|Top Computing Theory Book Choices|
|Written by Kay Ewbank|
|Monday, 23 March 2020|
Page 3 of 3
So far the books in this selection have covered the big ideas underlying computer science and programming. The next group of books are all about algorithms, so approach the theory of programming rather than the theory of computer science.
Author: Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein
Mike James described this book as a classic and a must read if you are interested in programming, giving it five stars, and saying that it is an academic text in the sense that it would, and does, make a good basis for a course on algorithms but it is still very readable.
Mike's conclusion is that in addition to forming a good foundation for a first course on algorithms and on data structures, it is also very suitable for individual study. It is a big to large a tome to be a comfortable read but if you have missed out on a formal introduction to algorithms and data structures this is a good place to start and the investment will be repaid as you use the book as a reference work.
Author: George Heineman, Gary Pollice, Stanley Selkow
There are lots of algorithm books, but this one is a little different, according to Mike James who gave it the maximum five stars. A standard algorithm book simply presents common or classic algorithms to do a range of things in the language of choice, but this one isn’t at all academic and it’s a very good and easy read.
Mike's conclusion was that despite not covering much of the academic analysis needed for a computer science course, this book would make a really good basis for such a course or background reading, and is a “keeper” - make room for it on your bookshelf as it’s essential reading and great for making up for what you never learned in Computer Science lectures.
Author: Steven S. Skiena
According to Mike James, this book is well presented with a good balance of theory and practice, managing not to be overly academic or too lightweight to be of use. In view of this he awarded it five stars. The first section - about 350 pages - of the book is about algorithm design - analysis, data structures, sorting and searching, graph traversal, weighted graphs, combinatorial search, heuristics, dynamic programming and finally intractable problems.
The second half is a catalog of algorithms. It doesn't actually give you details of the algorithms in question just a general discussion of the type of methods, what the problems are, variations on the problems, where the problem and solution prove useful and lots of places to look for more detailed information, including implementations.
Author: Thomas H. Cormen
It clearly is possible to write a book that explains algorithms for the general reader - mainly by leaving out runtime analysis and simply supplying the broad ideas - but this isn't it. Even so, if you are up for the math and happy with pseudo code, then this is good starting point.
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|Last Updated ( Tuesday, 24 March 2020 )|