000			03109nam a22003738i 4500
001			CR9780511808241
003			UkCbUP
005			20200124160300.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			101021s2008||||enk o ||1 0|eng|d
020			_a9780511808241 (ebook)
020			_z9780521849319 (hardback)
020			_z9780521614108 (paperback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aQA9.58 _b.E36 2008
082	0	0	_a518/.1 _222
100	1		_aEdmonds, Jeff, _d1963- _eauthor.
245	1	0	_aHow to think about algorithms / _cJeff Edmonds.
264		1	_aCambridge : _bCambridge University Press, _c2008.
300			_a1 online resource (xiii, 448 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
500			_aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
505	0		_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			_aThis textbook, for second- or third-year students of computer science, presents insights, notations, and analogies to help them describe and think about algorithms like an expert, without grinding through lots of formal proof. Solutions to many problems are provided to let students check their progress, while class-tested PowerPoint slides are on the web for anyone running the course. By looking at both the big picture and easy step-by-step methods for developing algorithms, the author guides students around the common pitfalls. He stresses paradigms such as loop invariants and recursion to unify a huge range of algorithms into a few meta-algorithms. The book fosters a deeper understanding of how and why each algorithm works. These insights are presented in a careful and clear way, helping students to think abstractly and preparing them for creating their own innovative ways to solve problems.
650		0	_aAlgorithms _xStudy and teaching.
650		0	_aLoops (Group theory) _xStudy and teaching.
650		0	_aInvariants _xStudy and teaching.
650		0	_aRecursion theory _xStudy and teaching.
776	0	8	_iPrint version: _z9780521849319
856	4	0	_uhttps://doi.org/10.1017/CBO9780511808241
999			_c520323 _d520321