Ask HN: What are the bibles of Computer Science?
I am building out my CS book collection, and I was curious to see if there is a widely accepted group of textbooks that are considered the bibles of different CS fundamentals. For an example:
* Brian Kerrigan's "C Programming Language" for C language
* W. Richard Steven's "IP/TCP Illustrated" for networking
Thoughts?
56 comments
[ 2.9 ms ] story [ 114 ms ] threadEdit: It's more popular to ignore history, but you can find Shannon's information theory, As We May Think, Cybernetics, etc. along with historical context. It might keep you from pretending you have invented the wheel.
Alan kay listed this on his list of good books: http://www.squeakland.org/resources/books/readingList.jsp
Thanks for that list of books from Alan Kay. He's the one that recommended The Dream Machine to me most recently.
https://mitpress.mit.edu/books/introduction-algorithms
AI, a modern approach (Norvig & Russel) - For classic AI stuff, although nowadays it might fade a bit with all the deep learning advances.
https://www.amazon.com/Artificial-Intelligence-Modern-Approa...
While it's not strictly CS, Tufte's Visual Display of Quantitative information should probably be on every programmer's shelf.
https://www.amazon.com/Visual-Display-Quantitative-Informati...
The C++ Programming Language, 4th Edition
https://www.amazon.com/C-Programming-Language-4th/dp/0321563...
It is amazing how this book can be interpreted as having predicted the necessity of Agile/DevOps long before the tooling was really available to easily enable that methodology.
https://www.amazon.com/Mythical-Man-Month-Essays-Software-En...
The Mind's I: Fantasies And Reflections On Self & Soul
I Am a Strange Loop
...and yes, they are all very challenging reads. On the "computer science" perspective, they are definitely worth reading if you are at all interested in machine learning, artificial intelligence, artificial (and actual) neural networks, and how these subjects relate to the "philosophy of mind" and similar related "hard problems" in CS and mathematics.
You may consider splitting your collection in three parts: those two and software engineering (examples: the mythical man-month, the psychology of computer programming), which itself can be split into a technical and a social part.
Doing that may show gaps in your library/where your interests lie.
For CS, I'll concur with others on these (for algorithms):
I'll add: More on the math side, I found this helped me bridge the gap between Calculus (and other continuous maths) and discrete math topics: SICP is good, and worth recommending, along with the Schemer series (Little, Seasoned, Reasoned). I have both The Reasoned Schemer and The Little Prover here at my desk. I had intended to work through them on my lunch breaks but, well, that hasn't happened yet. I don't know how much these are "bibles" versus good introductions to their topics, not really reference books.My library is at home, I'm trying to run through what all I have and would recommend in particular of that collection.
On the practical, software engineering, side:
Fantastic read on real-world experiences on a large-scale project. Every essay in there is worth reading at least twice, and several are worth rereading every year just in case you forgot the lessons.I am currently wracking my brain to recall the other titles, may edit later.
The C Programming Language K&R
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The 23 Gang of Four (GoF) patterns
"Compilers, Principles, Techniques and Tools", by Aho, Ullman, Sethi, Lam
"Artificial Intelligence: A Modern Approach", by Russell, Norvig
"Computer Architecture: A Quantitative Approach", by Patterson, Hennessy
"Computer Networks", by Tannenbaum
"Operating System Concepts", by Silberschatz
I don't consider it a bible of CS, but it's one of the most playful, imaginative and, essentially, fun, introductory programming books that I've read.
The analogy of the truthiness of a value as an energy or life force that flows through your program, or Ruby's ranges depicted as accordions, are just some examples of the book's approach to visualising some of the aspects of programming that seem so rote after you've used them for a while.
How useful it is to someone learning to program is questionable, as the book's style might get in the way of teaching fundamentals, but it's certainly fun to read as an experienced programmer (imho, of course).
Henderson's FP book: https://www.amazon.com/Functional-Programming-Application-Im...
Watson's Lisp: https://www.amazon.com/Lisp-3rd-Patrick-Winston/dp/020108319...
The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling
Raj Jain ISBN: 978-0-471-50336-1 720 pages April 1991
https://m.youtube.com/watch?v=4U9MI0u2VIE