Maybe worth mentioning that the author has also written a book, Midnight's Simulacra, which I found quite enjoyable. Kinda Pynchon meets DFW meets Greg Egan, if Egan was focused more on gritty engineering rather than abstruse physics.

Which one tells me how to do a hadouken?

Some of these books are quite old (like 20 years old or more), I wonder if there isn't newer books on the same subject but with more recent algorithms or methods.

For instance the book "Metric and Multidimensional Data Structures" from Samet, is described as very encyclopedic, but it's from 2006, isn't it missing new research? I'm not sure a twenty years old encyclopedia is very useful in computer science as the field move somewhat fast.

So how do you call people who love to read books like these in their free time, but hate working in the software industry? I hate with passion the “engineering talks”, the “architecture review sessions”, the “PR code reviews”, etc. Have been working for over 15 years for multiple different companies. I never liked a single one of them.

When family asks if i like my job, it’s not so straightforward to answer

I rather like this list of books. Anybody who follows the "Church of Edsger Dijkstra" can never go wrong :-)

I was rather surprised by the author's mention of The Anatomy of a High-Performance Microprocessor which few people have heard of. It is a great concrete case-study to follow and understand.

Network Algorithmics is an excellent guide to performance engineering (app level/OS/hardware). There is an updated 2nd edition which i have not yet browsed. It is relevant for everybody and not just for people making networking devices only.

Stepanov's From Mathematics to Generic Programming and The Elements of Programming shows you how to map your programming language constructs onto abstract algebra such that your "Program" implements a "Model" of that "Theory". Do not go to the second book (which should be in the advanced section) without reading the first more introductory book.

Crochemere et al's, Algorithms on Strings is new to me and seems relevant to NLP (used in LLMs?). Anybody browsed/read this care to share their opinions?

lae, there is nothing about self defense, martial arts or first aids

whats exactly streetfighting scientist ?

There are over 30 books here. Some are quite hefty, e.g. CLRS is over 1000 pages.

Am I supposed to believe the author of this rec list has read all 30+ of these, cover-to-cover?

If so, how many additional books have they read which didn't make the list?

Because I would ideally like their "recommended books" list to be, say, the top 10% of the books they've read. So this list would be most credible if the author has read ~300 books, then recommended the top ~30 to us.

Somehow I doubt that.

Experiment: If you have a favorite CS book, please reply to this comment stating your favorite CS book, and the estimated total number of CS books you've read. I'll bet such a thread would be more valuable/higher-signal than OP.

Deep knowledge! How passé. Haven’t you heard that with AI knowing things is out and being nutrient-dense is in? Did you think Knuth or Dijkstra would help you stand out in the slurry? Don’t you know that in processing individual flavors are chemically stripped and a flavor “pack” is then applied to provide a uniform consistent taste? Knuth may have been born in Wisconsin but has spent most his life in California, even if that delicate flavor were to survive the stripping process (good luck!), there is no chance it would survive the freezing. And that’s if you are lucky! Most biomass will end up as pellets for the power plants, and I doubt they care about your knowledge of algorithms.

Please do us all a favor and take this yesteryear concept of sharing knowledge and human advice and restrict it to the portions of the internet that have been selected for publication in the “time capsule” scheduled for deep storage under data center 8099FZN, the former site of what you re-enactment nerds call “the Smithsonian”. Or just ask Claude to do it for you. It’s unnecessary expenditure of joules, never teaching.

Streetfighting without math? How quaint.

http://streetfightingmath.com

This is a list of books for programmers, not computer scientists, with the exception of Knuth's book, which is for both.

For example, Hopcroft & Ullman's "Formal Languages and their Relation to Automata" is nowhere to be found, neither is its second edition "Introduction to Automata Theory, Languages and Computation". Nor is there anything else on formal languages and automata, or complexity theory, boolean, propositional, and first-order logic, boolean satisfiability, (gasp) category theory, type theory, and so on and so forth.

So why not? Obviously programming texts are very useful and you have to be on top of that material if you want to call yourself a "computer scientist", but why is all the theoretical computer science missing? Don't "streetfighting computer scientists" need it? How do you get in a fight with someone who knows their finite state automata from their pushdown automata, and don't expect to get a bloody nose?

I love these books, but in a poor job market AND "AI can do it anyway", it's not going to get much attention.

Despite "AI can it" is not even true, anyone with a brain will let AI fill in the details but let a "streetfighting computer scientist" make the architecture AND check the AI contributions. I would tell you to look into how the artcraft applications are made but I bet that's too much trouble too.

How about you just try it? Demonstrate getting claude, the best model, making a big application for you. See if it works. Have it make Excel or Call Of Duty, like seems popular. Try it! It won't work! It'll look a bit like it works but it won't, while using $10k or so in tokens, but critically, what happens when you find flaws.

It will fix bugs, but will systematically require more tokens to do so and bog down more than more. After a few more thousand dollars worth of tokens it starts recreating old bugs every time you ask it to fix something, then takes ages fixing those, and eventually it gets so bad it notices and breaks the process off before it even fixes what you asked.

Maybe that's why both Claude and OpenAI have started making ridiculous amounts of test (I'm all for test driven development, BUT according to me if your test file is more than twice the length of the source, something's gone wrong and you need a better strategy for testing)

For the "Advanced CS Streetfighter" you need;

Understanding Formal Methods by Jean-Francois Monin - This is the best for getting a good grip on the breadth, concepts and sample tools for Formal Mathematics/Specification/Verification. Gives a map of the whole domain. Will force you to learn and understand a large set of mathematics, logic, its mapping to CS-theory/PLT and finally shows how they all come together in specific languages/tools. The chapters alternate between the needed abstract mathematics/logic and concrete languages/tools applying them.

Because everything is so succinct and precise (a graduate course in ~250 pages!), you will need to consult other detailed textbooks/AI tutor to understand difficult concepts. Specifically, you would need to consult detailed texts on the languages/tools you are interested in.

This is particularly important today for use with AI. Without knowing the mathematics/logic involved one cannot direct an agent correctly nor verify its output properly.

I’m always a bit baffled by people who go “you know what people need? A list of 12.000 pages worth of books that would take them multiple years of full-time studying to seriously work through!”.