Charles E. Leiserson

apparently the second most cited computer science book, and for good reason. (no, i don't know the top most cited, and no, its not knuth). but, what a vast and exciting array of pseudocode, algorithms, and their data structures! good largley for being rich and dense, but readable. doesn't waste space over explaining, but should be sufficient for most anyone with a active interest.

an interesting feature, with respect to the exercises and especially problems for each chapter, is that i think cormen subscribes to a methodology where the solution to a problem should often require information or intuition not found in the chapter, nor even necessarily in the preceding chapters. you find yourself driving towards solutions that are used in later sections, or revisiting old problems once you find a better solution later on.

and, of course, cormen is here at dartmouth. one should probably always have a copy handy when writing code.… (mais)

The definitive graduate or upper-level undergraduate computer science textbook. This is the place to go to learn basic algorithms, data structures, proofs of correctness, and big-O notation. I prefer it to Knuth's three-volume opus, because it's shorter and doesn't get bogged down in the details of an artificial assembly language.

Cormen et al. also makes for a fine self-study guide. If you're reading it on your own, check out the MIT Open Course Introduction to Algorithms class, which has a full set of online lectures and problem sets based on this book.… (mais)