000			01847cam a2200217 a 4500
008			080110s2008 enka 001 0 eng
020			_a9780521614108 (pbk)
041			_aeng
080			_a510.6 _bEDM
100	1		_aEdmonds, Jeff
245	1	0	_aHow to Think about Algorithms
260			_aNew York _bCambridge University Press _c2008
300			_axiii, 448p
505			_aIterative algorithms: measures of progress and loop invariants Examples using more-of-the-input loop invariants Abstract data types Narrowing the search space: binary search Iterative sorting algorithms Euclid's GCD algorithm The loop invariant for lower bounds Abstractions, techniques, and theory Some simple examples of recursive algorithms Recursion on trees Recursive images Parsing with context-free grammars Definition of optimization problems Graph search algorithms Network flows and linear programming Greedy algorithms Recursive backtracking Dynamic programming algorithms Examples of dynamic programs Reductions and NP-completeness Randomized algorithms Existential and universal quantifiers Time complexity Logarithms and exponentials Asymptotic growth Adding-made-easy approximations Recurrence relations A formal proof of correctness
520			_a"This book presents insights, notations, and analogies to help the novice describe and think about algorithms like an expert. Jeff Edmonds provides both the big picture and easy step-by-step methods for developing algorithms, while avoiding the common pitfalls. Paradigms such as loop invariants and recursion help to unify a huge range of algorithms into a few meta-algorithms. Part of the goal is to teach the students to think abstractly."--Jacket
650		0	_aAlgorithms
650		0	_aInvariants
650		0	_aRecursion theory
690			_aMathematics
942			_cBK
999			_c23505 _d23505