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Comment by ericmoritz | Hacker News Reader

I apologize for any offense that I may have given by using the phase "self-taught computer scientist".

This article is my personal recommendation of books that I often recommend to junior developers that are smart but didn't complete a degree and often find their knowledge of basic computer science lacking.

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To be fair, I didn't take offense to "self-taught computer scientist". I took offense to "every self-taught computer scientist".

I'll be the first to admit that university is bullshit and mostly acts as a social signifier. Like I mentioned above, I'm credentialed, and I'll put that on my business cards but between you and me and the internet at large I mostly work as a software engineer.

There are even many problems with talking about "computer science" because for the most part it's treated like a branch of mathematics and its academic circle really hates dabbling in messy empirical data.

Yet, there's a degree of rigour in it. There's an actual underpinning behind a lot of this stuff.

So! Can you be a self taught computer scientist? Certainly! K&R and The Little Schemer just have almost nothing to do with it - even if they might make you into better programmers :).

This gets repeated again and again on HN, but it's not true. I am a CS researcher, and I always have messy empirical data. Systems research almost always has tons of experimental results. A large chunk of our papers are dedicated to the experimental design and results.

I have made this point many times before:

http://news.ycombinator.com/item?id=968013

http://news.ycombinator.com/item?id=690798

http://news.ycombinator.com/item?id=1131606

One of these days I'm going to actually set up a blog, write this point up as an essay, and be able to point to it.

My own personal definition of computer science: everything concerned with computation, both in the abstract and in the implementation.

Please do! And link to the rest of your research :)!

I'm just talking from my own (very) limited personal experience, though, and the Greg Wilson video I linked to (albeit it's been two years since I last watched it).

You can find everything that I have currently published in a peer-reviewed place on my (old) webpage in my profile. I've done lots since graduating (lots), but we've hit a bunch of paper rejections (aarrrrggg), so they're not published yet. I was, however, involved in a paper that we've submitted to a journal, so it has not gone through peer-review yet, but we made a tech report so that others could cite it: http://researcher.ibm.com/files/us-hirzel/tr11-rc25215-opt-c...

That looks interesting! I saved it for later.

From what I can tell (based on HN and other forums), systems research is empirical testing of systems, while theoretical computer science is math heavy. The typical systems paper is "The design, implementation, and performance of a [application] system, using [technology]". While a theory paper is "Proof of the existence of a solution for [problem] in time [O(something)]".

These two branches do talk to each other, but not much.

In general you got it, but CS theorists do more than just algorithmic analysis. They also may be after some other desired, provably guaranteed effect with an algorithm, and they'll say in passing "By the way, this is a linear algorithm, so it's performance isnt an issue." This is true in scheduling, cryptography and probably many other areas. (It's early, sorry.)

You got systems research pretty much head-on, but I would stress the design and implementation part more. That is, CS systems research tends towards engineering, where we claim we made a better whatzit, and then we need to provide a suite of experiments to support our claim.

As a self-taught C software developer, I came here to say the same thing Phillip said.

To it, I would also add that C isn't the "latin" of computer science (if any language is going to prove to be that, it's Lisp, but it's too early to say, other than to say that isn't going to be C).

I'd also suggest that the best book to follow up K&R is Hansen's _C Interfaces and Implementations_.

If I wanted to teach someone to be a computer scientist, I'd look for a book that would help them read papers. I'd also point them towards compiler theory, not so much because it's fundamental computer science (it's a vital applied discipline), but because it exposes you to more real computer science than most other domains.

Do you have a book recommendation to help someone read papers. I spent an couple evenings going over MIT course notes on discrete mathematics to attempt to read a paper on Conflict-free Replicated Data Types <http://hal.archives-ouvertes.fr/docs/00/55/55/88/PDF/techrep...;

What I would give for a book at that time that would help me translate the following:

    merge (X, Y ) : payload Z
       let ∀i ∈ [0, n − 1] : Z.P[i] = max(X.P[i], Y.P[i])

Into

    def merge(X, Y):
       Z = ... new object ...
       for i in range(len(X.P) - 1):
           Z.P[i] = max(X.P[i], Y.P[i])
       return Z

I eventually figured it out but it was a bit rough trying to figure out what all the symbols meant.

Well… it depends on the paper! Some stuff might need more than a single course of background to fully understand.

For more rudimentary papers, any undergrad course on discrete mathematics should get you started. I personally was forced to read http://www.amazon.com/Discrete-Mathematics-Applications-Susa... - and it's pretty decent.

Thanks for the recommendation. That was one of the text books that I looked at but the sticker shock steered me towards free MIT course notes.

Buy it second hand from Amazon - they are much cheaper! ($17)

+1 for the book recommendation - I also have a copy of that.

I don't know if it is true about that book in particular, but if I'm buying a textbook as a resource I usually look for the international editions. They sell near identical versions of the books (shuffle the problem sets around) in other places around for much, much less.

There is a really nice book trying to teach exactly this (among other things) called "The Haskell Road To Logic, Maths and Programming":

http://www.amazon.com/Haskell-Logic-Maths-Programming-Comput...

available for free, according to

http://hackershelf.com/topic/math/

Lisp is the "greek". Older, more free-wheeling. Intellectually more influential but swamped in "the real world" by the latin-speakers.

And full of lambdas.

> books that I often recommend to junior developers that are smart but didn't complete a degree and often find their knowledge of basic computer science lacking.

I think you may be confusing "Computer Science" with "Software Engineering".

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