The Algorithm Design ManualMost professional programmers that I’ve encountered are not well prepared to tacklealgorithmdesignproblems.Thisisapity,becausethetechniquesofalgorithm design form one of the core practical technologies of computer science. Designing correct, e?cient, and implementable algorithms for realworld problems requires access to two distinct bodies of knowledge: • Techniques – Good algorithm designers understand several fundamental  gorithm design techniques, including data structures, dynamic programming, depth?rst search, backtracking, and heuristics. Perhaps the single most  portantdesigntechniqueismodeling,theartofabstractingamessyrealworld application into a clean problem suitable for algorithmic attack. • Resources – Good algorithm designers stand on the shoulders of giants. Ratherthanlaboringfromscratchtoproduceanewalgorithmforeverytask, they can ?gure out what is known about a particular problem. Rather than reimplementing popular algorithms from scratch, they seek existing imp mentations to serve as a starting point. They are familiar with many classic algorithmic problems, which provide su?cient source material to model most any application. This book is intended as a manual on algorithm design, providing access to combinatorial algorithm technology for both students and computer professionals. 
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Review: The Algorithm Design Manual
User Review  GoodreadsThis is an excellent book and must for anybody interested in computer science algorithms. For preparation of interviews also it offers very interesting coverage of algorithms problems. The best part is that it gives the code in actual C implementation which makes the understanding more concrete. Read full review
Review: The Algorithm Design Manual
User Review  Muhammad  GoodreadsThis is not an introductory book. You should have some previous knowledge of algorithms to enjoy it. The book builds a way of thinking towards solving algorithms problems, instead of just stating the ... Read full review
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adjacency lists algorithm design applications array backtracking breadthfirst search characters clique coloring combinatorial compute connected components constraints construct contains convex hull cost cycle data structure defined deletion depthfirst search directed graph discussed in Section dynamic programming edge efficient algorithm elements exactly example Figure function geometric given graph G Hamiltonian hash heuristic implementation independent set Input description INPUT OUTPUT insertion integer integer partitions intersection isomorphism kdtrees linear longest matrix maximum minimize minimum spanning tree node NPcomplete operations optimal pair partition permutations planar pointer polygon possible Prim’s priority queue Problem description Programming Challenges prove provides query quicksort random recursive reduction Related Problems represent root sequence set cover shortest path simulated annealing smallest solution solve sorting algorithm subgraph subset substring suffix tree topological sorting tour traversal triangle undirected vertex cover vertices Voronoi diagrams weight worstcase