELLINGA recent social function I went to…Party Host – “So, what line of work are you in Alistair?”Me – “Ummm Data, insights and helping our clients find profitable new customers…that sort of thing.”Party Host (Colour draining from face) – “Oh data, how interesting…”Me – “It is actually!!! It still amazes me that since man walked the Earth, data and it’s interpretation has been the foundation of every decision ever made… good or bad!I’m not sure I totally convinced him on the marvellousness of data but no doubt my enthusiasm on the subject lightened the topic for him!THE POWER OF DATAEvery day, each one of us analyses the information (or data) we receive and then makes a decision based on that data. Some decisions are small, some are big.I recently watched a wonderful movie - The Big Short - which follows the story of hedge fund manager, Michael Burry, and acknowledges his foresight of the GFC. By using data, and correctly interpreting it, Michael convinced many of Wall Street’s largest and well known finance houses to sell him credit default swaps against what he knew to be ‘vulnerable’ sub prime deals.In layman’s terms, Michael Burry strolled into Wall Street with $1.3 billion and put it all on Red…the only difference being that in Wall Street’s history, Red had never come up as a winner. As far as Wall Street was concerned, this was easy money!By understanding and correctly interpreting the data he had uncovered, Michael Burry realised a net return of $1 Billion (AUD) on top of his original $1.3 billion wager.Now how cool is that story!For some data can be as dull as watching paint dry. So when you are using data as part of your marketing conversations try to delivering it in the form of a story instead. Giving them a start , a middle and one hell of an ending – as in The Big Short – and you’ll no doubt shine a little light on the beauty and importance of data.For 5 tips on how to tell a great story with data here’s a great article by Jim Stikeleather that may help you out in that next marketing meeting (or party conversation if you’re as passionate as me on the topic ;).HOW TO TELL A STORY WITH DATAAn excellent visualisation, according to Edward Tufte, expresses “complex ideas communicated with clarity, precision and efficiency.” I would add that an excellent visualisation also tells a story through the graphical depiction of statistical information. As I discussed in an earlier post, visualisation in its educational or confirmational role is really a dynamic form of persuasion. Few forms of communication are as persuasive as a compelling narrative. To this end, the visualisation needs to tell a story to the audience. Storytelling helps the viewer gain insight from the data. (For a great example, how much do you think steroids have influenced baseball?)So how does a visual designer tell a story with a visualisation? The analysis has to find the story that the data supports. Traditional journalism does this all the time, and journalists have become very good at storytelling with visualisation via infographics. In that vein, here are some journalistic strategies on telling a good story that apply to data visualisations as well.1- Find the compelling narrative.Along with giving an account of the facts and establishing the connections between them, don’t be boring. You are competing for the viewer’s time and attention, so make sure the narrative has a hook, momentum, or a captivating purpose. Finding the narrative structure will help you decide whether you actually have a story to tell. If you don’t, then perhaps this visualisation should support exploratory data analysis (EDA) rather than convey information. However, for the designer of an exploratory visualisation it is still important to spark the viewers’ imagination to encourage examining relationships among and facilitate interacting with the data – think gamification.2 - Think about your audience.What does the audience know about the topic? Is it meant for decision makers, general interested parties, or others? The visualisation needs to be framed around the level of information the audience already has, correct and incorrect:Novice: first exposure to the subject, but doesn’t want oversimplificationGeneralist: aware of the topic, but looking for an overview understanding and major themesManagerial: in-depth, actionable understanding of intricacies and interrelationships with access to detailExpert: more exploration and discovery and less storytelling with great detailExecutive: only has time to glean the significance and conclusions of weighted probabilitiesBe objective and offer balance.A visualisation should be devoid of bias. Even if it is arguing to influence, it should be based upon what the data says–not what you want it to say. Tufte found numerous charts that misled viewers about the underlying data, and created a formula to quantify such a misleading graphic called the “Lie Factor.” The Lie Factor is equivalent to the size of the effect shown in the graphic, divided by the size of the effect in the data. Sometimes it is unintentional-a number that is three times bigger than another will be perceived nine times bigger if represented in 3D. There are simple ways to encourage objectivity: labelling to avoid ambiguity, have graphic dimensions match data dimensions, using standardised units, and keeping design elements from compromising the data. Balance can come from alternative representations (multiple clustering’s; confidence intervals instead of lines; changing timelines; alternative colour palettes and assignments; variable scaling) of the data in the same visualisation. Maintaining objectivity and balance is not a trivial effort and is easily unintentionally violated. Viewers and decision makers will eventually sniff out inconsistencies which in turn will cause the designer to lose trust and credibility, no matter how good the story.4 - Don’t CensorDon’t be selective about the data you include or exclude, unless you’re confident you’re giving your audience the best representation of what the data “says”. This selectivity includes using discrete values when the data is continuous; how you deal with missing, outlier and out of range values; arbitrary temporal ranges; capped values, volumes, ranges, and intervals. Viewers will eventually figure that out and lose trust in the visualisation (and any others you might produce)5 - Finally, Edit, Edit, Edit.Also, take care to really try to explain the data, not just decorate it. Don’t fall into “it looks cool” trap, when it might not be the best way to explain the data. As journalists and writers know, if you are spending more time editing and improving your visualisation than creating it, you are probably doing something right.By Alistair Malloy, Account Director, ContactAbilitySource: Harvard Business ReviewContactAbility specialises in customer acquisition and can reach more than 12 million prospects. To find out how we can help you reach new segments, why not drop me line at [email protected] today.

AbstractHistorical research methods and approaches can improve understanding of the most appropriate techniques to confront data and test theories in internationalisation research. A critical analysis of all “texts” (sources), time series analyses, comparative methods across time periods and space, counterfactual analysis and the examination of outliers are shown to have the potential to improve research practices. Examples and applications are shown in these key areas of research with special reference to internationalisation processes. Examination of these methods allows us to see internationalisation processes as a sequenced set of decisions in time and space, path dependent to some extent but subject to managerial discretion. Internationalisation process research can benefit from the use of historical research methods in analysis of sources, production of time-lines, using comparative evidence across time and space and in the examination of feasible alternative choices.IntroductionThe title of this focused issue is ‘About Time: Putting Process Back into Firm Internationalisation Research’. It would therefore seem obvious that historical research methods, whose primary concern is the role of time, would be at the forefront of the analysis. This is not necessarily the case, as these methods are neglected in internationalisation research, and in international business more generally. Historians face many of the same research problems that business researchers do—notably questions related to the analysis of process—but they have produced different answers, particularly in relation to the nature of causation. As a field, international business researchers need to question our research approaches more deeply.This paper seeks to examine the types of research approaches from history that might aid in a more rounded analysis of internationalisation. Issues of sequencing, path dependence, contingent choices and the evaluation of alternatives are all critical in the internationalisation process and are grist to the mill of historical research. An examination of historical research methods leads to a new approach to the concept of internationalisation itself.Historical Research Approaches: The Challenge of Different Underlying PhilosophiesIt is the difference in underlying philosophy between history and social science that presents the keenest challenge in integrating the temporal dimension with international business research. The contrast between the philosophy underlying history and that of social science—an issue for over a century (e.g., Simiand 1903)—is put by Isaiah Berlin:History details the differences among events, whereas the sciences focus on similarities. History lacks the sciences’ ideal models, whose usefulness varies inversely with the number of characteristics to which they apply. As an external observer the scientist willingly distorts the individual to make it an instance of the general, but the historian, himself an actor, renounces interest in the general in order to understand the past through the projection of his own experience upon it. It is the scientist’s business to fit the facts to the theory, the historian’s responsibility to place his confidence in facts over theories (Berlin 1960, p. 1 (Abstract).Footnote1Gaddis (2002) suggests that a particular contrast between history and social science is that history insists on the interdependence of variables, whilst mainstream social science methods rely on identifying the ‘independent variable’ which affects (causes) changes in dependent variables (Gaddis 2002, particularly Chapter 4). He suggests that this parallels the distinction between a reductionist view and an ecological approach (2002, p. 54), and that this arises from the social scientists’ desire to forecast the future (2002, p. 56). This also implies continuity over time—the independent variable persists in its causative effect(s). It is also connected with assumptions of rationality, which also is assumed to be time-invariant. Social scientists would counter that historians are theory resistant, at least to the kind of independent variable/rationalist/context-invariant reductionist theory that (perhaps stereotypically) characterises economistic approaches.Compromises are possible. Recognising sensitive dependence on initial conditions brings ‘narrative’ and ‘analysis’ much closer together, as does dividing time into manageable units—perhaps ‘short-term and long term’ or ‘immediate, intermediate and distant’ (Gaddis 2002, p. 95). Causality, interdependence, contingency and moderating variables are more manageable when the time-frame is defined. Research in history therefore demonstrates the importance of time, sequencing and process. It also highlights the role of individuals and their decision making. These elements are particularly important in examining entrepreneurship and individual (manager’s) decisions and their outcome in contexts such as the internationalisation of the firm.Footnote2How, then, would we recognise if genuinely historical work had been accomplished in internationalisation studies (or indeed in any area of the social sciences)? Tilley (1983, p. 79) gives us an answer:By ‘genuinely historical’, I mean studies assuming that the time and place in which a structure or process appears makes a difference to its character, that the sequence in which similar events occur has a substantial impact on their outcomes, and that the existing record of past structures and processes is problematic, requiring systematic investigation in its own right instead of lending itself immediately to social-scientific synthesis.History matters—the importance of historical effects in international business—is illustrated by Chitu et al. (2013), who document a ‘history effect’ in which the pattern of foreign bond holdings of US investors seven decades ago continues to influence holdings today. Holdings 70 years ago explain 10–15 % of the cross-country variation in current holdings, reflecting the fixed costs of market entry and exit together with endogenous learning. They note that fixed costs need not be large to have persistent effects on the geography of bilateral asset holdings—they need only to be different across countries. Evidence was also found of a ‘history effect’ in trade not unlike that in finance. The history effect is twice as large for non-dollar bonds as a result of larger sunk costs for US financial investments other than the dollar. Legacy effects loom large in international finance and trade.It is argued in this paper that time and place (context) do make a difference to the structure and process of an individual firm’s internationalisation, that past structures and processes do influence outcomes and that proper acknowledgement of context is vital in understanding and theorising internationalisation. It is further argued that attention to these issues leads to a new conception of internationalisation.Research MethodsReflecting on the purpose of his methods in his book Bloodlands, on Eastern Europe in the period 1933–45, the historian Timothy Snyder (2010, p. xviii) states that:…its three fundamental methods are simple: insistence that no past event is beyond historical understanding or beyond the reach of historical enquiry; reflection upon the possibility of alternative choices and acceptance of the irreducible reality of choice in human affairs; and chronological attention to all of the Stalinist and Nazi policies that labelled large numbers of civilians and prisoners of war.This paper follows similar principles. These are: (1) that the methods of history are appropriate to the study of the internationalisation of firms; (2) that choices and alternatives at given points of time are central to this process; (3) that the role of sequencing and time are central; and (4) that the comparative method is an aid to comprehension of the process of internationalisation.This paper now examines research methods widely used in historyFootnote3 that have the capability to improve international business research. These are: (1) source criticism (here it is argued that international business researchers are insufficiently aware of deficiencies in “texts”); (2) the analysis of sequences, including time series analyses and process theorising; (3) comparative methods (not exclusive to historical research); and (4) counterfactual analyses (which are currently less utilised than in previous periods of international business theorising). This followed by a proposed research agenda based on the two key methods of examining change over time and utilising comparative analysis.Source CriticismThe use of sources is as prevalent in international business as in history but they are often accepted uncritically. Gottschalk (1950), noting that few source documents are completely reliable, suggests that, ‘for each particular of a document the process of establishing credibility should be separately undertaken regardless of the general credibility of the author’. Given that reliability cannot be assumed, source criticism, as Kipping et al. (2014) argue, is fundamental to any historical research.The trustworthiness of an author may establish a basic level of credibility for each statement, but each element must be separately evaluated. This requires questioning the provenance of the text and its internal reliability (Kipping et al. 2014)—including, importantly, attention to language translation issues if relevant. This leads to the important checks brought about by triangulating the evidence. Triangulation requires the use of at least two independent sources (Kipping et al. 2014). This principle is utilised in international business journals by the requirement that both elements of a dyadic relationship are needed to cross check each other. Examples include licensor and licensee, both partners in a joint venture, parent and subsidiary in a multinational enterprise. The question of how far these are independent sources also needs careful investigation. Documents or statements addressed to different individuals and institutions may serve a variety of purposes. Those addressed to powerful individuals, groups or institutions may be intended for gain by the sender. Interviews may be designed to impress the interlocutor. The purpose of the document needs to be explicated. Documents may be designed for prestige, tax minimisation, satisfaction of guarantees (by government, sponsors or creditors) or to cover deficiencies in performance. The historian’s craft is, in part at least, to expose fraud and error (Bloch 1954).Source criticism includes evaluating what is not present in archives, not just what is. Jones (1998) points out that the company archives many analysts require often do not survive—those that involve statutory obligations often do, but those involving high-level decision making, such as Board papers, often do not. He points out that ‘issues of capabilities, innovation and culture will necessitate looking at what happens “lower down” within a firm’s structure’ (Jones 1998, p. 19). Further,The study of intangibles such as the knowledge possessed within a firm, flows of information, and the corporate culture—and how all these things changes over time can involve a very wide range of historical record far removed from documents on strategies… Oral history—of staff employed at all levels—is of special use in examining issues of culture, information flows and systems (Jones 1998, p. 19).These issues—intangible assets, strategy, culture and decision making in the face of imperfect information—are crucial in international business strategy research.In addition to criticisms based on material that exists in ‘the archive’, we need to recognise that the archive is the result of a selection process and therefore that excluded material may be important.Footnote4 The selection process may be biased towards particular nations, regions, races, classes, genders, creeds, political groupings or belief systems. This is a key theme of ‘subaltern studies’ growing out of South Asia, and particularly India, in imperial times (Ludden 2001). The clear implication of these studies is that the colonial era archive was compiled by the colonial (British) administrators and this presents a largely pro-Imperial bias. However, it is also true that among the dispossessed voices, some were privileged (e.g., the Congress Party spokespeople) and others selected out. The lineage of subaltern studies leads us through Gramsci (1973) to postmodern views of the text: Derrida (1994), Foucault (1965), Barthes (2005). As well as not ‘hearing’ particular groups, the archive records may not cover particular questions or issuesFootnote5 (see also Belich 2009 Footnote6; Decker 2013; Moss 1997).Analysing Sequences, Time Series and ProcessesThere are a number of important techniques in historical research which are useful to international business scholars in examining process, sequence, rhythm and speed—all of which are important in internationalisation. As Mahoney points out (2004, p. 88), ‘Causation is fundamentally a matter of sequence’. This is a problem addressed in economics as ‘Granger causality’ (1988). The critical question is not data access, but careful theorising. Sequence and duration arguments attempt to pick up sensitivity to time and place.Process analysis holds out the possibility of integrating the time dimension into the internationalisation of firms. Process research, which is contrasted to ‘variance paradigms’, pays particular attention to the sequencing of events that take place within cases (Welch and Paavilainen-Mantymaki 2014). Events, not variables, are the crucial writ of analysis and capturing multiple time points builds narrative, event studies and panel data analyses. In combination with variance approaches, process analysis has the potential to explain the effects of context (place) and time in internationalisation. The critical task is the identification of the linking mechanisms that connect cause and effect. This requires connecting qualitative data evaluation with experimental reasoning. It is also a useful check on spurious statistical relationships (Granger and Newbold 1974). Easterlin (2013) argues that cross-sectional relationships are often taken to indicate causation when they may merely reflect historical experience, i.e., similar leader–follower patterns for variables that are causally unrelated. This is particularly the case when similar geographic patterns of diffusion are captured by the data—as may well be the case when studying the internationalisation of firms. This may reflect the fact that one set of (national) firms get an early start whilst others play catch-up.We must, however, beware of ‘ingrained assumptions about historical periodization where mere temporal succession is insufficiently distinguished from historical explanation’ (Gregory 2012, p. 9). This provides a connection to ‘path dependence’ and sensitivity to initial conditions. Careful examination of relevant data allows analysts to identify reactive sequences ‘whereby an initial outcome triggers a chain of temporally ordered and causally connected events that lead to a final outcome of interest’ (Mahoney 2004, p. 91).Page (2006), however, shows that path dependence describes a set of models, not a single model. Forms of history dependence can be divided between those where outcomes are history dependent and those in which the equilibria depend on history. Path dependence requires ‘a build-up of behavioural routines, social connections, or cognitive structures around an institution’ (p. 89). Page shows that there is a variety of types of path dependence, each of which can be precisely defined, and that it is insufficient to cite ‘increasing returns’ as evidence of path-dependent processes. The consequences for process research on internationalisation are profound and require researchers to be as precise as possible, when asserting path dependence, to evidence its roots and specify their impact on future trajectories. Jackson and Kollman (2010) build on Page’s definitions and suggest ‘If social scientists use notions of path dependence, they should have clearly articulated definitions and criteria for what constitutes a path dependent process’ (p. 258): ‘Any such formulation must be able to explain how the effects of initial and early outcomes are maintained over long periods of time and continue to be observed in current outcomes’ (p. 280). This is far stronger than a simple statement that ‘history matters’. Path-dependent sequences raise important theoretical issues and thereby contribute to a further and deeper round of understanding; as with quantitative analysis we need to be constantly attentive to sources of bias (Nickell 1981).Understanding sequences entails additional complexities. Brown (2012, p. xxii) points out that choosing the periodicity (start and end points of data collection and investigation) can risk coming to foregone conclusions and ‘a deceptive teleology’:Two aspects of history are particularly important for historians: propulsion and periodization. The first concerns the forces that promote change. The second involves mental architecture: the chronological framework within which we set out history. Since all periodization presumes a theory of change, these are linked theoretical properties (Green 1993, p. 17).Propulsion and periodization—change and classification—are ultimately constructs and need to be placed both within a theoretical framework and a given context of time and place. This is a challenge to international business research which is often insufficiently theoretical and contextualised.International business studies need to be sensitive to the period of study. Laidler (2012, p. 5) advises,The past may be the only source of data against which economic hypotheses can be tested or calibrated, but data never speak entirely for themselves. They need to be interpreted through a theory. When the only theory deemed suitable for this purpose embodies itself as part of its own structure, even on an ‘as if’ basis, then that structure is inevitably projected onto the past, and other perspectives on the historical record are obscured.This suggests that a fundamental problem is that international business research is often inadequately theorised. Theories which stand up to testing in many historical periods are more robust than those that do not. Jones and Khanna (2006, p. 455) see history as an important source of time series data: ‘historical variation is at least as good as contemporary cross-sectional variation in illuminating conceptual issues’. Although it should be noted that many historians are sensitive to the limits of generalisation across historical periods. Burgelman (2011) sees longitudinal qualitative research being situated between history as ‘particular generalization’ (Gaddis 2002) and reductionism; that is, ‘general particularization’.Longitudinal research and good process research draw on both history’s narrative methods and statistical and mathematical models. Such longitudinal studies clearly need rigorous methods from both history and statistics. A relevant example is Kogut and Parkinson (1998), who examine the adoption of the multidivisional structure, testing Chandler’s (1962) core thesis over a long time period, ‘analysing history from the start’. Despite the difficulties of compiling archival data for a large sample of firms, the authors are able to test an innovative methodology on diffusion histories of the ‘M-form’ from the period beginning in 1950. They use a hazard model (of adopting the M-form) with imitation and firm covariates that predict adoption rates. The sample (62 firms) is large enough to be split into ‘fast’ and ‘slow’ adopters of this organisational innovation and a comparison of the difference between the two samples enables the authors to confirm Chandler’s historical account and to point to some qualifications concerning flows of information between firms which meant that proximate firms were more likely to adopt the M-form structure. Imitation effects by firms located in the same industry and firms with links to M-form adopters also seemed significant.The Kogut and Parkinson (1998) study is a successful example of ‘History Meets Business Studies’ (p. 257) and also of the application of techniques of organisational demography. This approach has also been successfully applied to the birth and death of subsidiaries and foreign market entry strategies (Kogut 2009). Historical studies have established an important precedent of ‘the importance of sampling on founders rather than survivors and of the effects of age on mortality’ (Kogut 2009, p. 721). Shaver (1998) pointed out that many previous studies had not accounted for endogeneity and were subject to self-selection bias but that such effects could be corrected for using a methodology that factors in the full history of entries, taking account of strategy choice based on firm attributes and industry conditions. Strategy choice is endogenous and self selected based on these conditions and modelling has to account for this. Concepts such as the ‘liability of newness’ (Stinchcombe 1965) and the (in International Business) celebrated ‘liability of foreignness’ (Zaheer 1995 after Hymer 1976) examine diffusion over time. There are, however, as Kogut (2009) points out, several unresolved challenges in the organisational demography literature. First, self-selection bias is still unresolved in that successful firms are more likely to venture abroad. Second, because of unobserved variables (such as the quality of the firm) heterogeneity remains in any sample of firms and any heterogeneous population can be shown to suffer ‘liability of newness’. Controls for heterogeneity, of course, are a palliative (e.g., size of firm) but it is difficult to control all such variation. A careful specification of the growth process of firms (despite Penrose (1959) and her heirs) still eludes us.In concluding this section, it should be mentioned that cliometrics, or the measurement of history (also called the New Economic History) is not uncontroversial (Diebolt 2012). ‘Hypothetico-deductive models’ (utilising the counterfactual position) using ‘propositions contrary to the facts has not escaped criticism’ (Diebolt 2012, p. 4), and they contrast with the inductive position of the German historical school (Grimmer-Solem 2003). The economistic tradition of ‘opportunity cost’ whereby the true costs of any action is the best alternative foregone, provides a firm philosophical link between economics and the counterfactual as discussed below.Comparative MethodsThe comparative method is of great importance throughout the social sciences. There are three classic comparators in social science research: across space, across time, and against a carefully specified counterfactual state of the world (Buckley et al. 1992). International business research has traditionally focused on just one of these—across space. Historical research specialises particularly in comparisons across time, but also has lessons in spatial comparison and in counterfactual analysis.Research that depends on ex post statistical adjustment (such as cross-country regressions) has recently come under fire; there has been a commensurate shift of focus towards design-based research—in which control over confounding variables comes primarily from research design, rather than model-based statistical adjustment (Dunning 2012, p. xvii).The design of a randomised controlled experiment has three characteristics (Freedman et al. 2007, pp. 4–8):1.The response of the experimental subjects assigned to receive a treatment is compared to the response of subjects assigned to a control group. This allows comparisons of outcomes across the two groups.2.The assignment of subjects to treatment and control groups is done at random—a coin toss, for example. This establishes ex ante symmetry between the groups and obviates the existence of confounding variables.3.The manipulation of the treatment or intervention is under the control of the experimental research. This establishes further evidence for a causal relationship between the treatment and the outcomes (Dunning 2012, p. 15).Crucially most extant research utilises ‘as if random’ assignment of interventions rather than ‘natural’. Its success depends upon the plausibility of ‘as if random’, the credibility of models and the relevance of intervention. ‘Qualitative evidence plays a central role in the analysis of natural experiments’ (Dunning 2012, p. 228). This is because an investigation of the causal process is critical (Collier et al. 2010) in avoiding ‘selecting on the dependent’ variable by analysing only those cases where causal-process observations appear to have played a productive inferential role. Indeed, Dunning (2012, p. 229) suggests that a future research agenda should focus on developing a framework that distinguishes and predicts when and what kinds of causal-process observations provide the most useful leverage for causal inference in natural experiments. Results however may be very particular and parochial because of the limited availability of natural experiment possibilities (Yin 2014). Experimental results, therefore, come at a price.The price for success is a focus that is too narrow and too local to tell us ‘what works’ in development, to design policy, or to advance scientific knowledge about development processes (Deaton 2009, p. 426).Comparison across places by geographic area or space is frequent in international business research (across nations, cultures, regions, areas, cities). The multinational enterprise is an excellent laboratory or natural experiment because it holds constant the single institution of the firm but varies the location of study. The division, and the later unification, of Germany allowed Kogut and Zander (2000) the opportunity to conduct a natural experiment by comparing the two sections of the Zeiss Company under socialism and capitalism. The experimental design measured the dependent variable (outcome)—the technological output of the two firms proxied by patents—under ‘treatments’ offered by the different economic contexts of the two different economic systems. This unusual design substituted for a random sample by eliminating the effects of extraneous factors and isolating the effects of the treatment variable on the ‘same’ firm. Comparative management experiments can be done by comparing company A’s subsidiary in Vietnam with its subsidiary in Virginia. This is the stock-in-trade of many international business experiments and was utilised by Hofstede (1991, 1997, 2001), whose work on culture held the host company (IBM) culture constant whilst varying the purported national cultural responses of the firm’s employees.Comparisons across time, holding place constant, are the essence of ‘history’. They give rise to notions of ‘growth’, ‘progress’, ‘design’, ‘loss’. Chandler (1984) describes his method as the comparison of detailed case studies to generate ‘non historically specific generalizations’. Research in business history has challenged the Chandler thesis that managerial capitalism is universally becoming the norm (Whittington 2007; Rowlinson et al. 2007). Hannah (2007) illustrates the use of comparative historical data to challenge the received wisdom. As noted elsewhere in this piece, such comparisons are fraught with danger unless carefully conducted. Meanings of documents, words, artefacts and statements vary according to different point of time usage and must be carefully analysed as best practice historical research dictates. As Ragin says (1987, p. 27),many features of social life confound attempts to unravel causal complexity when experimental methods cannot be used… First, rarely does an outcome of interest to social scientists have a single cause… Second, causes rarely operate in isolation. Usually, it is the combined effect of various conditions their intersection in time and space, that produces a certain outcome… Third, a specific cause may have opposite effects depending on context.These three factors—multiple, interacting causes, differential by context—are the very essence of international business research. Because of the difficulty of designing natural experiments International business research has emphasised statistical control in its methods. Ragin (1987) points out that statistical control is very different from experimental control.Footnote7 Statistical control does not equate to experimental control: ‘the dependent variable is not examined under all possible combinations of values of the independent variables, as is possible in experimental investigations’ (Ragin 1987, p. 61). Ragin presents a Boolean approach to qualitative comparison (after George Boole (2003) [1854] and also known as the algebra of logic or algebra of sets). Kogut (2009) shows the relevance of this approach to international business research (see also Saka-Helmhout 2011). A recent development of the use of Boolean algebra in international business is the application of fuzzy-set qualitative comparative analysis in the assessment of different models of capitalism (Judge et al. 2014).Qualitative comparisons are of the essence in (historical) international business research. As Kogut (2009) shows, a proposition based on a three-cause explanation in order to avoid simplifying assumptions at the outset requires a truth table of 23 or eight combinations as in Fig. 1. Thus, to achieve experimental control, the investigation needs eight cases with the characteristics shown in the table in order to determine which combination of causes (A, B, C) determines the outcome (1). (See Ragin 1987, particularly Chapters 7 and 8.) Thus historical comparative data can focus our attention on cases as wholes and to explore the combinatorial complexities of causation (Ragin 1987, p. 171).Footnote8 It is also suggestive of the answer to the perennial question of how many cases are needed to satisfy a proposition. For instance, it might be suggested that the rise of Japan was due to (1) lifetime work contracts, (2) company unions and (3) the Keiretsu system. In order to prove or disprove the argument, the bottom line where all three proposed casual factors are present must be contrasted with situations where none of them are present (the top line) where only one of the proposed causes is present and where combinations of two causes are present. This enables the analyst to identify necessary and sufficient conditions. In a three cause theoretical proposal, a total of eight cases are needed.Fig. 1Truth table for a three cause propositionHistorical Research Approaches to the Analysis of InternationalisationHistorical research methods and approaches can improve understanding of the most appropriate techniques to confront data and test theories in internationalisation research. A critical analysis of all “texts” (sources), time series analyses, comparative methods across time periods and space, counterfactual analysis and the examination of outliers are shown to have the potential to improve research practices. Examples and applications are shown in these key areas of research with special reference to internationalisation processes. Examination of these methods allows us to see internationalisation processes as a sequenced set of decisions in time and space, path dependent to some extent but subject to managerial discretion. Internationalisation process research can benefit from the use of historical research methods in analysis of sources, production of time-lines, using comparative evidence across time and space and in the examination of feasible alternative choices.https://link.springer.com/article/10.1007/s11575-016-0300-0/figures/1As Mahoney (2004, p. 82) says, ‘comparative-historical methodology offers tools well adapted to the analysis of necessary and sufficient causes’. This need not rely on deterministic logic because necessary and sufficient causes can be expressed in a probabilistic framework. This also aligns with expressing variables in a continuous rather than in a dichotomous fashion. These techniques are helpful, as Saka-Helmhout (2011) points out, in analysing cross-case analyses of bundles of conditions, in particular in the identification of patterns of regularities and differences. The methodological stream (and theoretical underpinnings) of comparative historical research therefore lead to the more systematic pinpointing of necessary and sufficient causes in international business case research. For applications to management research, see Oz (2004).Counterfactual AnalysisThe third classic comparator is the ‘alternative position’. The counterfactual question—‘what if?’—is a particular type of thought experiment designed to elucidate causality. It is widely (if sometimes unwittingly) used in economics where ‘opportunity cost’ (the real cost of resources) is defined as the cost of the next best alternative foregone. The ‘alternative position’ and its specification have long been a particular problem in international business research—classically in the analysis of foreign direct investment (FDI). What would have happened in the absence of a particular foreign investment? (Reddaway et al. 1968; Steuer 1973; Cairncross 1953; Buckley et al. 1992, p. 36). Jones and Khanna (2006, p. 464) say that a ‘comparative approach also gets at the spirit of specifying counterfactuals’.Historians have long had to face this issue. Several variously sophisticated attempts have been made to try to answer the question of what would (might) have happened had some of the crucial turning points of history turned out differently (Beatty 2011; Ferguson 1997; Cowley 1999; Lebow 2014). Lebow (2012) points out that counterfactuals are frequently used in physical and biological sciences to develop and evaluate sophisticated, non-linear models. The counterfactual has to be well defined and this requires a thorough analysis and presentation of the context of the alternative position. Such thought experiments are perhaps history’s closest comparator to a laboratory experiment (Gaddis 2002, p. 100)—although see the section on natural experiments in the social sciences above. The counterfactual counteracts the static nature of much historical analysis by focusing upon dynamics and processes.Durand and Vaara (2009, p. 1245) have examined the role of counterfactuals in explicating causality in the field of business strategy. They argue that:Counterfactual history can add to our understanding of the context-specific construction of resource-based competitive advantage and path dependence, and causal modelling can help to reconceptualize the relationships between resources and performance.The role of counterfactual reasoning in organisation studies was also explored in two issues of Management & Organizational History [volume 3(1) 2008 and volume 4(2) 2007]. MacKay (2007) pointed out that counterfactuals can guard against path dependencies in both structure of organisations and perception. Counterfactuals illustrate that the world could be other than it is and help the analyst to evaluate different possibilities including decisions and their outcomes. Thus socio-economic and technical path dependencies can introduce rigidities and cognitive or psychological path dependencies can impair organisational learning. Toms and Beck (2007) criticise received counterfactuals (on the Lancashire cotton industry) as suffering from the problems of teleology and hindsight that occur when the counterfactual is contaminated by ex post knowledge of the outcome (Maielli and Booth 2008).Footnote9 Toms and Beck (2007, p. 315) attempt to construct a history ‘from the perspective of decision making entrepreneurs as embedded historical actors’. This is surely the model for internationalisation researchers, when examining past decisions and their outcome.The key, as Leunig (2010) points out, is to be explicit in specifying the counterfactual position as this provides more evidence than a simple judgement on the impact of (say) a critical innovation. Fogel (1964) in finding that agricultural land opened up by the railroads might otherwise have been undeveloped, examined the possibility of an alternative network of canals.Footnote10 This was done not by simple perusal of a map but by examining detailed typographical maps, as a canal builder would do. A limitation of counterfactual analysis is the ability to go on to use comparative analysis because the carefully constructed counterfactual is often locationally or temporally specific. For instance, although in Fogel’s counterfactual, canals could have done most of the work of railroads, he assumed away the vagaries of the weather—in the Northeast of the US at least, canals would have been frozen for at least 4 months of the year.Footnote11 An excellent example of a carefully constructed counterfactual is Casson’s construction of the (optimal) counterfactual railway network (complete with timetable) for the UK taking account of network performance, the physical geography of the UK, Victorian urbanisation and traffic, engineering constraints, regulation, institutional and political constraints (Casson 2009).The counterfactual has an important place in the development of international business theory as analyses of the impact of FDI on host and source countries have been cast in the terms of the ‘alternative position’—what would have happened in the absence of FDI. Foreshadowing the current debate an offshoring and outsourcing, earlier literature on the impact of FDI following Hufbauer and Adler (1968) identified three polar ‘alternative positions’ (Buckley and Artisien 1987, pp. 73, 78–79, 80).The classical assumption assumes that FDI produces a net addition to capital formation in the host country but a similar decline in capital formation in the source country. This is equivalent to the assumption that FDI substitutes for exports. The reverse classical assumption assumes that the FDI substitutes for investment in the host country but leaves investment in the source country unchanged. This is equivalent to ‘defensive investment’ where the source country firm cannot penetrate the target market via exports and would lose the market to host country firms in the absence of FDI. The anti-classical assumption is that FDI does not substitute for capital investment in the source country, neither does it reduce investment by host country firms. Consequently FDI increases world capital formation (in contrast to the other two assumptions where world capital formation is unchanged).Anticlassical conditions are most likely when host country firms are incapable of undertaking the projects fulfilled by FDI. Each of these assumptions is static and rigid—not allowing for a growth of demand, perhaps from the ‘presence effect’. An organic model, postulating that FDI substitutes for exports in the short run, but in the long run substitutes for rival investment is more likely. Hood and Young (1979) pointed out that the relationship between FDI and exports needs to be fully specified in any such examination of effects of FDI.This debate needs to be updated as it predated studies of MNEs’ foreign market servicing strategies and motives other than market-seeking. A parallel move away from economic counterfactuals towards specifying alternative decision making scenarios for decision-making entrepreneurs would be a step forward here (Toms and Beck 2007). A further important question here concerns the identity of the decision maker and whether ownership (foreign versus domestic) matters. As concern with the employment impact of FDI at home and abroad grows, counterfactual analysis is useful in specifying the myriad impacts (employment among them) of modern MNEs.The ‘historical alternatives approach’ (Zeitlin 2007) is a specifically business history variant of counterfactual analysis. The historical alternatives approach is promoted by Zeitlin (2007) as ‘against teleology and determinism’. The approach suggests that plasticity of technology has been underrated, leading to technological determinism of a particularly narrow type. Strategic action in the face of uncertainty, mutability and hedging strategies gives a far wider range of outcomes than conventionally allowed for and ‘the market’ is dogmatically and narrowly the result of historical construction. Size of firms, strategic action, industry imperatives and rationality are too glibly taken as determining factors and the result is an excessively pre-determined view of business choices. While it is certainly the case that many analyses based on historical reasoning are unduly constrained in terms of other potential outcomes, alternative futures have to be specified extremely carefully and constraints that are to be lifted on outcomes must be spelled out and the degree to which they are assumed to be not binding requires extensive and meticulous research.In internationalisation research, alternative positions are important concepts in the development of the process. The decisions that key managers make can be evaluated by presenting them with alternative scenarios, as Buckley et al. (2007) did. This is usually, for practical and cost reasons, a point-of-time rather than a continuous exercise even though, in principle, these choices could be presented to managers frequently throughout the internationalisation process. There are examples of where a single investment is considered as a ‘Go/No go’ decision and others where several alternative investments are simultaneously considered (Buckley et al. 1978). In many cases firms will themselves investigate alternative scenarios even if this is done informally rather than through ‘scenario planning’.DiscussionTable 1 shows the areas where the four key methods identified above have been successfully applied in international business.Table 1 The use of historical research methods in international businessHistorical Research Approaches to the Analysis of InternationalisationHistorical research methods and approaches can improve understanding of the most appropriate techniques to confront data and test theories in internationalisation research. A critical analysis of all “texts” (sources), time series analyses, comparative methods across time periods and space, counterfactual analysis and the examination of outliers are shown to have the potential to improve research practices. Examples and applications are shown in these key areas of research with special reference to internationalisation processes. Examination of these methods allows us to see internationalisation processes as a sequenced set of decisions in time and space, path dependent to some extent but subject to managerial discretion. Internationalisation process research can benefit from the use of historical research methods in analysis of sources, production of time-lines, using comparative evidence across time and space and in the examination of feasible alternative choices.https://link.springer.com/article/10.1007/s11575-016-0300-0/tables/1The application of the above principles of method suggests that a new international business history is called for that relies on the two key principles of examining change over time and using the comparative method. If we accept that the study of history is about change over time, then international business history needs to take a long-run view of change and of the role of multinational firms in large scale social and economic development. This presents a major challenge in view of the material in archives. Company archives cover the world from the point of view of the (single) company. In international business this represents only one actor in a complex drama. The roles of host and source countries are perforce omitted. It behoves the writers of international company histories to take a wider perspective than just the company’s viewpoint. In approaching the comparative method, the spatial comparison encompasses the international dimension but changes over time require a longer run view than most company histories allow for. Comparing the role of a company in the eighteenth century with the nineteenth is not often possible from a single company’s archives (and it can be argued, were this to be so, we would be dealing with an outlier). In short, the writing of international business history needs to be more imaginative, not only in method but also in its engagement with wider theory and technique.It is equally the case that international business theory and methods can enrich historical research.Footnote12 In addition to the Chitu et al. (2013) examination of ‘history effects’ in international finance and trade, international business can be focused on global history in the way that Bell and Dale (2011) analysed the economic and financial dimensions of the medieval pilgrimage business (using contract and network theory and the analysis of saints’ shrines as business franchise, under an umbrella brand of the Universal Catholic Church).Historical Research Approaches and the Internationalisation ProcessThe question of how firm internationalisation evolves over time is best answered by the careful use of historical research methods duly adapted for the context of international business research (Jones and Zeitlin 2007) . The temporal dimension of the internationalisation process needs to be centre-stage and critical decision points and turning points need to be mapped on a timeline and against feasible alternatives. As extant international business research has shown (Buckley et al. 2007), managers are only partly guided by rational processes and context and contingency play roles in determining the final decisions. If we know when these critical decisions are made, then it becomes much easier to understand the factors that were in play in the decision makers’ minds. It is frequently remarked that key ‘events’ (a coup, the launch of a rival’s product, a competitive market entry) were the triggers for investment (or non-investment) decisions and a timeline of events—a mapping of process—can be a key to understanding. The temporal sequencing of ‘events’ in the internationalisation process is clearly vital to comprehension of the firm’s strategy and decisions. As well as time, at a given place, we need to add place at a given time for all these events. Thus a double comparative across time and space is necessary for a rounded understanding of outcomes.Process research also needs to comprehend simultaneous processes as there is not just one sequence of events in internationalisation; rather, there are multiple. Selection of processes to track has to be theoretically driven. Process research cannot stand apart from the theory, it is has to be fully engaged with the appropriate theories and to feed back into them (Paavilainen-Mantymaki and Welch 2013). This is fully in accord with Pettigrew’s (1997) approach to processual analysis. Moreover, as Pettigrew (1997, p. 340) says, ‘The time quality of a processual analysis thereby lies in linking processes to outcomes’. Linking internationalisation processes to outcomes (performance) is a missing element in our understanding—the results of the managerial decisions form an essential element of a feedback loop to further internationalisation.The four generic methods applied in historical research outlined here—source criticism, time series analysis, the use of comparative methods and counterfactual analysis—are all vital in constructing a proper process analysis of the internationalisation of the firm (or of a firm’s internationalisation). It is fundamental that a critical appraisal of all sources be undertaken, be they company statements, archives, documents or interviews. Wherever possible these should be triangulated against other sources. Nothing should be taken on trust and, if it has to be, this should be clearly stated. Wherever possible, a timeline of relevant events should be made in order to sequence the decision processes and outcomes. The construction of multiple timelines—of different managers, sub-units of the firm and other key actors (such as competitors, agents, customers, suppliers, governmental bodies, support agencies) should be compared and contrasted. The coincidence in time of actions by interested parties is prima facie evidence of joint causality. These techniques can be extended by the use of comparisons not only in time but in space. The geographical mapping of actions and outcomes gives richness to the process analysis. The transmission and impact of decisions from one geographical point (e.g., headquarters) to another (a subsidiary, a potential takeover victim), the time-lags involved and the reaction time of the recipient are all vital in understanding internationalisation. Counterfactual analysis, too, can be a useful tool. Firms often approach internationalisation decisions with a number of contingencies. If they cannot acquire foreign firm X, should they turn to Y, or to a greenfield venture instead? These alternatives are useful to know and it may be possible to construct feasible alternative internationalisation paths.In summary, historical research methods and approaches provide a research design for internationalisation process studies that enhance the depth of understanding by incorporating concrete timelines, alternatives and decision processes.A New Concept of InternationalisationThe new concept of internationalisation that emerges from a consideration of the light shed by historical research on managerial processes is that internationalisation is the outcome of a set of decisions, dependent on context and previous decisions, considering alternative locations, entry and development methods in a choice set of time and space. In these sequential decisions, knowledge of past decisions and their outcomes plays a part in the next round of decisions. Hence companies can create ‘vicious circles’ or ‘virtuous circles’ in their internationalisation processes. In this sense, a knowledge of history of the company making the decision and of similar companies making comparable decisions can be valuable for the manager. History matters to decision-makers as well as analysts. The question of when to take history into account and when to ignore it and ‘take a chance’ is the essence of managerial judgement (and of ‘real options theory’—see Kogut and Kulatilaka 2001; Buckley et al. 2002). Those who make regular correct calls will develop a ‘track record’ and be valued accordingly. Thus both the weight of history and the judgement of successful individuals will build path dependence into the internationalisation process.The research approach formulated in this article encompasses the Uppsala approach to internationalisation (Johanson and Vahlne 1977, 2009) as a special case. The Uppsala approach has no explicit role for time. It explains market entry as a sequence which is determined by psychic proximity to the source country in a loose path dependent fashion. A more careful specification of the relationship between market entry and psychic distance and an explicit acknowledgement of the role of time would allow a fully historical analysis of market entry sequencing in the Uppsala tradition.Conclusion: The Response to the Challenge of Historical ResearchThe last sentences of Butterfield’s (1965, p. 132) The Whig Interpretation of History encompasses the challenge of historical research methods: ‘In other words, the truth of history is no simple matter, all packed and parcelled ready for handling in the market-place. And the understanding of the past is not so easy as it is sometimes made to appear’. Historical research methods can help international business researchers to be more questioning, analytical and critical and to think laterally in terms of alternative states of the world, different choices and outcomes. There is a justifiable argument that international business research is insufficiently critical of ‘texts’ in all their forms—company statements, official statistics, interviews with managers among them—and historical research has a number of techniques for improving the penetration of meaning behind texts, as this piece has shown.In using research methods derived from history we must always factor in ‘Contingency, choice and agency’ (Clark 2012, p. 362). We should also remember that history interacts with geography—context is crucial. To quote the historian Peter Brown’s work on wealth in the early Christian period, ‘A true history of Latin Christianity requires an unremitting sense of place’ (Brown 2012, p. xxii). A good example relevant to international business is the combined use of historical, geographical and sectoral data by Becuwe, Blancheton and Charles (2012) in analysing the decline of French trade power in the ‘first globalization’ of 1850–1913. A sense of place involves understanding both the global macro context and the particular location.There is an awkward disjunction between traditional historical research and hypothetico-deductive modelling. This is paralleled by the lack of integration between quantitative and qualitative methods in international business research, arising from their philosophical bases in positivism and subjectivism. The careful integration of historical research methods into international business provides us with one channel of progress towards a more complete understanding of the phenomena of international business.In the particular case of the analysis of the internationalisation of the firm, historical approaches place managerial judgement central to the process. Such judgement, however, is constrained by context. This context is both temporal and spatial. ‘When’ and ‘where’ matter in both an individual decision and the analysis of decisions. The use of the plural here implies sequencing and therefore a focus on process. The choice set faced by the manager is constrained by what has gone before—by history. This does not determine the next decision in the sequence but it influences it. The new concept of internationalisation is that sequence, not events, are at the heart of the international growth of the firm, that spatial issues (including psychic distance to a potential host country) must be accounted for, and that past decisions constrain outcomes.On the importance of methodology (in international business as elsewhere) we can end with a quote from Kogut (2009, p. 711): ‘It is one of the best-kept secrets of research that a methodological contribution is the most powerful engine for the replication and diffusion of an idea’.Noteshttp://1.It is suggested by Cannadine (2013, p. 9) that academic histories are often responsible for emphasising divergences rather than similarities: ‘Most academics are trained to look for divergences and disparities rather than for similarities and affinities, but this relentless urge to draw distinctions often results in important connections and resemblances being overlooked’. The contrast between history and social science has been an issue for over a century (see Simiand 1903).2.See also the debate on the ‘historic turn’ in organisation studies (Clark and Rowlinson 2004).3.Stephanie Decker (2013, p. 6) identified four features that ‘clearly distinguish historical from non-historical research designs’. These are: reconstruction from primary sources (empirical rigour), thick contextualisation in time and space (empirical at times, theoretical rigour), periodization (theoretical rigour when combined with strong historiography) and historical narrative (accessibility, empirical and theoretical rigours).4.For an excellent review of the use (and extension) of archive material see Wilkins and Hill (2011) ‘Bibliographical Essay’ pp. 445–458.5.See also Schwarzkopf (2012).6.Belich notes, of trying to identify ‘emigrants’ and their opinions: ‘This problem of the silent majority is, of course, endemic in the social history of ideas. The standard solution, not one to be despised in the absence of alternatives, is to pile up available examples of opinions in the vague hope that these are typical. Once possible refinement is the analysis of the conceptual language of substantial groups of lesser writers who are trying to persuade their still-larger target audience to do something’ (Belich 2009, p. 148 f.).7.‘In most statistical analyses, the effect of a control variable is its average effect on the dependent variable, across all cases, not of the effects of other variables. The subtraction of effects central to statistical control is a purely mechanical operation predicted on simplifying assumptions. It is assumed in multiple regression, for example, that a variable’s effect is the same in each case—that a one-unit change in an independent variable has the same effect on the dependent variable regardless of context, that is, regardless variable’s effect by simple subtraction. The result is a dependent variable whose values have been “corrected” for the effects of one or more independent variables’ (Ragin 1987, p. 59).8.For a full discussion of varieties of comparative history, see Skocpol and Somers (1980).9.See Evans (2014) for a critical appraisal of counterfactuals.http://10.As a referee points out, Fogel was not posing the ‘what if’ question but rather ‘by how much less would the US economy have grown if there had been no railways’.11.I owe this point to Geoff Jones (personal communication 09.07.2013).12.Kobrak and Schneider (2011) make a call for a renewal of historical research methods in business history, ‘reviving some basic historiographical notions’ (p. 401).Following is the link for newly created space for getting all Indian government jobs updates. This space is managed from the student of Banaras Hindu University.Link…Following is the link of newly created You Tube Channel- “India tour”. Your one subscribe will make the US dollar, come into Indian Economy.Link…India TourThis is You Tube channel-India Tour. Basically, on this channel you see the all tourism place whatever we hear from any people. We know that looking anything live is the another thing but whenever we go somewhere then which kinds of things are popular on that area, that also matters. So, about the famous things of that particular criteria, you would be able to get information about that particular place. Except, the information about any tourism place in India, you will also also be able to know about the importance of that tourism centre and you will also be able to get the particular information about that tourism centre. Is You Tube channekl par aap sabhi log Bharat ke baare mein sabhi jankari ekatra kar paasyenge aur wo saari jankari Bharat ke prachalit jagahon ke baare mein hogi. Saath hi aap sabhi un tamam videos ko dekh paayenge, jin par unse sambamdhit jaankariyan hogi, jo bharat ke bhavishya ko prastut karta hai.https://www.youtube.com/channel/UCI0S7f2y_9C5IBkyRl5LyBgTeachmintRajas AcademyClassroom Id for student who want to join the class for Commerce (12th) from the teacher who is topper of CommerceID - 447168176

Curriculum for Bachelor of Technology in Information Technology at MNNITData Structures (III Semester CSE & IT 4L)SyllabusData Structure (CS1301)Prerequisite: C Programming, Basic Mathematics.Objective: Implementation of databases, designing efficient algorithms, memory management etc.Data structures provide the necessary data abstraction for the development of large software systems and their central role in software engineering. Data structure covers include sets, linked lists, stacks, queues, hash tables, trees, heaps, and graphs. Students are introduced to algorithms for searching, sorting, and data structure manipulation and learn the techniques to analyze program efficiency. Programming using recursion and dynamic data structures are covered.Course DescriptionThis course introduces the students fundamentals of data structures and takes them forward to software design along with the course on Algorithms. It details how the choice of data structures impacts the performance of programs for given software application. This is a precursor to DBMS and Operating Systems. A lab course is associated with it to strengthen the concepts.Course Outline (To be covered in 40 lectures)1. Introduction, Elementary Data Organization, Data Structure Operations, Algorithms Complexity, Time-Space Trade off (6)2. Arrays, Linked List, stacks and Queues (10)3. Tree, Binary tree, Search tree, Heap, B+ tree (12)4. Sorting methods, External Sorting/Searching, Hashing (8)5. Graphs (6)Text Books1. The Art of Computer Programming (Volume 1 and Volume 3) - D E Knuth,2. Data Structures Using C & C++, Langsam, Augenstein & Tenenbaum,3. Data Structures – A Programming Approach with C, Kushwaha & Mishra,4. R.L. Kruse, B.P. Leary, C.L. Tondo, “Data structure and program design in C”5. Fundamentals of Data Structures in C, by Ellis Horowitz, Sartaj Sahni, and Susan Anderson-Freed7Principles of IT Industry Management (III Sem CSE & IT 3L)SyllabusManagement of IT Industries (MS-1301)Prerequisite: NoneObjective: Competently employ broad-based analytical tools and computers for decision-making and system design, analysis and performance. Assume managerial and leadership roles in their chosen professional careers while working in multidisciplinary teams. Engage in continuous learning by seeking out opportunities for higher education or ongoing training related to their employment.Effectively adapt to the changing demands in workplace and are able to perform increasingly complex tasks, and tasks outside their field of expertise.Course DescriptionThis course introduces students the working and management of IT industries. The emphasis of the course will be on the skills and knowledge needed to understand and successfully manage an IT based organization. A central concept of the course is that there is a general framework for understanding management that applies to managers in all organizations-large or small, public or private, product-oriented or service-oriented.Course Outline (To be covered in 30 lectures)1. Introduction, Nature & Concept of Management; Managerial skills; Evolution of management thought; Concept of functional management; Management styles, Productivity measurement, productivity index, types of production system. (3)2. Human Resource Management: Definition and theories of Managing People for IT Industry, Human Resource Planning, responsibility assignment matrix, resource management, developing and managing the project team, Case Studies (6)3. IT Industry Supply Chain Management: Types, Business processes, Strategic, tactical, and operational decisions in supply chains, performance measures, inventory management, bullwhip effect, e-marketplaces, e-procurement, e-logistics, e-fulfillment, customer relationship management, web services, ERP and supply chains, Case Studies (6)4. IT Project Quality Management: Tools and techniques for quality control (Pareto Analysis, Statistical sampling, testing), process control, SQC control charts, single, double and sequential sampling, TQM. Case Studies (6)5. Environmental Issues, Pollution Control Acts, Green IT Practices, Establishing a Green IT Action Plan, techniques and technologies available to enable Green IT Case Studies6. Comprehensive Case studies: Any three from TCS, Cisco, Infosys, Wipro, Facebook, Accenture, Google, IBM, Microsoft etc (3)Text Books1. Managemenet :Global Perspectives, by Koontz and Weihrich2. Principles of Management by Prasad, L.M.,3. Environmental and Pollution Awareness by Sharma B.R.8Analog and Digital Electronics (III Semester CSE & IT 3L)SyllabusAnalog & Digital Electronics(CS-1303)Prerequisite: Basic circuits, Semiconductor devices, digital logic.Objective:Analog and Digital Circuits is an introductory course on circuit design that aims to develop a combination of design, analysis and experimental skills among the students. In addition, the course will help students understand mechanisms of sensing and actuation that are commonly used. The laboratory component will expose the student to topics in measurement and instrumentation.Course DescriptionThis course introduces the students fundamentals of basic electronics and takes them forward to digital circuits. The course provides introduction to (semiconductor) electronic devices. Conduction of electric currents in semiconductors, the semiconductor p-n junction, the transistor. Analysis and synthesis of linear and nonlinear electronic circuits containing diodes and transistors. Biasing, small signal models, frequency response, and feedback. Operational amplifiers. Further, this course covers combinational and sequential logic circuits. Topics include Boolean algebra, logic families, MSI and LSI circuits. This is an precursor to Computer Organization course. A lab course is associated with it to strengthen the concepts.Course Outline (To be covered in 40 lectures)1. Introduction to semiconductor physics. Diode, Zener Diode, Diode as a switch, Rectifier, Clipping and Clamping Circuits (6)2. Bipolar Junction Transistor, Biasing of Transistor, Transistor configurations, Transistor as an Amplifier, Transistor as a Switch. (8)3. Introduction to FET, MOSFET, Operational Amplifier, SCR, UJT and other devices (6)4. Introduction to Boolean Algebra and fundamental theorems, Basic Logic Gates, Realization of combinational circuits using universal gates, Gate level minimization (8)5. Important Digital Circuits Decoder, Multiplexer, PLA, ROM, RAM (4)6. Flip Flops, Design of Sequential Circuits, Registers, Counters (8)Text Books1. Digital Design by M Morris Mano, M D Ciletti2. Integrated Electronics by Millman & Halkias3. Electronic Principles by Malvino4. Foundations of Analog and Digital Electronic Circuits by Anant Agarwal and Jeffrey Lang9Foundations of Logical Thought ( III Semester CSE & IT 4L)SyllabusFoundations of Logical Thought (CS-1304)Prerequisite: NoneObjective:This course is aimed at Computer Science majors who have never taken any type of mathematical theory courses before, though it is also a useful course for developing general reasoning and problem solving skills. For those that continue studying Computer Science, this course serves as excellent preparation for the required course Discrete Math For Computer Scientists. However, all students taking this course should benefit by improving their reasoning and abstract thinking skills, learning how to construct sound, logical arguments, and by learning to detect flaws in unsound arguments.Course DescriptionThis course offers a presentation of fundamental tools required in advanced computer science. The main topics covered in this subject include propositional and first-order logic, recursion, proofs, other kinds of logic. This forms the basis for the subjects like Automata theory and formal methods.Course Outline (to be covered in 40 lectures)1. Introduction, Set theory, Notion of proofs , Linear congruence (8)2. Formal logic: Propositional Logic, Relational logic, First order logic, and related issues (8)3. Lattices and related issues (8)4. Group Theory and related issues (6)5. Finite Fields and related issues (6)6. Generating Functions and related issues (4)Text Books1. The Essence of Logic, by John Kelly, Ed.2. Logic for Applications, Anil Nerode and Richard A. Shore, Ed.3. Logic, Sets, and Recursion, by Robert L. Causey, Ed.4. Concrete mathematics: a foundation for computer science, by R. Graham, D. Knuth, O. Patashnik,5. A Mathematical Introduction to Logic, Enderton, H6. Discrete Mathematical Structure with Application to Computer Science”, J.P Trembley,. & R. Manohar10Technical Writing (III Semester CSE & IT 3L)SyllabusTechnical Writing (CS-1305)Prerequisite: English, Foundations.Objective:English is a dedicated writing course offered to students in an online classroom environment. Students enrolled in the course will be expected to work in three ways: independently; in consultation with their instructor; and also collaboratively in writing teams to be established by the instructor following the first module (unit) of the course.Course DescriptionThis course is an introduction to Technical Writing. To help students analyze the communication situation fully and accurately: which includes needs, audiences, and users. To gather, interpret, and document information logically, efficiently, and ethically. To develop professional work and teamwork habits. To be able to design usable, clear, persuasive, accessible documents. To educate the students to select the appropriate format for presenting information and organize information using reader-based principles. To motivate them to use graphics effectively. And finally develop an effective, clear writing style.Course Outline (To be covered in 30 lectures)1. Introduction, Introduction To Latex, Introduction to Xfig and other drawing software. (8)2. English usage, when English is a foreign language. (6)3. Reading a draft, Writing a draft, revising a draft, Introduction to IEEE, ACM style files (6)4. Writing a technical talk, presenting the technical talk (4)5. Writing a project/thesis. Introduction to various styles. (4)6. Copyright issues and plagiarism (2)Text Books1. Handbook of Writing for the Mathematical Sciences By Nicholas J. Higham2. The Elements of Style, William Strunk, ISBN 0-205-30902-X3. LaTeX: A document preparation system, User's guide and reference manual Leslie Lamport, ISBN 0-201-52983-14. Cambridge English for Engineering, Mark Ibbotson11Analysis of Algorithms (IV Semester CSE & IT 3L)SyllabusAnalysis of Algorithms (CS-1401)Prerequisites: Discrete Mathematics (counting arguments, induction, recurrence relations and discrete probability)Objectives:This is an introductory course in the analysis and design of combinatorial algorithms. Emphasis is given on (i) familiarizing the students with fundamental algorithmic paradigms and (ii) rigorous analysis of combinatorial algorithms. This is a modern introduction to combinatorial algorithms and it maintains some consistency with previous courses.Course DescriptionThis course teaches techniques for the analysis of efficient algorithms, emphasizing methods useful in practice. Algorithms are recipes for solving computational problems. In this course we will study fundamental algorithms for solving a variety of problems, including sorting, searching, divide-and-conquer, dynamic programming, greediness, and probabilistic approaches. Algorithms are judged not only by how well they solve a problem, but also by how effectively they use resources like time and space. Techniques for analyzing time and space complexity of algorithms and to evaluate tradeoffs between different algorithms. Analysis of algorithms is studied - worst case, average case, and amortized - with an emphasis on the close connection between the time complexity of an algorithm and the underlying data structures. NP-Completeness theory is examined along with methods of coping with intractability, such as approximation and probabilistic algorithms. A basic understanding of mathematical functions and data structures is a prerequisite for the subject. A lab course is associated with it to strengthen the concepts.Course Outline (To be covered in 30 lectures)1. Introduction, Review of basic concepts, advanced data structures like Binomial Heaps, Fibonacci Heaps (5)2. Divide and Conquer with examples such as Sorting, Matrix Multiplication, Convex hull etc(6)3. Dynamic programming with examples such as Kanpsack, All pair shortest paths etc (4)4. Backtracking, Branch and Bound with examples such as Travelling Salesman Problem etc (6)5. Algorithms involving Computational Geometry (4)6. Selected topics such as NP-completeness, Approximation algorithms, Randomized algorithms, String Matching (5)Text Books1. Introduction to Algorithms by Thomas H. Coreman, Charles E. Leiserson and Ronald L. Rivest2. Fundamentals of Computer Algorithms by E. Horowitz & S Sahni3. The Design and Analysis of Computer Algorithms by Aho, Hopcraft, Ullman,12Graph Theory and Combinatorics (IV Semester CSE & IT 3L)SyllabusGraph Theory & Combinatorics (CS-1402)Prerequisites: Discrete Mathematics, Computer Algorithms and ProgrammingObjectives: The course aims to introduce the students about topics and techniques of Graph Theory and Combinatorial analysis. The course provides a large variety of applications and, through some of them, the algorithmic approach to the solution of problems in computer science and related areas. This helps in developing mathematical maturity skills of students. To present a survey of essential topics for computer science students who will encounter some of them again in more advanced courses.Course DescriptionThe course provides an introduction to graph theory and combinatorics, the two cornerstones of discrete mathematics. The student will gain an insight into the basic definitions of relevant vocabulary from graph theory and combinatorics, and know the statements and proofs of many of the important theorems in the subject. It helps to simulate real world problems, with applications in communication and networks, operating systems, robotics, wireless and sensor networks, VLSI and many more. Topics that will be discussed include Euler formula, Hamilton paths, planar graphs and coloring problem; the use of trees in sorting and prefix codes; useful algorithms on networks such as shortest path algorithm, minimal spanning tree algorithm and min-flow max-cut algorithm. The Prerequisite is basic knowledge of set and matrix theoryCourse Outline (To be covered in 30 lectures)1. Combinatorics Basic counting techniques, pigeon-hole principle, recurrence relations, Polya's counting theorem. Introduction to probabilistic method in combinatorics (6)2. Fundamental concepts of graphs and digraphs, (4)3. Spanning tree, connectivity, optimal graph traversals (5)4. Planarity of Graphs, Drawing graphs and maps, graph coloring (5)5. Special digraph models, network flow and applications (6)6. Algebraic specifications of Graphs, Non planar layouts (4)Text Books1. Introduction to Enumerate Combinatorics, M. Bona,2. Introduction to Graph Theory, D.B.West3. Graph Theory and Applications J.A. Bondy and U.S.R.Murty: ( Freely downloadable from Bondy's website; Google-Bondy)4. Graph Theory: Modeling, Applications, and Algorithms, by Geir Agnarsson and Raymond Greenlaw5. Introductory Combinatorics by R A Brualdi,13Computer Organization (IV Semester CSE & IT 3L)SyllabusComputer Organization (CS-1403)Prerequisites: Discrete Structures and Digital LogicObjectives: The objective of this course is to master the basic hardware and software issues of computer organization. The students are expected to know the inner workings of a computer and have the ability to analyze the hardware and software issues related to computers and the interface between the two. This allows the students to work out the trades off involved in designing a modern computer.Course DescriptionThis is a first course dealing with layout and design principles of a computing system and its peripherals. It requires understanding of digital electronics. It prepares foundations for the operating system, microprocessor and embedded systems courses.Course Outline (To be covered in 30 lectures)1. Introduction, Register Transfer Language, Bus and Memory Transfers, Bus Architecture, Arithmetic Logic Unit (6)2. Fundamental concepts of controller design. (6)3. Processor design and related issues (8)4. Input/Output Organization and related concepts(4)5. Optical, magnetic and semiconductor memory devices, Memory organization (6)Text Books1. Computer Organization and Design: The Hardware-Software Interface, by David Patterson and John Hennessy.2. Computer Organization, by Vravice, Zaky & Hamatcher3. Structured Computer Organization, by Tannenbaum4. Computer System Architecture, by M. Mano14Automata Theory(IV Semester CSE & IT 4L)SyllabusAutomata Theory (CS-1404)Prerequisites: Knowledge corresponding to the Formal languages and automata, Computability and complexity.Objectives: At the end of the course students should be able to understand and explain selected advanced parts of automata theory, including parsing techniques for deterministic context-free languages, relationship between finite-state automata and MSO logic, automata on infinite words, and process specifications. Further, students should be able to make reasoned decisions about computational models appropriate for the respective area and to understand methods and techniques of their applications.Course DescriptionAutomata theory is the study of abstract computational devices. They have applications in modelling hardware, lexical analysis, machine design, syntax analysis, parser generation, program verification, text editing and so on. The class of formal languages, context free grammar, DFA, NFA and PDA are being covered up in the course. The knowledge of these concepts form the foundations of computer science and continues towards the development of the student's skills in understanding mathematical models. The prerequisite is basic knowledge of mathematics. A lab course is associated with it to strengthen the concepts.Course Outline (To be covered in 40 lectures)1. Introduction, inductive Proofs Relations and Functions (4)2. Regular Languages DFA, NFA Machines and their equivalence, Regular Expressions, Equivalence of Regular Expressions and Finite State Machines, Closure Properties of Regular Languages Proving Non-Regularity (8)3. Context-free Languages Context-free Grammars, Derivations, Leftmost, Rightmost, Inherent Ambiguity, Parse Trees, Normal Forms, Proof of Containment of the Regular Languages Pushdown Automata, Equivalence of PDAs and Context-free Grammars Closure Properties of Context-free Languages (12)4. Pumping Lemma for both Regular & Context-free Languages, Proving Some Languages are not Context-free. (6)5. Recursive and Recursively Enumerable Languages, Turing Machines Definition of Recursive and Recursively Enumerable, Church's Hypothesis, Computable Functions, Methods for Turing Machine Construction (10)Text Books1. Introduction to the Theory of Computation, by Michael Sipser2. Introduction to Automata Theory, Languages, and Computation, by Hopcroft, Motwani, and Ullman (ISBN 0-321-45536-3)3. Theory of Computer Sciences Korral,4. Automata, Computability and Complexity: Theory and Applications. by E Rich15Communication Foundations (IV Semester CSE & IT 3L)SyllabusCommunication Foundations (EC-1405)Prerequisites: Developing Windows Communication Foundation (WCF)–based applications including experience with .NET Framework.Objectives: This course introduces the .NET Windows Communication Foundation (WCF) technology and its architecture. It shows how to create a basic WCF service and how to host the service in a managed application, a Windows Service, Internet Information Service (IIS), or Windows Process Application Activation Services (WAS). It also covers how to generate a client proxy class and configuration file to access a WCF service. This course is one of a series in the Skillsoft learning path that covers the objectives for the Microsoft Technology Specialist: Microsoft Windows Communication Foundation Development with Microsoft .NET Framework. This course is ideal for Application Developers, .Net Programmers, Web Developers.Course DescriptionIn this course students will study fundamentals of analog and digital communication. The course includes the basics of Electromagnetic waves, antennas, modulation, information theory, sampling and quantization, coding, signal detection and system performance in the presence of noise. This is a prerequisite for the course on Computer Networks. A lab course is also associated with it.Course Outline (To be covered in 30 lectures)1. Introduction, Elements of communication systems, review of signal2. epresentations in time and frequency domain, bandwidth, filters, Electromagnetic spectrum (6)3. Sky waves, ground waves and space waves, Antenna fundamentals and types of antennas (4)4. Amplitude Modulation, Frequency modulation, Radio receivers (4)5. Sampling theorem, quantization and pulse code modulation, digital modulation techniques (6)6. Fundamentals of guided waves, wave guides, coaxial cables, fiber optic cables, cable types and specifications. (6)7. Case studies: FM Broadcast, satellite communication, telephone systems, mobile telephonyText Books1. Communication Systems Engineering by Proakis, John, and Masoud Salehi2. Electronic Communication Systems by Kennedy D3. Computer Networks by Tanenbaum, Andrew4. Communication Systems by Haykin, Simon.16Contemporary Issues in Information Technology (IV Sem CSE & IT 2L)SyllabusContemporary Issues in Information Technology (CS-1405)Prerequisites: Application areas of Information TechnologyObjectives: This course addresses the current issues that surround the use of information technology (IT) and the development of IT-based solutions. Using an overview of the IT components utilized in the areas of computer hardware and software, information processing and telecommunications as a foundation, this course explores the current issues and trends which challenge IT professionals. The primary purpose of this course is to teach students how to approach, investigate, consider, analyze, use and apply information technology in order to address specific information based needs. The course is intended to serve as a foundation formore advanced work in the information Technology concentration.Course DescriptionA survey of the computer engineering profession's contemporary role in society, including concerns for business principles, safety, and the environment; the role of computer engineers in achieving economic stability, growth, and improving the human condition. Course prepares general awareness amongst students pertaining CS/IT by motivating them to go through the debates, and discussions taking place in national and international societies like CSI, ACM and IEEE and articles published in their respective magazines.Course Outline (To be covered in 10 lectures of two hour duration per week)1. Introduction, Information technology in the past, present, and in the future (4)2. Contemporary theoretical and research issues which include the digital divide, optical and quantum computing, human computer interfaces and computing limitations. (8)3. Applying information technology across disciplines (4)4. Case study of famous IT professionals (4)Text Books (Not Applicable)1. CSI Communications ( latest 12 issues)2. Communications of ACM ( latest 12 issues)3. IEEE Software ( latest 12 issues)4. IEEE Computer ( latest 12 issues)5. IEEE Spectrum ( latest 12 issues)17Computer Graphics (V Semester IT 3L)SyllabusComputer Graphics (CS-1507)Prerequisites: Data Structure and Linear Algebra.Objective: understand the internal workings of commercial systems for the rendering of digital images from 3D models write their own software for 3D modeling and rendering use 3D graphics API's undertake creative work and research in 3D graphicsCourse DescriptionIn this course students will study the fundamental concepts in creating graphical images on the computer. Computer graphics uses ideas from Art, Mathematics, and Information Technology to create images. The students are expected to be comfortable writing programs in an upper level language, and have sound background in mathematics, as a great deal of computer graphics is best described mathematically. This course leads to courses on multimedia and image processing. This course has an associated lab course with it.Course Outline (To be covered in 30 lectures)1. Introduction, Input-Output devices, Line Scan algorithms, Mid –point Circle and Ellipse Generating algorithms, Polygon Filling, Clipping (7)2. Geometrical Transformations (2D & 3D), Projections, Visible-Surface Determination (9)3. Representation of Curves and Surfaces, Solid Modeling (6)4. Color models and applications(4)5. CAD/CAM and Applications of computer Graphics (4)Text Books1. Computer Graphics, by Hearn and Bakerand2. Procedural Elements of Computer Graphics by Rogers3. Principle of Interactive Computer Graphics by Newman and Sproul4. Computer Graphics, A programming Approach by Steven Harrington18Operating System (V Semester CSE & IT 4L)SyllabusOperating Systems (CS-1502)Prerequisite: C, Java, and data structures.Objective: - gain extensive knowledge on principles and modules of operating systems- understand key mechanisms in design of operating systems modules- understand process management, concurrent processes and threads, memory management, virtual memory concepts, deadlocks- compare performance of processor scheduling algorithms- produce algorithmic solutions to process synchronization problems- use modern operating system calls such as Linux process and synchronization libraries- practice with operating system concepts such as process management, synchronization, networked processes and file systemsCourse DescriptionIn this course students will study the basic facilities provided in modern operating systems. The emphasis will be on understanding general concepts that are applicable to a wide range of operating systems, rather than a discussion of the features of any one specific system. Topics that will be covered in the course include: protected kernels, processes and threads, concurrency and synchronization, memory management, virtual memory, file systems, secondary storage, protection, and security. This course requires as prerequisite the course on computer programming, data structures and computer organization. This course has an associated lab with it.Course Outline (To be covered in 40 lectures)1. Introduction and Overview (2)2. Process fundamentals, scheduling, synchronization (12)3. Inter-process communication, Deadlock (8)4. Memory management and virtual memory (7)5. File system and secondary storage (5)6. Protection and security issues, Case studies e.g. Linux, Solaris and Android (6)Text Books1. Operating Systems, by William Stallings2. Operating Systems Concepts by Silberschatz, Galvin, and Gagne3. The Design of the UNIX Operating System, by Maurice J. Bach4. Advanced Programming in the UNIX Environment, by W. R. Stevens & S. A. Rago5. The Design and implementation of the 4.4 BSD UNIX operating system by Marshall Kirk McKusick, Keith Bostic, Michael J. Karels, John S. Quarterman19Computer Networks (V Semester CSE & IT 4L)SyllabusComputer Networks (CS-1503)Prerequisite : C or Java programming, Course in algorithms, Course in probability.Objective:1. Build an understanding of the fundamental concepts of computer networking.2. Familiarize the student with the basic taxonomy and terminology of the computernetworking area.3. Introduce the student to advanced networking concepts, preparing the student forentry Advanced courses in computer networking.4. Allow the student to gain expertise in some specific areas of networking such as the design and maintenance of individual networks.Course DescriptionIn this course students will study computer networks within the context of the Internet. It will build on prior knowledge in Communication foundations, computer organization, basic algorithms, data structures and C programming. Students will study the fundamental principles, elements, and protocols of computer networks. Course will investigate how the different protocols work, why they work that way, and their performance trade-offs. This course prepares foundations for wireless networks and distributed systems. This has a lab course associated with it.Course Outline (To be covered in 40 lectures)1. Introduction, Fundamental requirements of network, OSI & TCP/IP model (3)2. Physical and Link layer issues (4)3. Medium Access protocols (IEEE 802.3 ...) and related issues (8)4. Network layer: IP and other protocols, Routing protocols, and LAN design. (11)5. Transport layer Protocols and related Issues (8)6. Basic client server architecture, introduction to different application layer protocols like ftp, telnet, mail(SMTP), HTTP, DNS, DHCP and peer to peer (6)Text Books1. Computer Network – Top down approach by James. F. Kurose & Keith W. Rose,2. Compuer Network – A system approach by Larry.L.Peterson & Bruce.S.Davie3. Data Communication & Networking by Behrouz Forouzan4. Unix Network Programming –volume-I by W.Richard Stevens20Object Oriented Modeling (V Semester CSE & IT 3L)SyllabusObject Oriented Modeling(CS-1504)Prerequisite : Basic Concepts of Object Oriented Programming, Software Engineering.Objective: Analyze and Design a real – world problem into Object- Oriented form. Create a requirements model using UML class notations and use-cases based onstatements of user requirements, and to analyze requirements models given to them forcorrectness and quality. Create the OO design of a system from the requirements model in terms of a high-levelarchitecture description, and low-level models of structural organization and dynamicbehavior using UML class, object, and sequence diagrams. Comprehend enough Java to see how to create software that implements the OO designsmodeled using UML. Comprehend the nature of design patterns by understanding a small number of examplesfrom different pattern categories, and to be able to apply these patterns in creating an OOdesign. Given OO design heuristics, patterns or published guidance, evaluate a design forapplicability, reasonableness, and relation to other design criteria.Course DescriptionIn this course students will study the fundamental principles of object-oriented approaches to modeling software requirements and design. Topics include strategies for identifying objects and classes of objects, specification of software requirements and design, the design of class hierarchies, software reuse considerations, graphical notations, system implementation using object-oriented and object-based programming languages, and comparison of object-oriented approaches to more traditional approaches based on functional decomposition.Course Outline (To be covered in 30 lectures)1. Introduction, Need for formal and semi-formal modeling, UML-2 Meta-model (4)2. UML-2 Concepts and Examples: Object, Class, Relationship, Interface, Types, roles, Use Case, Interaction and Activity Diagrams, State Machine and State-chart Diagram, Events, signals, Process and threads (8)3. Software System Design, Design Patterns, Pattern Classification, Creational, Structural and Behavioral patterns, Idoms (12)214. Agents and Agent Modeling, Multi-Agent Systems Modeling, Case Study (6)Text Books1. Object-Oriented Modeling and Design with UML - Michael Blaha, James Rumbaugh2. Pattern-Oriented Software Architecture A System of Patterns, Volume 1 - Frank Buschmann, Regine Meunier, Hans Rohnert, Peter Sommerlad, Michael Stal3. Object-Oriented Analysis and Design with Applications - Grady Booch et al4. Object-Oriented Design with UML and JAVA - K. Barclay, J. Savage5. Practical Object-Oriented Design with UML - Mark Priestley22Operations Research (V Semester CSE & IT 3L)SyllabusOperation Research (CS-1505)Prerequisite: Basic Engineering Mathematics.Objective: This module aims to introduce students to use quantitative methods and techniques for effective decisions–making; model formulation and applications that are used in solving business decision problems.Course DescriptionIn this course students will study some common operations research models and algorithms. Operations Research (OR) refers to the science of informed decision making. The goal is to provide rational basis for decision-making by analyzing and modeling complex situations, and to utilize this understanding to predict system behaviour and improve system performance. The application of OR involves problem formalization, model construction and validation; other activities include a computational part, analysis of solutions, arriving at conclusions, and implementation of the decision. It extensively uses the concepts of mathematical modeling, statistical analysis and optimization techniques. The emphasis is on applications rather than the details of methodology. This would act as a tool to the courses namely data mining, business intelligence and decision support systems.Course Outline (To be covered in 30 lectures)1. Introduction, Linear programming (LP) models, (4)2. Simplex & revised simplex algorithms, Duality and sensitivity analysis in LP (6)3. Basics of Game theory, Transportation and assignment problems, Project scheduling (critical path method & PERT) (10)4. Integer programming models, Stochastic processes: Markov chains and birth/death processes, Queuing theory (6)5. Network Analysis and Inventory Control(4)Text Books1. Operations Research Models and Methods, by Paul A. Jensen and Jonathan F. Bardto2. Operation Research by Hamdy.A Taha3. Introduction to Operations Research, by Frederick Hillier & Gerald Lieberman4. Linear Programming by Hadely G.23Cryptography (V Semester CSE & IT 3L)SyllabusCryptography (CS-1506)Prerequisite: Coding Theory, Information Security.Objective:Appreciate the core techniques of cryptography and how they can be applied to meet various security objectives. Understand both the importance of cryptographic key management, and the different key management requirements and practices associated with the use of different security techniques. Appreciate how the techniques described are employed in practice in a variety of security applications, from SSL enabled websites through to disk encryption.Course DescriptionIn this course students will study the essential mathematical foundations for Information Security. This course features a rigorous introduction to modern cryptography, with an emphasis on the fundamental cryptographic primitives of public-key encryption, digital signatures, pseudo-random number generation, and basic protocols and their computational complexity requirements. After crediting this course students can look forward to wireless network security and E-commerce courses.Course Outline (To be covered in 30 lectures)1. Introduction, Prime Number Generation, Shannon's Theory of Perfect Secrecy (5)2. Asymmetric Key Cryptosystem and related issues (5)3. Public Key Cryptography and related concepts/methodologies (10)4. Cryptographic Hash Functions design and implementation issues. (5)5. Digital Signatures and related issues (5)Text Books1. Modern Cryptography : Theory and Practice by W Mao2. Applied cryptography by Bruce Schiener3. “Cryptography: Theory & Practice” D R Stinson,4. Introduction to cryptography by Johannes A Buchmann5. Network Security and Cryptography by Bernard Menezes24Multimedia Technology (VI Semester IT 3L)SyllabusMultimedia Technology (CS-1607)Prerequisites: Knowledge of basic application software.Objective: Knowledge of utilization of multimedia applications.Course DescriptionIn this course students will study multimedia technologies, both standard and newly developed. Course coverage will include both theoretical understanding of multimedia technologies, and hands-on experience with applications and hardware. Topics may include perception, cognition, and communication issues, multimedia interface standards, multimedia evaluation, digitizing and manipulating images, voice, and video materials. Courses namely Computer graphics, Operating System and Computer Networks are prerequisites. A lab course is associated with it to strengthen the concepts.Course Outline (To be covered in 30 lectures)1. Introduction, Multimedia Information, Multimedia Objects, Convergence of Computer, Communication and Entertainment products, Digital representation (6)2. Multimedia hardware, Memory & storage devices, Communication devices, Multimedia software's, presentation tools, tools for object generations, video, sound, image capturing, authoring tools, card and page based authoring tools (6)3. Introduction to Text, hypertext & hypermedia, Sound, MIDI, Digital Audio concepts, audio file formats Sampling Variables, Loss less compression of sound, Audio Capture. (6)4. Introduction to video& images :Multiple monitors, bitmaps, Vector drawing, Image format conversion, image compression, JPEG Compression, image & video file formats, animation, animation file formats. Video representation, Video Compression, color models, MPEG standards, Video Streaming on net, Video on demand. (6)5. Introduction to multimedia communications. multimedia over I.P, multimedia Over ATM Networks, multimedia Data Base, content based retrieval in Digital libraries, multimedia over wireless networks. Serial port programming and interrupts (6)Text Books1. Fundamental of Multimedia by Li and Drew2. Principle of Multimedia by Rajan Parekh3. Multimedia, Making it Work by Tay Vaughan25Scientific Computing(VI Semester CSE & IT 3L)SyllabusScientific Computing (CS-1602)Objective: The goal of this course is to introduce students to the fundamental concepts of Scientific Programming using Matlab/Octave and similar programming languages (e.g. sage math) and we will introduce the necessary mathematical concepts as we go (including linear algebra, differential equations, probability and statistics). The course will cover the syntax and semantics of Matlab/Octave including data types, control structures, comments, variables, functions, and other abstraction mechanisms.Prerequisites: Calculus, Algebra, The ability to write and run programs under a UNIX operating system, in one of the languages C, C++, or Fortran.The ability to create executables involving multiple files and libraries either by a script or a makefile .Write programs that read and write formatted data from and to files.Course DescriptionScientific computing has become an indispensable tool in many branches of research, and is vitally important for studying a wide range of physical and social phenomena. This course will examine the mathematical foundations of well-established numerical algorithms and explore their use through practical examples drawn from a range of scientific and engineering disciplines. It gives the computational algorithms for analyzing and solving mathematical problems such as model fitting, calculus operations, finding roots for equations and other statistical computation. The prerequisites for this course are linear algebra, calculus, and elementary probability theory along with computer programming.Course Outline (To be covered in 30 lectures)1. Introduction, Algebraic and Transcendental Equations and related issues (8)2. Discussion on different Interpolation concepts and methods (8)3. Curve Fitting, Cubic Spline & Approximation(7)4. Numerical Integration and Differentiation. (6)5. Numerical Linear Algebra (5)6. Statistical Computations (6)Text Books1. Numerical Recipes in C The Art of Scientific Computing by W H Press, S A Teukolesky, W T Vellerling and B P Flannery2. Numerical Methods for Scientific and Engineering by M.K.Jain, S.R.K.Iyenger and R.K.Jain3. Numerical Methods and Analysis by James I. Buchman and Peter R.Turner4. Applied Numerical Analysis by C.F.Gerald and P.O.Wheatley26Business Intelligence (VI Semester IT 3L)SyllabusBusiness Intelligence (CS-1608)Prerequisites: Clear understanding of what kind of business Questions must be answered.Objective: Gather all needed information from the business applications, to link them into the business context and to reduce the amount of information to answer the Business questions represented by the key indicators.Course DescriptionIn this course students will study the features, uses, and design strategies for IT-enabled managerial decision support and business intelligence. The course includes an overview of business intelligence framework, business process management and application-based business analytics and reporting.Course Outline (To be covered in 30 lectures)1. Introduction, Overview of Business Intelligence, deduction, induction, machine learning and neural networks, (5)2. Introduction to analysis, quantitative methods for data analysis and knowledge extraction: classification and regression, Bayesian approaches, belief networks. (8)3. Introduction to DSS development, Traditional system development life cycle, Alternate development methodologies, Prototyping: DSS Methodology, Tools for DSS development, DSS Technology levels and tools (8)4. Enterprise system : Concept and definition, Enterprise Decision Support System, Evolution of executive and enterprise information system (EIS), Characteristics and capabilities of EDSS , Comparing and integrating EIS and DSS (6)5. BI applications: Knowledge management, Decision analysis, Investment Strategies, Marketing Campaigns (3)Text Books1. Decision Support Systems and Intelligent Systems by Efrain Turbon.2. Adaptive Business Intelligence by Michalewicz Z., Schmidt M., Michalewicz M. and Chiriac C.3. Business Intelligence: A Managerial Approach by Turban E., Sharda R., Aronson J.E. and King, D.4. Advanced Management Information Systems by W.S. Jawadeka27Wireless Network Security (VI Semester CSE & IT 3L)SyllabusWireless Network Security (CS-1604)Objective: In this course, description and classification of security goals and attacks in wireless networks, security architectures of the following wireless systems and networks: 802.11, GSM/UMTS, RFID, ad hoc/sensor networks, reason about security protocols for wireless network will be covered.Prerequisites: This course assumes prior knowledge of Computer Networks, A basic understanding of TCP/IP networking, Mobile Computing & understanding of Computer Security concepts. Knowledge of data structures, databases, and mathematical logic are useful.Course DescriptionIn this course students will study wireless networks and their security. In this course, many recent, current and emerging developments will be discussed including advances in cellular, personal communications systems (PCS), wireless LANs, satellites, and fixed wireless networks. Significant details of wireless devices and middleware will be included. Many emerging challenges and solutions including ad hoc wireless networks, broadband wireless and quality of service, and location management besides security would be taken up. Communication Foundations, Computer Network and cryptography are prerequisite courses. A lab course is associated with it to strengthen the concepts.Course Outline (To be covered in 30 lectures)1. Introduction, Wireless Communications (2)2. Wireless devices and Middleware, Design of Wireless Networks (2)3. Ad-hoc wireless networks, wireless sensor networks(2)4. Security threats in wireless networks. Security requirements of wireless networks (4)5. Security case studies for Wireless LAN and Ad-hoc wireless networks (6)6. Speech Cryptology (5)7. Protocols and Applications of Cellular, Personal Communications Systems, and Bluetooth. Security issues and services. (9)Text Books1. Wireless Security Models, Threats, and Solutions By: Randall K. Nichols, Panos C. Lekkas2. Wireless Communications: Principles & Practice, by Ted Rappaport,3. Wireless Network Design: Optimization Models and Solution Procedures, by J. Kennington et. al.4. Security and Cooperation in Wireless Networks, by Levente Buttyán and Jean-Pierre Hubaux [Available Online]5. The IEEE 802.11 Handbook: A designers companion by Bob O Hara, Al Petrick28Database Management System(VI Semester CSE & IT 4L)SyllabusDatabase Management System (CS-1605)Objective: This course will give principles and practical solutions for storage and retrieval of information using a computer system, particularly for large quantities of data, and with an emphasis both on the use of relational database management systems.Prerequisites: Elementary knowledge about computers including some experience using Unix or Windows. Knowledge of programming in some common programming language. Understanding of data structures and algorithms are required.Course DescriptionIn this course students will study the basic functions and capabilities of database management systems (DBMS). Emphasis is placed on the use of DBMS in solving information processing problems which will include database design case studies as well as SQL programming assignments along with transactions. A lab course is associated with it to strengthen the concepts.Course Outline (To be covered in 40 lectures)1. Database system concept and architecture, Entity Relationship and Enhanced E-R (5)2. Relational Data Model and Relational Algebra, SQL, Indexing, Query Optimization (10)3. Relational Database Design, Normalization principles and normal forms (8)4. Transaction concept and concurrency control (8)5. Web Interface to DBMS, Semi-structured databases, Object oriented databases (6)6. DBMS Case studies (3)Text Books1. Database system concepts, by Korth, Silberschatz, and Sudarshan2. Fundamentals of Database Systems by Elmasari and Nawathe3. Databases by O Neil,4. Database Systems The Complete Book by Garcia-Molina, Ullman, & Widom5. Database Management System by Ramakrishnan and Gehrke29Software Engineering (VI Semester CSE & IT 3L)SyllabusSoftware Engineering (CS-1606)Objective: The course assists to understand the basic theory of software engineering, and to apply these basic theoretical principles to a group software development project.Prerequisites: Data Structures & Algorithms, Programming Language abstract and Concrete Syntax, Logic Propositional and Predicate Logic, Proofs - Inference Rules, Proof Methods.Course DescriptionIn this course students will study the fundamentals of software engineering, including understanding system requirements, finding appropriate engineering compromises, effective methods of design, coding, and testing, team software development, and the application of engineering tools. The course will combine a strong technical focus with a mini project (offered alongside), providing the opportunity to practice engineering knowledge, skills, and practices in a realistic development setting.Course Outline (To be covered in 30 lectures)1. Introduction, Software life-cycle models (4)2. Software requirements, Requirements Specification (6)3. Software design and Software user interface design(7)4. Coding Issues, Software integration and testing. (6)5. Software support processes and Quality Assurance, IEEE Software Engineering Standards (4)6. Software maintenance, Software reuse, (3)Text Books1. Software Engineering – A Practitioner’s Approach, by Pressman R. S. and Ince D2. Software Engineering by Sommerville3. Software Engineering, Volume 1 and Volume 2, by Thayer, and Christiansen,4. Fundamentals of Software Engineering by Rajib Mall30Image Processing (VII Semester IT 4L)SyllabusImage Processing (CS-1703)Prerequisites: This course assumes that students have strong programming skill in MATLAB, and a working knowledge of Intermediate Calculus, Linear Algebra, basic estimation techniques, and some statistical topics on the level of introductory courses in statistics.Objective: This course will provide students a detailed overview of Digital Image Processing and its applications. Image processing has found applications in many areas from medical imaging to computer graphics. This course covers the fundamental concepts of visual perception and image acquisition, basic techniques of image manipulation, segmentation and coding, and a preliminary understanding of Computer Vision. With successful completion of the course, students will be able to perform image manipulations and analysis in many different fields.Course DescriptionIn this course students will study the theoretical foundations and modern applications in digital image processing. Insight into the basic operations like image acquisition, enhancement, restoration, transformations, compression, segmentation, object recognition and visual interpretation would be taken up along with the numerical interpretation. Wide variety of research applications ranging from pattern recognition, security measures such as digital signatures, watermarking; traffic video surveillance, medical imaging, remote sensing applications would be illustrated. Pre-requisite is the basic knowledge of mathematics and programming. A lab course is associated with it to strengthen the concepts.Course Outline (To be covered in 40 lectures)1. Introduction, digital image fundamentals Elements of digital image processing systems, Elements of visual perception, brightness, contrast, hue, saturation, Color image fundamentals - RGB, HSI models, Image sampling, Quantization, dither, Two-dimensional mathematical preliminaries, 2D transforms - DFT, DCT, KLT, SVD. (6)2. Image enhancement Histogram equalization and specification techniques, Noise distributions, Spatial averaging, Directional Smoothing, Median, Geometric mean, Harmonic mean, Contraharmonic mean filters, Homomorphic filtering, Color image enhancement. (8)3. Image Restoration - degradation model, Unconstrained restoration - Lagrange multiplier and Constrained restoration, Inverse filtering-removal of blur caused by uniform linear motion, Wiener filtering, Geometric transformations-spatial transformations. (8)4. Image segmentation, Edge detection, Edge linking via Hough transform –31Thresholding - Region based segmentation – Region growing – Region splitting and Merging – Segmentation by morphological watersheds – basic concepts – Dam construction – Watershed segmentation algorithm. (8)5. Need for image compression, Huffman, Run Length Encoding, Shift codes, Arithmetic coding, Vector Quantization, Transform coding, JPEG standard, MPEG. (8)Text Books1. Digital Image Processing by Rafael C. Gonzalez, Richard E. Woods,2. Fundamentals of Digital Image Processing by Anil K. Jain,3. Digital Image Processing by William K. Pratt4. Professional Ethics(VII Semester CSE & IT 2L)32Professional Ethics(VII Semester CSE & IT 2L)SyllabusProfessional Ethics (CS-1702)Objective : The course will develop a framework on which professional and ethical issues can be analyzed, and build up an awareness of various views of ethical issues as well as professionals and engineering ethical rights and responsibilities.Instructional Goal:1. To familiarize students with different professional codes of ethics.2. To familiarize students with the goals and possible effects of professional codes of ethics.Performance Objective:1. To develop awareness of different codes of ethics.2. To be able to distinguish between the goals of different societies and organizations.3. To be able to distinguish between the effects of different codes of ethics.Prerequisites: A course in public speaking and a course in writing a research papers.Course DescriptionIn this course students will study application of moral reasoning to established profession of computer engineering. Moral reasoning entails the search for values and principles that promote a good life and human flourishing. As a professional, one has to employ ones expertise in the ways that greatly affect the lives of others. After crediting the course the students are expected to identify ethical conflicts, identify their responsibilities and options, and think through the implications of possible solutions to ethical conflicts.Course Outline (To be covered in 20 lectures)1. Introduction, Ethical theories (4)2. Ethics in IT societies, Intellectual rights and privacy (6)3. Professional Relationships, Professional Responsibilities, Professional Ethics in Computing (6)4. Online crime, hacking, Legal aspects of Professional Ethics (4)Text Books1. IEEE/ACM Software Engineering Code of Ethics and Professional Practice (online)2. Computer Ethics by Deborah Johnson3. Ethics in Engineering by Martin M.W., Schinzinger R.4. Ethics in Information Technology by George Reynolds5. Readings in Cyber Ethics, Edited by Richard Spinello and Herman Tavani.33Privacy Preserving Publishing (VIII Semester IT 4L )SyllabusPrivacy Preserving Publishing (CS-1803)Prerequisites: Discrete Mathematics and Computer Systems Technologies.Objective: Primary goal is to develop critical understanding and thinking with respect to current research challenges in cyber security.Course DescriptionIn this course students will understand mechanisms and principles involved in the methods and tools of privacy-preserving publishing enabling the publication of useful information while protecting data privacy. In this course students will explore not only the privacy and information utility issues but also efficiency and scalability challenges.Course Outline (To be covered in 40 lectures)1. Introduction, Attack Models and Privacy Models (7)2. Anonymization Operations and Algorithms, Anonymization for Cluster Analysis. (9)3. Anonymizing Incrementally Updated Data Records, Collaborative Anonymization for Vertically Partitioned Data and Horizontally Partitioned Data. (8)4. Anonymizing Complex Data e.g. Anonymizing Transaction Data, Anonymizing Trajectory Data. (8)5. Anonymization for data mining, Anonymizing Social Networks . (8)Text Books1. Introduction to Privacy-Preserving Data Publishing Concepts and Techniques By Benjamin C.M. Fung, Ke Wang, Ada Wai-Chee Fu, Philip S. Yu2. Privacy-Preserving Data Publishing: An Overview by Raymond Chi-Wing Wong & Ada Wai-Chee Fu3. Research papers34Research Trends in IT (VIII Semester IT 3L)SyllabusResearch Trends in IT(CS-1804)Prerequisites: Discrete Mathematics and Computer Systems Technologies.Objective: Primary goal is to develop critical understanding and thinking with respect to currentResearch challenges in Information Technology.Course DescriptionIn this course students will study newer areas of research in Information Technolgy. In the last fitty years have seen computer science and communication technology evolve as major academic disciplines. Today the field is undergoing a fundamental change. Some of the drivers of this change are the Internet, the World Wide Web, large quantities of information in digital form, wide spread use of computers for accessing information and semantic web. In this course the students would be encouraged to identify their area of interest and to prepare and present a term paper pertaining recent advances taking place in that area.Course Outline (To be covered in 30 lectures)1. Introduction, History of information technology, (3)2. Presentation ScheduleText Books (Not applicable)1. DBLP to identify areas and TOC of Journals and Conference Proceedings2. INDEST, ACM digital Library, IEEE Digital Library etc to browse papers3. Handbook of Writing for the Mathematical Sciences By Nicholas J. Higham35Professional Elective I & II(Pool – 1)36Artificial Intelligence (Professional Elective for CSE & IT 3L)SyllabusArtificial Intelligence: (OE)Prerequisites: Basic Program, Logical Program, Probability, Discrete Mathematics.Objective: Identify problems that are amenable to solution by AI methods, and which AI methods may be suited to solving a given problem. Formalize a given problem in the language/framework of different AI methods (e.g., as a search problem, as a constraint satisfaction problem, as a planning problem, as a Markov decision process, etc). Implement basic AI algorithms (e.g., standard search algorithms or dynamic programming). Design and carry out an empirical evaluation of different algorithms on a problem formalisation, and state the conclusions that the evaluation supports. Develop an expert system. Learn Logical Programming Skills.Course DescriptionThis course introduces students to the basic knowledge representation, problem solving, and learning methods of artificial intelligence (AI). It covers basic elements of AI, such as knowledge representation, inference, machine learning.Course Outline (To be covered in 30 lectures)1. Introduction, Intelligent agents, reactive, deliberative, goal-driven, utility-driven, and learning agents, Artificial Intelligence programming (5)2. Defining problems at state space search, Production system, Problem and production system characteristics, Forward and backward, state-space, blind, heuristic, problem-reduction, A, A*, AO*, minimax, constraint propagation, neural, stochastic, and evolutionary search algorithms, sample applications. Issues in design of search programs (7)3. foundations of knowledge representation and reasoning, issues in knowledge representation, representing and reasoning about objects, relations, events, actions, time, and space; predicate logic, situation calculus, description logics, reasoning with defaults, sample applications. (6)4. Planning as search, partial order planning, construction and use of planning graphs, planning and acting in the real world (3)5. Basics of utility theory, decision theory, sequential decision problems, elementary game theory, sample applications. (4)6. Learning from memorization, examples, explanation, and exploration. Supervised and un-supervised learning, learning nearest neighbor, naive Bayes, and decision37tree classifiers, Q-learning for learning action policies, applications. Sample Applications of AI (5)Text Books1. Artificial Intelligence: A Modern Approach, by Stuart Russell and Peter Norvig,2. Artificial Intelligence by Eliane Rich, Kevin Knight and Shivashankar B Nair,3. Introduction to Artificial Intelligence by Charniak, McDermott38Data Compression (Professional Elective for CSE & IT 3L)SyllabusData Compression (OE)Prerequisites:Basic data structures and algorithms, Fundamental concepts of computer architecture.Objective:Develop theoretical foundations of data compression, concepts and algorithms for lossy and lossless data compression, signal modeling and its extension to compression with applications to speech, image and video processing.Course DescriptionThe course discusses the theory and methods of data compression of signals, images, and video. Data Compression is the computational problem of how to encode a data file (text, image, audio, video) so that the new file has fewer bits the original file. Techniques covered include: Quantization, Vector Quantization, Differential Schemes, Filterbanks and Subband Coding, Wavelet Transform, JPEG 2000, and MPEG. Coverage of selected topics of recent research issues in data compression is also taken up.Course Outline (To be covered in 30 lectures)1. Information theoretic foundations, Arithmetic coding (6)2. Dictionary techniques, Context modeling (6)3. Lossless image compression, Lossy coding preliminaries (6)4. Scalar and vector quantization (6)5. Differential encoding, Transform coding (6)Text Books1. Introduction to Data Compression by Sayood, Khalid,2. Data Compression: The Complete Reference by M. Nelson,39Data Warehousing and Mining (Professional Elective for CSE & IT 3L)SyllabusData Warehousing and Mining (OE)Prerequisites: An upper-level undergraduate course(s) in algorithms and data structures, a basic course on probability and statistics programming in Java, C++, C.Objective:Understand data mining principles and techniques: Introduce DM as a cutting edge business intelligence method and acquaint the students with the DM techniques for building competitive advantage through proactive analysis, predictive modeling, and identifying new trends and behaviors. Learning objectives include:a. Building basic terminology.b. Learning how to gather and analyze large sets of data to gain useful business understanding.c. Learning how to produce a quantitative analysis report/memo with the necessary information to make decisions.d. Describing and demonstrating basic data mining algorithms, methods, and tools .e. Identifying business applications of data miningf. Overview of the developing areas - web mining, text mining, and ethical aspects of data mining.Develop and apply critical thinking, problem-solving, and decision-making skills.Course DescriptionThe course is an introduction to data mining techniques for the data stored in a data warehouse. Data mining, or knowledge discovery in databases, has during the last few years emerged as one of the most exciting fields in Computer Science. Data mining aims at finding useful regularities in large data sets. Interest in the field is motivated by the growth of computerized data collections which are routinely kept by many organizations and commercial enterprises, and by the high potential value of patterns discovered in those collections. This course will cover data warehousing and data cleaning, clustering, classification, and association rules mining.Course Outline (To be covered in 30 lectures)1. Introduction and overview of data mining processes (3)2. Data Warehousing: Overview, Definition, Delivery Process, Multi Dimensional Data Model, Data Cubes, Stars, Snow Flakes, Fact Constellations, Concept hierarchy, Process Architecture, 3 Tier Architecture, Data Marting. (5)3. Data clustering and classification techniques (9)4. Association rule mining (5)5. Tuning Data Warehouse, Testing Data Warehouse Data Mining interface,40Historical information, Query Facility, OLAP function and Tools. OLAP Servers, ROLAP, MOLAP, HOLAP, Security, Backup and Recovery (5)6. Applications and case studies (3)Text Books1. Data Mining: Concepts and Techniques by J. Han and M. Kamber,2. Introduction to Data Mining by Pang-Ning Tan, Michael Steinbach and Vipin Kumar3. Data Warehousing in the Real World : A Practical Guide for Building Decision Support Systems by Sam Anahory, Dennis Murray41Design Patterns (Professional Elective for CSE & IT 3L)SyllabusDesign Pattern (OE)Prerequisites: Prior knowledge of object-oriented programming is essential for this course. The students are expected to be proficient in Java, Principle of Programming Languages.Objective:• Understand and be able to apply incremental/iterative development• Understand common design patterns• Be able to identify appropriate patterns for design problems• Be able to evaluate the quality software source code• Be able to refactor badly designed program properly using patternsCourse DescriptionThis course is an introduction to software design patterns. Each pattern represents a best practice solution to a software problem in context of some application. The course will cover both the rationale and benefits of object-oriented software design patterns. Several example problems need to be studied to investigate the development of good design patterns. Specific patterns, such as Observer, State, Adapter, Strategy, Decorator and Abstract Factory would be covered.Course Outline1. Introduction To Design Patterns, Introduction To Java, Some OO Design Principles , The Observer Pattern, The Template Method Pattern (6)2. Factory Patterns: Factory Method and Abstract Factory, The Singleton Pattern, The Iterator Pattern, The Composite Pattern, The Facade Pattern (6)3. The State and Strategy Patterns, Functors and the Command Pattern, The Proxy Pattern (5)4. RMI, The Adapter Pattern, The Decorator Pattern (4)5. Dynamic Proxies In Java, The Chain of Responsibility Pattern, Concurrency Patterns, The Visitor Pattern, Anti Patterns (5)6. Layer, Pipe and Filters, Black Board Broker, Case Studies (4)Text Books1. Design Patterns - Elements Of Reusable Object-Oriented Software, Erich Gamma, Richard Helm, Ralph Johnson, and John Vlissides,2. Head First Design Patterns, Eric Freeman and Elisabeth Freeman3. Applied Java Patterns, Stephen Stelting and Olav Maassen,4. Java Design Patterns - A Tutorial, James W. Cooper,5. Refactoring To Patterns, Joshua Kerievsky,42Functional Programming (Professional Elective for CSE & IT 3L)SyllabusFunctional Programming: (OE)Prerequisites: Basic Mathematics.Objective: master foundational techniques from the paradigm of functional programming. be trained in using abstraction to structure programs. be able to explain and use recursion in general, as well as know how to distinguish between recursive and iterative processes. be able to write and use higher-order functions. master techniques for delayed evaluation for working with infinite data structures such as streams. have insight in different models for understanding how code is evaluated.Course DescriptionThis course aims to make functional techniques and thought patterns part of programming skills of the students. This course presents the functional programming paradigm, based on the idea of functions as "first-class" values that can be computed and operated. Functional languages provide great power of expression while maintaining simplicity, making it easier to write correct and maintainable software. Upon successful completion of the course, students would be able to analyze problems and apply functional programming concepts and techniques to solve the problems.Course Outline (To be covered in 30 lectures)1. Introduction, Problem Solving with Functional Language, Programming with functions, List constructors and selectors, Recursive functions, Accumulating parameters, Local definitions, Higher Order functions, Dot notation, and example simple functional programs (12)2. Un-typed and Typed Lambda Calculus and Combinators, Term structure and substitution, alpha and Beta reductions and Beta Equality, Normal Form, Combinators, Church Numerals, Reduction Rules, Y-Combinator, Bracket Abstraction, Standard Combinator Expressions, Typed Lambda Calculus and Reduction Rules (10)3. Lambda Calculus Semantics: Reduction Machines SECD Machine , Graph Reduction Machine, Lazy/delayed Evaluation, (8)Text Books1. Functional Programming : Application and Implementation by Peter Henderson2. Lambda Calculus, Combinators and Functional Programming by G. Revesz3. Lambda Calculus and Combinators : An Introduction by J. Roger Hindley and Jonathan P. Seldin43Genetic Algorithm (Professional Elective for CSE & IT 3L)SyllabusGenetic Algorithm: (OE)Prerequisites: Fundamentals of Artificial Intelligence, Basic Mathematics, Knowledge of a programming language.Objective: The aim of the course is to introduce genetic algorithms and to give students practical experience in implementing and experimenting with them. The course will equip them to be able to assess the suitability of genetic algorithms for specific problems.Course DescriptionIn this course students will study Genetic Algorithm and its application to optimization problems. The course covers Basics of Optimization, Optimization Problems, Point to Point Algorithms, Simulated Annealing, Population Based Algorithms, Brief Overview of Evolutionary Computation, Genetic Algorithms (Theory and Advanced Operators), Genetic Representation, search operators, selection schemes and selection pressure, Operators on Real-valued Representations, Niche and fitness sharing, Particle Swarm Optimization, Memetic Algorithms and Real Life application of Evolutionary Algorithms.Course Outline (To be covered in 30 lectures)1. Basics of Optimization, Optimization Problems, Point to Point Algorithms, Simulated Annealing (3)2. Population Based Algorithms, Brief Overview of Evolutionary Computation, Genetic Algorithms (Theory and Advanced Operators), Genetic Representation, search operators, selection schemes and selection pressure. (7)3. Operators on Real-valued Representations, Niche and fitness sharing, Particle Swarm Optimization, Memetic Algorithms (7)4. Evolution Strategies, Genetic Programming, Evolutionary Programming, Differential Evolution (6)5. Constraint Handling in optimization problems , Real Life application of optimization Algorithms, Introduction of Multi-objective Evolutionary Algorithms (7)Text Books1. Genetic Algorithms in Search, Optimization & Machine Learning by D E Goldberg2. Multi-Objective Optimization Using Evolutionary Algorithms by K.Deb3. Handbook on Evolutionary Computation by T. Baeck, D. B. Fogel, and Z. Michalewicz (eds.)44Network Administration (Professional Elective for CSE & IT 3L)SyllabusNetwork Administration: (OE)Prerequisites: Basic knowledge of Computer Networks.Objective: To learn about the network and how the data route.Course DescriptionThe course is designed to provide students with essential knowledge and skills that an effective network administrator must possess. It provides an overview of the essential TCP/IP protocols, and discusses how to properly configure and manage the network services based on these protocols (including DNS, DHCP, AD/LDAP directory services, print and file servers, NFS/NIS, and routing services). The course also takes up various issues like Configuration management, accounting management, Fault and disaster management, security management and performance management.Course Outline (To be covered in 30 lectures)1. Introduction, Basic System Administration (3)2. Windows Installation, Linux Installation and Package Management, Backup and Security, Monitoring and Managing Processes/Daemons, Scripting basics and start-up scripts (8)3. Unix Networking, Network Protocols - TCP, IP, UDP, NetBIOS, TCP/IP Concepts and Configuration - the basics, Sub netting Implementation, Basic Network Trouble-Shooting and Monitoring Tools (8)4. Server configuration and management, DHCP, NIS, NFS, LDAP and Samba (6)5. Apache Web Server with PHP, DNS, BIND and Sendmail, Tools like Webmin, Webalizer, and Phpmyadmin; Security and firewall (5)Text Books1. TCP/IP Network Administration?, by Craig Hunt,2. Neural Networks and Learning Machines by S. Haykin3. Artificial Neural Networks by Robert J. Schalkoff4. Multi-Objective Optimization Using Evolutionary Algorithms by Deb Kalyanmoy5. Genetic Algorithms + Data Structures = Evolution Programs by Z Michalewicz45Neural Networks (Professional Elective for CSE & IT 3L)SyllabusNeural Network(OE) Prerequisites: Multivariate calculus and linear algebra.Objective: gain familiarity with a wide variety of neural network models and their applications Develop capabilities for creating and using neural network models. develop knowledge of the state-of-the-art in neural networks, and Gain some mathematical understanding of neural network models. Gain experience in using computational tools such as neural networks to perform computational experiments leading to new theoretical insights.Course DescriptionThe course is an introduction to neural networks. Neural networks provide a model of computation drastically different from traditional computers. Typically, neural networks are not explicitly programmed to perform a given task; rather, they learn to do the task from examples of desired input/output behavior. The course introduces biological information processing followed by an overview of the most important artificial neural network architectures and algorithms such as perceptrons, backpropagation, Hopfield and Boltzmann networks, self-organizing maps, adaptive resonance theory, reinforcement learning, and neuroevolution.Course Outline (To be covered in 30 lectures)1. Introduction, Brain Physiology, Neuron Model and Network Architectures (4)2. Nonlinear dynamical system theory (6)3. The Hopfield Model, Spin Glasses, Stochastic Neural Networks, Boltzmann Machine (8)4. Multilayer Feedforward Networks For Supervised Learning(6)5. Unsupervised and Competitive Learning Algorithms, Bifurcating Neural Networks (6)Text Books1. Neural Networks: A Comprehensive Foundation by S. Haykin,2. Neural Networks and Learning Machines by S. Haykin3. Artificial Neural Networks by Robert J. Schalkoff4. Multi-Objective Optimization Using Evolutionary Algorithms by Deb Kalyanmoy5. Genetic Algorithms + Data Structures = Evolution Programs by Z Michalewicz46Service Oriented Software Engineering (Professional Elective for CSE & IT 3L)SyllabusService Oriented Software Engineering (OE)Objective:1. To introduce the idea of service-oriented architectures2. To explain the notion of a reusable service, based on web service standards, that provides a mechanism for inter-organisational computing;3. To describe the service engineering process that is intended to produce reusable web services.4. To introduce service composition as a means of application development;5. To show how business process models may be used as a basis for the design of service-oriented systemsPrerequisites: Software Engineering, Service-oriented analysis and design, Service oriented Modeling.Course DescriptionService oriented software development paradigm is becoming the delivery model by all major IT companies. This course is intended to introduce the students with this paradigm. In this course students shall study the fundamentals of Service Oriented Software Engineering. Prerequisite for this course is course on Software Engineering.Course Outline (To be covered in 30 lectures)1. Concepts of Service orientation (8)2. Service oriented Software architecture concepts (5)3. Requirements Analysis & Design Process (7)4. Service Testing and Estimation models (6)5. Cloud based services models (4)Text Books1. Service Oriented Architecture – Concept Technology & Design by Thomas Earl2. Enterprise SOA – Designing IT for Business Innovation by Woods & Mattem3. Web Service Essentials, Eiban Cerami, O’Reilly47XML and Applications (Professional Elective for CSE & IT 3L)SyllabusXML Based Applications (OE)Objective:1. To familiarize students with various XML based applications with the help of case studies.2. To be able to develop new applications using XML schema.Prerequisites: Fundamental concepts of XML including document and language creation and implementation, XML SchemaCourse DescriptionThis course introduces students to the basic concepts of the eXtensible markup language (XML). XML has made a major impact in almost every aspect of software development. Designed as an open, extensible, self-describing language, it has become the world-wide standard for data and document delivery on the Web. Students will be instructed as to the purpose of an XML document and what it consists of, in how a Document Type Definition (DTD) or schema is used to validate an XML document and the extensible style language (XSL) to transform XML documents into HTML/XHTML. XML-related technologies continue to develop, to enable validation, navigation, transformation, linking, querying, description, and messaging of data. Students would be exposed to such wide range of application domains.Course Outline (To be covered in 30 lectures)1. Emerging Technologies; XML Documents: Syntax, Well formed and Valid; CCS and XHTML; Document Type Definition(DTD); XML Schema : XSD, XDR, Examples; JavaScript (12)2. SAX and DOM Parser and APIs, Example of API usage; XPATH, XLink, Xpointer; XSL: XSLT (10)3. Applications: RDF and RDFS, JENA API, Case Study (8)Text Books1. XML The Microsoft Way By Peter G. Aitken2. Learning XML By Erik T. Ray and Christopher R. Maden3. XML How to Program By Harvey M. Deitel, Paul J. Deitel, Tem R. Nieto, Ted Lin and Praveen Sadhu48Professional Elective III & IV(Pool – 2)49Distributed and Parallel Algorithms (Professional Elective for CSE & IT 3L-0T)SyllabusDistributed & Parallel Algorithms (OE)Prerequisites: Basic Algorithms and Data Structures.Objective: Parallel and distributed architectures appear in a wide range of areas including networking, computer architecture, databases, image processing, artificial intelligence, numerical computing, symbolic computing, and other areas. Distributed and parallel systems are characterized by concurrency, large scale, peculiar demands for resources, etc. Such systems require skills and knowledge that dicer substantially from sequential programming experience. This course serves to introduce the students to the computational and algorithmic aspects of parallel and distributed computing. Thus, this course is appropriate for students wishing to do research and thesis work in a variety of areas of computer science.Course DescriptionThis course is an introduction to distributed and parallel algorithms design. Aim is to acquaint students with the basic concepts of parallel and distributed computing. The course aims to look into the general principles of parallel and distributed algorithms and their time complexity.Course Outline (To be covered in 30 lectures)1. Introduction, architectures and languages for parallel and distributed processing. (3)2. Abstract models of parallel computing, PRAM (Parallel Random Access Machine). Distributed and parallel algorithms and their complexity. Interaction between processes, communication, synchronization. (9)3. Topologies, synchronous and asynchronous algorithms. Algorithms for parallel sorting. Algorithms for parallel searching. (6)4. Parallel matrix operations. All prefix sums and their applications. Graph and list algorithms. Synchronization algorithms and tasks. (6)5. Mechanisms and language constructs for synchronization. Recently published algorithms.(6)Text Books1. Parallel Computation, Model and Methods by Akl,2. An Introduction to Parallel Algorithms, by J’aJ’a, J3. Introduction to Parallel Algorithms and Architectures: Arrays, Trees, Hypercubes by Leighton,4. Synthesis of Parallel Algorithms by J. H. Rief,5. Introduction to Distributed Algorithms by Gerard Tel,50E-Commerce (Professional Elective CSE & IT 3L)SyllabusE-Commerce (OE)Prerequisites: Computer Information Systems , Business Data Management , System Analysis and Design .Objective: have an understanding of essential e-Commerce concepts and technologies and skills related to the management and application of e-Commerce and e-Business approaches . have an understanding of the technological, capital and social infrastructure for commercial activities such as buying and selling, marketing and advertising, supply-chain management etc. have hands on, real-life experience with electronic commerce applications . be able to define and explain the main issues facing businesses engaged in the planning and implementation of e-Business strategies . identify and define the main e-Business models currently being adopted by organizations have an understanding and ability to assess the strategic relevance of e-Commerce in shaping both inter-organisational relationships and intra-organisational structures and processes critically evaluate the design of e-Business sites and discuss human, organisational and social implications of electronic commerceCourse DescriptionThe growth of the Internet continues to have a tremendous influence on business. Companies and organizations of all types and sizes are rethinking their strategies and how they run their operations. This new course in the Temple E-Marketing program challenges students to explore the realities and implications of e-commerce from a marketer's perspective. Business-to-consumer (B2C) and business-to-business (B2B) e-commerce markets are examined. The course introduces students to a wide range of electronic commerce issues for marketers, as a foundation for continual learning in the dynamic e-commerce environment.Course Outline (To be covered in 30 lectures)1. Introduction to e-Commerce and Network Infrastructure for e-commerce. [4]2. E-commerce Models, e-Advertising & Marketing [6]3. Electronic Payment Systems and Electronic Data Exchange [6]4. E-commerce Security [4]515. e-CRM [6]6. Mobile Commerce [4]Text Books1. Introduction to E-commerce by Jeffrey F.Rayport & Bernard J.Jaworski2. Frontiers of E-commerce by Kalakota & Winston3. E-Commerce- Strategy technologies and Applications by David Whiteley4. E-Commerce-Concepts, Models & Strategies by C.S.V. Murthy5. E-Commerce by Perry52Gaming and Animation (Professional Elective for CSE & IT 3L)SyllabusGaming and Animation (OE)Prerequisites: This course requires general familiarity with computer concepts, an interest in and experience with games, and a vivid imagination.Objective: This course gives students a solid understanding of designing, modeling and implementing a game.Course DescriptionThe purpose of this course is to give students a thorough understanding of computer animation and gaming. The course introduces camera and vehicle animation, parent/child hierarchies, character rigging, character animation, facial animation, lip syncing, physical simulations, motion capture for gaming.Course Outline (To be covered in 30 lectures)1. Introduction, Fundamental Principles of Animation and gaming (6)2. Rigging & Posing Techniques, Fundamentals of Character Animation, Facial Animation and Lip Sync Techniques (8)3. Fundamentals of Motion Capture, Principles of Motion Simulation (6)4. Game design principles and processes (8)Text Books1. Fundamentals of Game Design. By E. Adams.2. The Art of Game Design by J. Schell3. Computer Animation: Algorithms and Techniques by Rick Parent53Information Retrieval (Professional Elective for CSE & IT 3L)SyllabusInformation Retrival (OE)Prerequisites:Basic knowledge of web design, Basic Programming, data structures, Algorithms, Basic linear algebra, Basic statistics.Objective:To give students a solid understanding of: the genesis and variety of information retrieval situations. the variety of information retrieval models and techniques. design principles for information retrieval systems. methods for implementing information retrieval systems. characteristics of operational and experimental information retrieval systems. methods and principles for the evaluation of information retrieval systems.Course DescriptionThis course will cover traditional material, as well as recent advances in Information Retrieval (IR). The course includes the study of indexing, processing, and querying textual data basic retrieval models, algorithms, and IR system implementations. The course will also address advanced topics in IR, including Natural Language Processing techniques, and Web agents.Course Outline (To be covered in 30 lectures)1. Introduction to IR models and methods, Text analysis / Web spidering Text properties (5)2. Vector-based model, Boolean model, Probabilistic model, other IR models; IR evaluation and IR test collections; Relevance feedback, query expansion (8)3. Web search: link based and content based; Query-based and content sensitive link analysis; Search engine technologies (8)4. Text classification and clustering; Question answering on offline and online collections (5)5. Personalized IR, Cross-language IR, Web 2.0, (4)Text Books1. Introduction to Information Retrieval by Christopher D. Manning, Prabhakar Raghavan, Hinrich Schütze (available online)2. Information Retrieval: Algorithms and Heuristics. By D.A. Grossman, O. Frieder3. Readings in Information Retrieval by K.Sparck Jones and P. Willett54Pattern Recognition (Professional Elective for CSE & IT 3L)SyllabusPattern Recognition (OE)Prerequisites: Analysis of algorithms, Calculus, Introductory Statistics, Linear Algebra.Objective: Learn the fundamental concepts and applications of pattern recognition. Learn the concepts of Bayes decision theory. Understand the concepts of linear and nonlinear classifiers. Understand the concepts of feature selection and generation techniques. Understand the concepts of supervised learning and system evaluation. Develop some applications of pattern recognition.Course DescriptionThe emphasis of the course is on algorithms used for pattern recognition. Pattern Recognition is assigning a meaningful or classifying label to the elements of the input data. It uses the concepts of classification and clustering to separate the interclass elements. This information can then be used to classify or recognize new data using supervised or unsupervised learning methods and classifiers such as Support Vector Machine, Hidden Markov Model and Linear Discriminant Analysis. Pattern recognition has several important applications in the fields of data mining, artificial intelligence, networking and image processing. The prerequisites of the course are basic knowledge of statistics and linear algebra along with the concepts of probability theory.Course Outline (To be covered in 30 lectures)1. Introduction to Pattern Recognition, Feature Detection, Classification, Decision Theory, ROC Curves, Likelihood Ratio Test, Linear and Quadratic Discriminants, Fisher Discriminant, Sufficient Statistics, Coping with Missing or Noisy Features, Template-based Recognition, Feature Extraction, Eigenvector and Multilinear Analysis (10)2. Training Methods, Maximum Likelihood and Bayesian Parameter Estimation, Linear Discriminant/Perceptron Learning, Optimization by Gradient Descent, Support Vector Machines, K-Nearest-Neighbor Classification (6)3. Non-parametric Classification, Density Estimation, Parzen Estimation,Unsupervised Learning, Clustering, Vector Quantization, K-means, Mixture Modeling, Expectation-Maximization (6)4. Hidden Markov Models, Viterbi Algorithm, Baum-Welch Algorithm, Linear Dynamical Systems, Kalman Filtering, Decision Trees, Multi-layer Perceptrons, Reinforcement Learning with Human Interaction (8)Text Books1. Pattern Classification by Richard O. Duda, Peter E. Hart and David G. Stork2. Pattern Recognition and Machine Learning by C. M. Bishop3. Pattern Recognition by S. Theodoridis and K. Koutroumbas55Semantic Web (Professional Elective for CSE & IT 3L)SyllabusSemantic Web (OE)Prerequisites: Basic Web technology like html.Objective: The aim of the course is to make the students familiar with the Semantic Web, with technologies used on the Semantic Web, and with applications using Semantic Web technologies. The course will focus on the theoretical background of various languages on the Semantic Web such as RDF, SPARQL, OWL, and F-Logic (Programming), and the practical use of these languages on the Semantic Web. In addition, the course will focus on important application areas for Semantic Web technology, namely Web Services and Life Sciences.Course DescriptionThis course introduces techniques that are useful stand-alone and can be integrated for building a semantic web. It will review XML with Document Type Definitions and Schemas; transformation/inference rules in XSLT, metadata with RDF (Resource Description Framework); metadata taxonomies with RDF Schema; description logic and the W3C ontology language OWL 2; as well as integrating these techniques for ontology/rule-based multi-agent systems. Students may note that besides enabling quick and accurate web search, semantic web may also allow the development of intelligent internet agents and facilitate communication between a multitude of heterogeneous web-accessible devices.Course Outline (To be covered in 30 lectures)1. Review of XML; Meta-model and Meta-data, RDF & RDFS; OWL; Ontology Engineering and tools (12)2. Description Logic(DL); Programming with DL; Example Application (12)3. Knowledge Acquisition and Management System, (6)Text Books1. A Semantic Web Primer by Antoniou, Grigoris and Frank van Harmelen2. The Description Logic Handbook: Theory, Implementation and Applications by Franz Baader, Deborah L. Guinness, Daniele Nardi, and Peter F. Patel-Schneider (Eds.)3. An Introduction to Description Logic by Daniele Nardi and Ronald J. Brachman56Software Metrics & Quality Assurance (Professional Elective for CSE and IT 3L)SyllabusSoftware Metrics & Quality Assurance (OE)Prerequisites: Software engineering process, analysis, design etc.Objective: This course introduces concepts, metrics, and models in software quality assurance. The course covers components of software quality assurance systems before, during, and after software development. It presents a framework for software quality assurance and discuss individual components in the framework such as planning, reviews, testing, configuration management, and so on. It also discusses metrics and models for software quality as a product, in process, and in maintenance. The course will include case studies and hands on experiences. Students will develop an understanding of software quality and approaches to assure software quality.Course DescriptionIn this course students will study the foundational concepts of measurement of various aspects of software during the entire course of its development. The course takes up various existing metrics and tools that measure various activities of the software development. Topics such as Property-oriented measurement, Meaningfulness in measurement, Measurement quality, Measurement process, Scale, Measurement validation, Object-oriented measurement are covered. Students may note that the course is credited only after having undergone Software Engineering.Course Outline (To be covered in 30 lectures)1. The state of IT project management & basics of measurement (6)2. Measuring internal product attributes: size and structure (6)3. Measuring cost and effort (6)4. Measuring external product attributes: Quality & Reliability (6)5. Software test metrics (6)Text Books1. Software Metrics: A Rigorous and Practical Approach by N.E. Fenton and S.L. Pfleeger2. Metrics and Models in Software Quality Engineering by Stephen H. Kan3. Software Project Management in practice by Pankaj Jalote4. Software Project Management by Bob Hughes and Mike Cotterell57Software Testing (Professional Elective for CSE & IT 3L)SyllabusSoftware Testing (OE)Prerequisites: Software engineering and Software project management.Objectives: To understand the fundamental of software testing, different approaches to testing, managing test cases and different testing strategies.Course DescriptionIn this course students shall study the fundamentals of testing, various approaches to testing, managing test cases and various testing strategies. Students may note that the course is credited only after having undergone Software Engineering and/or Software Project Management.Course Outline (To be covered in 30 lectures)1. Fundamentals of Testing and its current state of art (8)2. Various approaches to Testing (6)3. Test planning and Management (6)4. Test Strategies - Preventive, Reactive Approach, Analytical, Heuristic, Configuration Management (6)5. Mutation Testing & Testing Object Oriented Software (4)Text Books1. Software Testing Techniques by Borris Beizer2. Software Testing – A Craftman’s Approach by Paul C. Jorgensen3. Software Testing by Hambling, Samaroo & Williams.4. Software Testing Practice: Test Management by Spillner, Rossner, Winter & Linz58Theory of Virtualization (Professional Elective for CSE & IT 3L)SyllabusTheory of Virtualization (OE)Prerequisites: Operating system and Computer network.Objectives: Understanding the skills and knowledge related to the concepts and principles of virtualization, the mechanisms and techniques of building virtualized system and virtualization-enabled processing scenario.Course DescriptionThis course provides description of the concepts of virtualization and the properties of virtualization that make it a powerful technology. It contrast different forms of virtualization and focus on system level virtualization which has become very popular lately in the computer industry. It describes various architectures for implementing system-level virtualization. Upon completion of this course, students will possess the skills and knowledge related to the concepts and principles of virtualization, the mechanisms and techniques of building virtualized systems, as well as the various virtualization-enabled computing paradigms. Further, they will also gain knowledge about some State-of-the-art virtualization software and systems through their course projects. The basic courses on Operating System and Computer Networks are prerequisites.Course Outline (To be covered in 30 lectures)1. Introduction, Overview of virtualization (8)2. Hardware/Server virtualization (8)3. Network virtualization (8)4. Virtual machines (6)Text Books1. Virtual Machines: Versatile Platforms for Systems and Processes by James E. Smith, Ravi Nair,2. Virtualization: From the Desktop to the Enterprise by Chris Wolf, Erick M. Halter3. Network virtualization by Kumar Reddy, Victor Moreno,4. Advanced Server Virtualization: VMware and Microsoft Platform in the Virtual Data Center by David Marshall, Wade A. Reynolds,59Web Mining (Professional Elective for CSE & IT 3L)SyllabusWeb Mining (OE)Prerequisites: Data mining, Data Base.Objectives: Web usage mining is the process of extracting useful information from server. Web Usage Mining is the application of data mining techniques to discover interesting usage patterns from Web data in order to understand and better serve the needs of Web-based applications.Course DescriptionThe course is an introduction to web mining technologies. Though the Web is rich with information, gathering and making sense of this data is difficult because the documents of the Web are largely unorganized. The course will cover machine learning techniques to mine the Web and other information networks, social networks, and social media. Applications to search, retrieval, classification, and recommendation would be studied. Various models to explain the dynamics of Web processes will also be emphasized.Course Outline (To be covered in 30 lectures)1. Introduction, Practical web mining applications overview (3)2. Natural Language Processing methods used for web information retrieval (6)3. Web Content Mining (5)4. Web Structure Mining (5)5. Web Usage Mining (6)6. Specific applications and case studies (5)Text Books1. Web data mining: exploring hyperlinks, contents, and usage data by LIU, B.2. Mining the Web - Discovering knowledge from hypertext data, by Soumen Chakrabarti,3. Ontology learning and population from text : algorithms, evaluation and applications by CIMIANO, P.60Programming Tools I ( III Semester CSE and IT 3P)Lab DescriptionThis is first independent lab course in programming tools which intends to introduce shell programming skills. UNIX is popular alternative to the Windows environment, especially in high-performance PC Linux servers and other UNIX-based web servers. Topics include: Unix utilities and file structure, Links and symbolic links, Data processing and process control in the Unix shell, Shell programming, Regular expressions, Exposure to different shells like bash, csh, ksh. Introduction to the Python/Perl programming in the Unix environment.Programming Tools II ( IV Semester CSE and IT 3P)Lab DescriptionThis is second independent lab course in programming tools which intends to introduce programming involving system calls. System calls are commands that are executed by the operating system. System calls are the only way to access kernel facilities. In this lab course students would learn to use these system calls as file system, multitasking mechanisms and the interprocess communication primitives.Programming Tools III ( V Semester CSE and IT 3P)Lab DescriptionThis is third independent lab course in programming tools which intends to introduce web programming skills. The web is an integral part of society and our lives. The web browser has also grown to be a critical piece of software on many platforms: PC, Laptop, mobile devices, and video game consoles. This course will follow the course tradition of "looking under the hood," exploring ways to create web content and applications.Note: Other labs are associated with respective theory courses and hence do not require explicit description.61Computer Programming ( I/II Semester All Branches)SyllabusCourse DescriptionThis is a first course in programming which intends to introduce students to the foundations of computing, programming and problem-solving. Aim is to develop basic programming skills necessary for engineering education. Students would learn C/C++ programming in a Linux environment. This course has an associated lab with it.Course Outline1. Introduction, LINUX Commands, editors, Files & Directories, Design of algorithms (4)2. Writing a Simple Program: Learning the form of a C program, Declaring variables, designing program flow and control, using standard terminal I/O functions. (4)3. Fundamental Data Types and Storage Classes, Operators and Expressions Conditional Program Execution Loops and Iteration, Introduction to Abstraction, functions, (6)4. Arrays, Pointers, Structures (6)5. Introduction to Object Oriented Programming concepts, Classes and Objects, Important C++ constructs (6)6. The Standard C/C++ Preprocessor, The Standard C/C++ Library (4)Text Books1. How to solve it by Computer by R. J. Dromey2. The C Programming Language by Brian W. Kernighan, Dennis M. Ritchie3. On to C++ by P H Winston ( also available online)4. Structure and Interpretation of Computer Programs by Harold Abelson and Gerald Sussman with Julie Sussman, (Also available online)5. Herbert Schield, Complete reference in C,