I'm writing a book about algorithms and Lisp

Paradigms of Artificial Intelligence Programming (Norvig)

That's worth a separate thread. I'm digging deep into analysis and combinatorics[0]. But I'm fairly convinced that the market for this is small. Be sure to look at the situation when doing efforts.

[0] I used to find it impossibly hard to work with trendy frameworks and preferred the mental bliss of hard topics. But at one point you need money and being good enough at making a company work can be a good compromise. As long as it's not too hellish.

A CS degree is just a collection of topics that you study. Look up the topics, find books, articles, etc on the topics, find a mentor, study the topics, "get degree". The only thing missing are metrics but the metrics aren't the point.

My local university has a book store and the books per course are all there so if I wanted to I could pick up all the books for a CS degree and read um. I could find a list of profs too and I bet if I emailed some I could find one that might talk back.

There's all kinds of ways to go about this :)

go visit a campus and just talk to a professor, the usually love the attention.

You can also audit classes for very cheap (or at least it was cheap when i was in school). + I think MIT posts their lectures online for anyone to watch.

So a CS degree is half or even more a math degree. I am yet to find a popular "learn c++ in 24 hours" course that teach you the math needed to think correctly.

The core problem with programming is not the syntax or even the tools, but complexity and abstraction. I.e. programming do not scale well. A 1M LOC program is much different than 100K LOC which is different from 10K LOC, and you need intellectual tools to analyse at different scale.

A non CS programmer usually lack the intellectual tools to analyse problems logically before programming, and jump to code too fast (which is actually encouraged by the "agile" methods, TDD etc).

You don't need a CS degree. It might help, but I dunno. I don't have one, and I am a dev. What you do need is what YOU need, which is to say you have inclinations and limitations.

You'll quickly learn your inclinations as you get into programming, as certain activities will be way feel way more interesting & fun to you. I hate studying things I don't need now, which is a limitation, but that no means does that mean I cannot learn those things.

Back to the BSCS thing. The more competitive a job is, the higher the bar to get that job. High paying dev jobs often have the questionably relevant algo questions. 10 years ago it was questions about pirates with gold coins & moving My. Fuji. In 10 years it might be Alan Turing trivia questions. The only thing you can do to optimize for interviewing is to interview, and it helps to be generally competent in your no niche of choice.

The degree isn't important IMO. What is important is a strong understanding of algorithms, data structures, memory, cache locality, your chosen language runtime, etc. Granted, it depends somewhat what you are doing. If your job is to make wordpress templates then it's probably not as important (not to diminish the people working with wordpress & friends), but still an invaluable thing to learn.

The associated calculus & math you'd learn in school for CS/engineering is also worthwhile to learn.

CS isn't anymore of coherent subject than, say, math. And (much like math), the useful/practical parts that'll get you 80%-90% there in solving arbitrary practical problems aren't all that difficult to learn.

Just learning your data structures and how to implement them will serve you very well for many/most tasks.

One thing I really love about Sandi Metz's POODR is how readable the code examples are.

He is planning on using LeanPub and they support specifying what programming language code snippets are written in so listings tend to look pretty good.

Thanks for the comment. The style issue will be addressed in the next chapter that is entitled "Crash-Course into Lisp"

Going to push back on this. Lisp is written to be "flexed". And people can and should write it however they want. I think treating students like they're all incapable of googling is utterly infantilizing and nothing about it serves any purpose other than stroking the authors ego. The vast, and I mean seriously vast, majority of programming books waste pages and often multiple whole chapters on treating the user like they can't find the documentation, like they can't reason about different syntactical constructions, and it leaves the learner hobbled and weakened when going out into the real world and trying to read, let alone write, actually code to accomplish a real task. People can cry about Paul Grahams style in ANSI lisp, or Let over Lambda, anyone who can work through either of those books is going to be fine reading Practical Common Lisp (or whatever). Also, finally, Common Lisp isn't exactly known for being a "team language" and the overwhelming majority of projects that I know of were originated by one person. I for one hope the author contributes his work in whatever way will he feels like. Lisp is a liberating language to use, we should write about it in the same way

My thought exactly. Lisp is probably okay (if not even one of the better choices) to get the general message transferred, though.

Something like CRLS? That is fairly implementable pseudocode, but maybe still too hand wavey at times.

Isn't that pretty much what CLRS is for?

If you don't know Lisp, it would be basically a pseudocode in prefix notation for you.

It takes some time to get used to reading s-expressions, but it's not that hard at all.

Over at Rosettacode they already ported a lot of stuff in a huge number of languages.

https://rosettacode.org/wiki/Category:Programming_Tasks

As for books, I liked a lot Niklaus Wirth's "Algorithms + data structures = programs" a couple geological eras back. The book was written with Pascal in mind before the OOP era, but given Pascal's simplicity its examples can be easily translated in other languages. I'd consider more modern books if I knew any; the very few I've briefly skimmed in the past seem either too advanced or too abstract.

That is basically what The Art of Computer Programming by Donald Knuth is and I cant recommend the books enough.

Pseudocode isn't perfect though. It's prone to off-by-one errors among other issues. You end up having to describe the specifics of your "flavour" of pseudocode and at that point you've just made a language.. except it's not well thought out and isn't executable anywhere.

TL,DR Just use a language designed for readability, like Python.

The idea of this book is not be a 10th version explaining the same algorithms. It is as more about how to implement those algorithms for real — production-level stuff, so to say. And pseudocode isn't an implementation language, you will not face the same difficulties, and not get to feel the tools

Sigh...

Seriously, you should learn Lisp instead.

> will

That's future tense that you just quoted.

From the first paragraph of the blogpost:

> Now, I'm, finally, at the stage when I can start publishing it. But I intend to do that, first, gradually in this blog and then put the final version — hopefully, improved and polished thanks to the comments of the first readers — on Leanpub.