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Programming Algorithms: A comprehensive guide to writing efficient programs with examples in LispНазвание: Programming Algorithms: A comprehensive guide to writing efficient programs with examples in Lisp
Автор: Vsevolod Domkin
Издательство: Leanpub
Год: 2020
Страниц: 365
Язык: английский
Формат: pdf (true), epub, mobi
Размер: 27.4 MB

There is a lot of books on algorithms, but I haven't seen any that primarily aims to bridge the gap between the theory and practice. This is one of the key distinctions of "Programming Algorithms". It is definitely not the best exposition of the theoretical ideas, but I hope that, instead, it builds sufficient understanding and skill, for the common developer, to start writing efficient algorithmic programs.

In our industry, currently, there seems to prevail a certain misunderstanding of the importance of algorithms for the working programmer. There’s often a disconnect between the algorithmic questions posed at the job interviews and the everyday essence of the same job. That’s why opinions are voiced that you, actually, don’t have to know CS to be successful in the software developer’s job. That’s true, you don’t, but you’d better do if you want to be in the notorious top 10% programmers. For several reasons. One is that, actually, you can find room for algorithms almost at every corner of your work — provided you are aware of their existence. To put it simply, the fact that you don’t know a more efficient or elegant solution to a particular programming problem doesn’t make your code less crappy. The current trend in software development is that, although the hardware becomes more performant, the software becomes slower faster. There are two reasons for that, in my humble opinion:

- Most of the application programmers don’t know the inner workings of the underlying platforms. And the number of platform layers keeps increasing.
- Most of the programmers also don’t know enough algorithms and algorithmic development technics to squeeze the most from their code. And often this means a loss of one or more orders of magnitude of performance.

In the book, I’ll address, primarily, the second issue but will also try to touch on the first whenever possible. Besides, learning the art of solving difficult algorithmic problems trains the brain and makes it more apt to solving various other problems, in the course of your day-to-day work. Finally, you will be speaking the same lingua franca as other advanced programmers — the tongue that transcends the mundane differences of particular programming languages. And you’ll gain a more detached view of those differences, freeing your mind from the dictate of a particular set of choices exhibiting in any one of them.

The book covers:

All the important data structures and algorithms.
Essential tools that help in the development of algorithmic code.
Real-world engineering considerations and constraints that influence the programs that use these algorithms.
Practical use cases of the applications of the algorithms to a variety of real-world problems.

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