[Computer Programming Books Pdf Free Download
Laurice Whack
There are lots of books about programming out there, and it seems Code Complete is pretty much at the top of most people's list of "must-read programming books", but what about The Art of Computer Programming by Donald Knuth? I'm a busy person, between work and a young family I don't have a ton of free time, so I have to be picky about how I use it.
I'm wondering - has anybody here read 'TAOCP'? If so, is it worth making time to read or would some other book or more on-the-side programming like pet projects or contributing to open source be a better use of my time in terms of professional development?
DISCLAIMER - For those of you who sport "Knuth is my homeboy" t-shirts, don't get me wrong - I want to read it, but I'm just wondering if it should be right at the top of my priority list or if something else should come first.
TAOCP is an utterly invaluable reference for understanding how the data structures and algorithms that we use every day work and why they work, but undertaking to read it cover-to-cover would be an extraordinary investment of your time.
No, it should not be at the top of your priority list. I've got a full set and I have NOT read the whole thing. I've used it (so far) as a good reference on certain problems (it was invaluable in my understanding of randomness and the testing of random generators, for instance). Whenever a CS topic comes up that I don't have a REALLY good handle on, I tend to grab the relevant bit of TAOCP as a good step in my understanding.
It's one of those books (well, collections of books) that is good to read early in your career because it really gives you good insights you normally wouldn't get to until later, but it's not essential to survival until you graduate to that part of your career where you don't just code, you choose the toolbox. This is the point where you really want to study algorithms, hopefully already understand language design a bit, and have a very broad understanding of what tools, languages, and systems are out there, and how each one fits into the ecosystem of things you can draw on for a particular project.
In other words: it's big-picture learning, so if you are obsessive like me read it now, if you aren't, it's okay to put it off until you start yearning to move up the ladder and become a big picture guy.
TAOCP is a great work, but reading it would be a terrible time investment for a practicing software developer.If you do it you will be sacrificing couple of years (thats how long will it takes) of your professional self-improvement budget to learn too much about too little.
At the same time you can buy one or several volumes of TAOCP, look it through to understand what areas does Knuth covers in it, and keep it in your library in case you will actually need some information from it in your day-to-day work. My educated guess is that you wouldn't and that is another reason why I do not advise trying to read. But if you will find yourself referencing it often enough, then you will know that it is well worth your time to read it cover to cover.
Having recently undertaken this very task, I can say that the way he writes is very enjoyable and the problems are labeled (according to difficulty) very aptly. Get the first volume and read chapters 1 and 2 and see how you like it.
I'm firmly in the camp of folks that feel that every developer should make the investment in getting the books at some point (and it's getting easier now that it looks like they are being reprinted in paperback) but on the same token, I would also be hard pressed to believe that someone would sit down and read them all from cover to cover.
The best approach to them - if you don't have a commute to work where you have free time to sit and read - is to read enough of them to know where to find things in them and then to read a full chapter when ever you find yourself using them as reference books for a given problem. With Google and Stack Overflow it's not as common to be reaching for reference books, but in some cases you may find that the books provide some insight that you would have to send some extra time looking for on the internet.
He's up to like 4 volumes and 5 fascicles (whatever those are) so completing the books would be probably better than a university course in the fundamentals of computer science and make you nearly the best programmer ever.
It's not something most people will want to sit down and read cover-to-cover, no. It is an incredibly invaluable reference, and it's certainly good to pick it up, pick an interesting section, read over it, and do some exercises. But the encyclopedia comparisons made above are pretty apt... it's big, extensive, and detailed. And some of the "exercises" are research problems that might take years to solve.
I recently learned that Gerald M. Weinberg, computer scientist and author of many books on programming and human behavior, had passed away. I was a bit saddened by this news, yet grateful for the knowledge and wisdom he shared through his books.
Many people say that TAOCP is not supposed to be read as a book (actually a volume of books), but if I decide to go that way, which math/computer science books/topics do I need to study to help me follow it? There is a related question on stackoverflow but I would like to read the suggestions of cs.se users.
Indeed the preface states some prerequisites on page v, which he sumsup into "the single requirement that the reader should have alreadywritten and tested at least, say, four programs for at least onecomputer".
Starting page viii, he gives a few words regarding mathematicalcontent."the material has been organized so that persons with no more than aknowledge of high school algebra may read it, skimming briefly overthe more mathematical portions; yet a reader who is mathematicallyinclined will learn interesting mathematical techniques [...]". Hecalls his organization a dual level of presentation.
"Concrete Mathematics: A Foundation for Computer Science" by Graham, Knuth and Patashnik is a textbook in a way that TAOCP isn't. Moreover, in a sense, it is a summary of the maths that Knuth used throughout his career (apart from the formal language stuff; people forget that Knuth's greatest research contribution to computer science is actually the theory of LR parsing) in convenient textbook form.
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