000			02996cam a22003854i 4500
999			_c10572 _d10572
001			16889879
005			20201006145636.0
008			110726s2012 maua b 001 0 eng
010			_a 2011027089
020			_a9780273764113
020			_a027376411X
035			_a(OCoLC)ocn743298766
040			_aDLC _cDLC _dYDX _dYDXCP _dBWX _dDLC _dEG-NcFUE _erda
042			_apcc
050	0	0	_aQA76.9.A43 _bL48 2012
082	0	0	_a005.1 _223 _bL.A.I
100	1		_aLevitin, Anany.
245	1	0	_aIntroduction to the design & analysis of algorithms / _cAnany Levitin.
246	3		_aIntroduction to the design and analysis of algorithms
250			_a3rd ed.
260			_aBoston : _bPearson, _cc2012.
300			_a589 p. : _bill. ; _c23 cm.
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
338			_2rdacarrier _avolume
500			_acomputer bookfair2016
504			_aIncludes bibliographical references and index.
505	0		_a1Introduction 1 1.1 What Is an Algorithm? 3 Exercises 1.1 7 1.2 Fundamentals of Algorithmic Problem Solving 9 Understanding the Problem 9 Ascertaining the Capabilities of the Computational Device 9 Choosing between Exact and Approximate Problem Solving 11 Algorithm Design Techniques 11 Designing an Algorithm and Data Structures 12 Methods of Specifying an Algorithm 12 Proving an Algorithm’s Correctness 13 Analyzing an Algorithm 14 Coding an Algorithm 15 Exercises 1.2 17 1.3 Important Problem Types 18 Sorting 19 Searching 20 String Processing 20 Graph Problems 21 Combinatorial Problems 21 Geometric Problems 22 Numerical Problems 22 Exercises 1.3 23 1.4 Fundamental Data Structures 25 Linear Data Structures 25 Graphs 28 Trees 31 Sets and Dictionaries 35 Exercises 1.4 37 Summary 38 2 Fundamentals of the Analysis of AlgorithmEfficiency 41 2.1 The Analysis Framework 42 Measuring an Input’s Size 43 Units for Measuring Running Time 44 Orders of Growth 45 Worst-Case, Best-Case, and Average-Case Efficiencies 47 Recapitulation of the Analysis Framework 50 Exercises 2.1 50 2.2 Asymptotic Notations and Basic Efficiency Classes 52 Informal Introduction 52 O-notation 53 -notation 54 -notation 55 Useful Property Involving the Asymptotic Notations 55 Using Limits for Comparing Orders of Growth 56 Basic Efficiency Classes 58 Exercises 2.2 58 2.3 Mathematical Analysis of Nonrecursive Algorithms 61 Exercises 2.3 67 2.4 Mathematical Analysis of Recursive Algorithms 70 Exercises 2.4 76 2.5 Example: Computing the nth Fibonacci Number 80 Exercises 2.5 83 2.6 Empirical Analysis of Algorithms 84 Exercises 2.6 89 2.7 Algorithm Visualization 91 Summary 94
650		0	_aComputer algorithms.
856			_3Abstract _uhttp://repository.fue.edu.eg/xmlui/handle/123456789/3675
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _cBK