TY  - BOOK
AU  - Levitin,Anany
TI  - Introduction to the design & analysis of algorithms
SN  - 9780273764113
AV  - QA76.9.A43 L48 2012
U1  - 005.1 23
PY  - 2012///
CY  - Boston
PB  - Pearson
KW  - Computer algorithms
N1  - computer bookfair2016; Includes bibliographical references and index; 1Introduction 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
UR  - http://repository.fue.edu.eg/xmlui/handle/123456789/3675
ER  -