Design and Analysis of AlgorithmsThis book is designed for the way we learn and intended for one-semester course in Design and Analysis of Algorithms . This is a very useful guide for graduate and undergraduate students and teachers of computer science. This book provides a coherent and pedagogically sound framework for learning and teaching. Its breadth of coverage insures that algorithms are carefully and comprehensively discussed with figures and tracing of algorithms. Carefully developing topics with sufficient detail, this text enables students to learn about concepts on their own, offering instructors flexibility and allowing them to use the text as lecture reinforcement.Key Features:" Focuses on simple explanations of techniques that can be applied to real-world problems." Presents algorithms with self-explanatory pseudocode." Covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers." Includes chapter summary, self-test quiz and exercises at the end of each chapter. Key to quizzes and solutions to exercises are given in appendices. |
Contents
CHAPTER1pdf | 1 |
CHAPTER2pdf | 41 |
CHAPTER3pdf | 67 |
CHAPTER4pdf | 85 |
CHAPTER5pdf | 115 |
CHAPTER6pdf | 149 |
CHAPTER7pdf | 167 |
CHAPTER8pdf | 179 |
AppApdf | 191 |
AppBpdf | 197 |
REFERENCESpdf | 255 |
257 | |
Common terms and phrases
0/1 knapsack 0/1 knapsack problem adjacency list amortized analysis array articulation point assignment asymptotic backtracking biconnected binary search tree branch-and-bound cg(n color connected components contains cost data structure decision problem depth-first search disjoint sets divide and conquer dynamic programming element Endfor Endif Endwhile example feasible solution fractional knapsack problem function given graph G greedy method Hamilton cycle Hamiltonian cycle Huffman code Huffman tree input integer iteration knapsack problem Kruskal's algorithm live nodes loop lower bound matrix multiplication maximum merge mergesort minimum spanning tree NP-complete NP-hard O(n log O(n² optimal solution optimal substructure path compression performed polynomial-time Prim's algorithm primitive operations problem in NP pseudocode queue quicksort recurrence relation root running selected sequence shortest path solved in polynomial sort space tree step subarray subproblems subset subtree technique total number undirected graph upper bound variable vertex vertices worst-case