The fact that this book focuses on working source code in examples (as opposed to just pseudo-code) makes it extremely useful for drilling for programming interviews. There were some instances (graph algorithms) where the code in Skiena was taken straight out of CLRS. What I like about this book is that, it does not talk about what a particular algorithm does and how it is implemented, but more it takes you on a flight between two algorithms.

The 103 third parties who use cookies on this service do so for their purposes of displaying and measuring personalized ads, generating audience insights, and developing and improving products. This book is ideal for the working professional who uses algorithms on a daily basis and has need for a handy reference. It is essential for scientists, engineers, and any professionals who aim to solve problems, with a noticeable emphasis on real problems. I read the first edition of this book back in University and bought a new copy for my girlfriend who's learning programming, it's as good as I remembered. It's been a great guide to actually thinking like a professional, even if most of the day job is data plumbing.For a decade, Steven Skiena’s Algorithm Design Manual retained its title as the best and most comprehensive practical algorithm guide to help identify and solve problems. The first part, Techniques, provides accessible instruction on methods for designing and analyzing computer algorithms.

I found the "Hitchhiker's Guide to Algorithms" in the back to be extremely useful if you really find yourself tackling an algorithmic problem in practice. 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. 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.For those who are new to the book, its main aim remains to provide a comprehensive catalogue of algorithms and background resources. If I were to go back in time, I'd probably pick either a 100% practical Algo book or something like CLRS for very rigorous understanding. over 30 hours of audio lectures on the design and analysis of algorithms are provided, all keyed to on-line lecture notes.

It does ramble at times with personal anecdotes, which some readers may find enjoyable, but if you want to-the-point algorithms these may be a distraction. One of Skiena's "war stories" tells of making a program run 30,000 times faster by using a better-designed algorithm. the book is an algorithm-implementation treasure trove, and putting all of these implementations in one place was no small feat. This is very useful for gaining a broad overview of what tools are available, though the coverage can be somewhat brief (e. The list of implementations, an extensive bibliography … make the book an invaluable resource for everyone interested in the subject.Every programmer should read this book, and anyone working in the field should keep it close to hand - The Algorithm Design Manual is not just for use on university courses. For a decade, Steven Skiena's Algorithm Design Manual retained its title as the best and most comprehensive practical algorithm guide to help identify and solve problems. THE ALGORITHM DESIGN MANUAL comes with a CD-ROM that contains: * a complete hypertext version of the full printed book. This book is a practical, example-driven book on computer science algorithms, which is very readable and has a wealth of ready-to-use examples. A lot of people might enjoy this, but I feel that having the mathematical understanding of algorithms and the proofs to back it up will greatly increase your understanding of the material.

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 tutorial material in the first half of the book covers the essentials: data structures such as lists, arrays, stacks, queues, binary trees, etc. 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.

It trains the methodology, logical plan how (and possibly why) one takes off from an earlier algorithm and goes on developing something new. This second edition has updated the bibliography to include recent works, making it an extensive bibliography. Overall, a good choice for a first algorithms book, after which you may want to move onto something more advanced.