The Algorithm Design Manual

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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. This is very useful for gaining a broad overview of what tools are available, though the coverage can be somewhat brief (e. 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. More than any other book it helped me understand just how astonishingly commonplace … graph problems are -- they should be part of every working programmer’s toolkit. This second edition has updated the bibliography to include recent works, making it an extensive bibliography.

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It has all the right ingredients: rich contents, friendly, personal language, subtle humor, the right references, and a plethora of pointers to resources. 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 list of implementations [and] extensive bibliography make the book an invaluable resource for everyone interested in the subject. I especially liked The Algorithm Design Manual because of the author's writing style, the "war stories" (that are some clever and practical applications of the data structures and algorithms the author tries to teach you) and the second half part of the book which is a sort of encyclopedia of problems. and so one should probably have a more rigorous book at hand to fill in some details when necessary. I would give this book 4 1/2 stars; it has a fair share of typos, and sometimes problems are duplicated in different sections; this probably reflects how the book was updated. the book is an algorithm-implementation treasure trove, and putting all of these implementations in one place was no small feat.Addressing the main difficulties of solving problems, this book goes far beyond the design of algorithms. The first part, Techniques, provides accessible instruction on methods for designing and analyzing computer algorithms. If you want to use it as a course textbook then there are lots of exercises at the end of every chapter. For someone who's never taken CS101, this book an eye-opener into the hows and whys of basic data structures like linked lists, trees, hash tables, and arrays, as well as sorting techniques and more advanced practices like dynamic programming. This book is ideal for the working professional who uses algorithms on a daily basis and has need for a handy reference.

Coverage is divided into two parts, the first being a general guide to techniques for the design and analysis of computer algorithms. the book is an algorithm implementation treasure trove, and putting all of these implementations in one place was no small feat.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. The second part, Resources, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations and an extensive bibliography. It will not only serve as a valuable undergraduate textbook, but it will also become an irreplaceable reference guide for most professionals in the area.

It trains the methodology, logical plan how (and possibly why) one takes off from an earlier algorithm and goes on developing something new. I know that this book is C++ - centric but can it give some extra points for learning rust even from an algorithmic point of view, or does it deal with things that are not suitable for rust?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. Skiena covers this varied field with a mix of humour and wisdom, and he provides an excellent array of references, online code and other resources for everything he touches on. There were some instances (graph algorithms) where the code in Skiena was taken straight out of CLRS.