The book builds a way of thinking towards solving algorithms problems, instead of just stating the algorithms and data structures in a mechanical way, but in many parts it is not very clear and you have to read a passage multiple times to understand what the author meant. The main part (maybe skipping/skimming down a few chapters) is a very good preparation for algorithm-heavy job interviews (e. But regardless, the reason for the 3 stars is that this book tries to straddle the middle of being a practical interview prep book and being a proof heavy, theoretical Algo book. The first part, Techniques , provides accessible instruction on methods for designing and analyzing computer algorithms. A unique and illuminating feature of this book is an extensive collection of "war stories" describing the author's personal experiences with applying these algorithmic tools in various circumstances (quite fascinating, and some a bit darkly humorous).

This book is ideal for the working professional who uses algorithms on a daily basis and has need for a handy reference.

I've found that a lot of computer programming is easy if you just know the name of thing you need to Google.

It trains the methodology, logical plan how (and possibly why) one takes off from an earlier algorithm and goes on developing something new. It has all the right ingredients: rich contents, friendly, personal language, subtle humor, the right references, and a plethora of pointers to resources.The extensive collections of problems at the end of each tutorial chapter provide excellent practice; in particular, the lists of "interview problems" for drilling are very valuable preparation. My absolute favorite for this kind of interview preparation is Steven Skiena’s The Algorithm Design Manual. In reality, even though it starts from the basics of math and programming, the topics covered are broad enough and discussed in much depth to make it appealing even to the senior programmer.

One of Skiena's "war stories" tells of making a program run 30,000 times faster by using a better-designed algorithm. ACM Computing Reviews "It has all the right ingredients: rich contents, friendly, personal language, subtle humor, the right references, and a plethora of pointers to resources. With its aid, most programmers could go from writing code that merely works to writing code that is thousands of times more efficient and reliable: this book will earn some people fortunes. In comparison to "Introduction to Algorithms" (the other algorithm book I had significant exposure to) this one is faster to read, easier to digest and more tailored towards applications.You can change your choices at any time by visiting Cookie preferences, as described in the Cookie notice. The second part, Resources, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations and an extensive bibliography. the book is an algorithm implementation treasure trove, and putting all of these implementations in one place was no small feat. The second half of the book is collection of short essays on various kinds of problems and sketches of techniques to handle them.

I used the "introductory" adjective earlier as this is supposed to be an introductory book on the topic.

Megan Squire, Elon University, USA This newly expanded and updated second edition of the best-selling classic continues to take the "mystery" out of designing algorithms, and analyzing their efficacy and efficiency. I also skipped all the problems in chapter 10, which dealt with NP hard problems and approximate algos and more proofy ones about reducing problems down to satisfiability. Data Structures: Repeatedly extracts the smallest remaining element from the unsorted part of the set but will take a total of O(n