Sicp Types: Fill & Download for Free

I don’t learn well from books. I’ve read fewer CS books than you’d think¹, and didn’t get much from most of them. Only one book fundamentally changed how I approach programming: The Structure and Interpretation of Computer Programs (SICP).Cover released by MIT Press and the book’s authors under a CC-BY-SA 4.0 license, just like my own answers.SICP gave me a deep appreciation for abstraction as the cornerstone of programming.Before reading the book, I had learned a hodgepodge of specific techniques for building abstractions—design patterns, object-oriented programming (OOP) with classes, basic functional programming—but I did not have a mental framework to unify these ideas. I could apply specific patterns and techniques in an almost rote manner and I had already started developing an intuition for organizing programs, but it was all disconnected.SICP taught me to appreciate and understand abstraction unto itself. OOP, functional programming, types, patterns… all just tools of abstraction. SICP gave me the unified theory of abstraction I needed to see how all these different approaches accomplished the same goal. Understanding what you’re trying to achieve is far more important that learning how to achieve it, but it’s also harder to teach. SICP does a formidable job here.Moreover, SICP taught me how these techniques and approaches were abstractions themselves! Before reading the book, I had read a lot about OOP², and everything I read implicitly assumed that OO features had to be built into the language. OOP wasn’t just one way you could organize your code, it was the way to program and there was only one way to do it: the way built into your language. SICP neatly avoided this trope by using Scheme, where OO features are not part of the language but rather expressed as libraries. Instead of learning how to use OO ideas as if they were handed down from on high, SICP taught me how I might implement OO myself. Not only did this give me a stronger intuition for what OO was, it also showed me how a lot of the specific details of OOP in any given language were not fundamental and immutable, but rather arbitrary design decisions taken by the language’s creator.After demystifying OOP (and functional programming too for that matter), SICP went on and did the same thing to programming languages in general. The book takes you from simply using programming languages to thinking about how you can design and implement them yourself. Sure, you only implement a handful of simple interpreters ignoring real-world concerns like language complexity and performance, but that’s enough: you start to see whatever language you’re using as an abstraction itself, not some ground truth of programming in general. This is a massive shift in perspective! This made me a substantially better programmer across any language I use, which is crucial in a world where more and more languages are used in different combinations. I’ve used something like four or five different languages in my current job alone. Being able to take a mental step back, compare and contrast different languages and apply the same high-level ideas about programming and code organization in different contexts massively improves the quality of my code and the kind of impact I can have across a whole organization.The impact of any book is ultimately deeply personal, and SICP worked particularly well for me. I read it as part of an intro course to CS freshman year of college, which happened to be the perfect time for me. Even in high school, I was already leaning towards programming languages as a field, although I didn’t know it—in fact, I hadn’t even realized programming languages was a field you could study! SICP gave me a solid push in this direction and taught me how these ideas can apply to any kind of software, giving me a powerful understanding of abstraction that acts as a force multiplier in whatever area I end up pursuing.If I could only recommend a single book for programmers—and a single book is all I’m going to recommend here—it would be The Structure and Interpretation of Computer Programs, no questions asked.And, as a bonus, it’s available online for free.footnotes¹ I’m pretty sure I’ve fully read like five books about computer science, as well as two or three language-specific books back in high school. Something like 99% of my reading on programming and CS has been from online articles and papers.² People complain about functional programming evangelism today, but it falls far short of the OO evangelism back when I was learning programming. Have people just forgotten what that was like? Worse yet, it seems to have worked.For a long time—hell, even now, for a lot of people—OOP was considered foundational for programming and CS as a whole. You couldn’t be a good programmer if you didn’t have a bunch of specific OOP knowledge. I learned a bunch of different languages in high school (JavaScript, Perl, C++, Java…), and all the learning materials obsessed about OOP as the One True Way to program. What a time!

Racket and Haskell before Scheme with SICP. Racket is a multi-paradigm language but Haskell and Scheme are not (Comparison of multi-paradigm programming languages).Some reviewers recommend to learn Racket first before reading SICP (Structure and Interpretation of Computer Programs) with Scheme (Amazon.com: Customer Reviews: Realm of Racket: Learn to Program, One Game at a Time! - the reviewers are very excited).SICP for Racket"In DrRacket there is a SICP compatibility language." (Which lang packet is proper for SICP in Dr.Racket?)Others say, that "If you're doing it for the purpose of learning, get there to Haskell. It takes the paradigm to its logical conclusion" (Keith Adams). And there are approaches forSICP for HaskellAnother idea is porting ​SICP to Haskell, and also extending it to gradually introduce type theory. First we’d start off leaning entirely on type inference, and then slowly expand examples to include type signatures and advanced type concepts. (Haskell Now)Facit:Depending on your previous experiences, you should learn Haskell and Racket with SICP, and you do not need Scheme. Haskell seems to be more logical but Racket has more paradigms. The sequence is up to you.sicp scheme racket haskell

The Structure and Interpretation of Computer Programs (SICP) is a wonderful introduction to programming, computer science and—most importantly—abstraction. It does an incredible job of quickly covering basic CS, including the major different programming paradigms. Most importantly, it helps impart a true CS mindset and shows the inherent beauty and elegance of the subject. You can read it for free online.Introduction to the Theory of Computation is one of the most readable texts I've come accross in any discipline. It gives a wonderful introduction to formal languages (not programming languages), computability and complexity. Apart from being a very accessible introduction to theoretical computer science, it also has an innovative structure for teaching proofs which I've found very valuable for learning to reason abstractly and formally without sacrificing clarity. It's well worth reading just for an example of how clear proofs can be.Artificial Intelligence: A Modern Approach (AIMA) is a strong introduction to AI. It covers the high level ideas necessary to approach the field as well as a nice covering set of basic AI algorithms. It's an incredibly popular text used in over 1200 universities.Types and Programming Languages (TAPL) is a good overview of modern programming language design and theory. It's a good place to get a handle on the field as well as catch up with the last few decades of programming language research, much of which is only entering the mainstream now if at all. It's good as both a starting point for learning more advanced languages (like Haskell) and for understanding the design and trade-offs in more popular languages like Java.Introduction to Algorithms is the standard reference on algorithms. It's good for both learning to design algorithms and just learning the standard set most programs rely on.I actually learned algorithms with the prosaically named Algorithms by Dasgupta, Papadimitriou and Vazirani which was not too bad and is available free online.