A Textbook of Data Structures and Algorithms, Volume 3
Mastering Advanced Data Structures and Algorithm Design Strategies
1. Edition January 2023
368 Pages, Hardcover
Wiley & Sons Ltd
Further versions
Data structures and algorithms is a fundamental course in Computer Science, which enables learners across any discipline to develop the much-needed foundation of efficient programming, leading to better problem solving in their respective disciplines.
A Textbook of Data Structures and Algorithms is a textbook that can be used as course material in classrooms, or as self-learning material. The book targets novice learners aspiring to acquire advanced knowledge of the topic. Therefore, the content of the book has been pragmatically structured across three volumes and kept comprehensive enough to help them in their progression from novice to expert.
With this in mind, the book details concepts, techniques and applications pertaining to data structures and algorithms, independent of any programming language. It includes 181 illustrative problems and 276 review questions to reinforce a theoretical understanding and presents a suggestive list of 108 programming assignments to aid in the implementation of the methods covered.
Acknowledgments xvii
Chapter 13. Hash Tables 1
13.1. Introduction 1
13.2. Hash table structure 2
13.3. Hash functions 4
13.4. Linear open addressing 5
13.5. Chaining 13
13.6. Applications 18
13.7. Illustrative problems 23
Chapter 14. File Organizations 33
14.1. Introduction 33
14.2. Files 34
14.3. Keys 36
14.4. Basic file operations 38
14.5. Heap or pile organization 38
14.6. Sequential file organization 39
14.7. Indexed sequential file organization 41
14.8. Direct file organization 48
14.9. Illustrative problems 50
Chapter 15. k-d Trees and Treaps 61
15.1. Introduction 61
15.2. k-d trees: structure and operations 61
15.3. Treaps: structure and operations 76
15.4. Illustrative problems 83
Chapter 16. Searching 93
16.1. Introduction 93
16.2. Linear search 94
16.3. Transpose sequential search 96
16.4. Interpolation search 98
16.5. Binary search 100
16.6. Fibonacci search 104
16.7. Skip list search 108
16.8. Other search techniques 116
16.9. Illustrative problems 118
Chapter 17. Internal Sorting 131
17.1. Introduction 131
17.2. Bubble sort 132
17.3. Insertion sort 135
17.4. Selection sort 138
17.5. Merge sort 140
17.6. Shell sort 147
17.7. Quick sort 153
17.8. Heap sort 159
17.9. Radix sort 167
17.10. Counting sort 171
17.11. Bucket sort 175
17.12. Illustrative problems 179
Chapter 18. External Sorting 197
18.1. Introduction 197
18.2. External storage devices 198
18.3. Sorting with tapes: balanced merge 202
18.4. Sorting with disks: balanced merge 206
18.5. Polyphase merge sort 212
18.6. Cascade merge sort 214
18.7. Illustrative problems 216
Chapter 19. Divide and Conquer 229
19.1. Introduction 229
19.2. Principle and abstraction 229
19.3. Finding maximum and minimum 231
19.4. Merge sort 233
19.5. Matrix multiplication 234
19.6. Illustrative problems 239
Chapter 20. Greedy Method 245
20.1. Introduction 245
20.2. Abstraction 245
20.3. Knapsack problem 246
20.4. Minimum cost spanning tree algorithms 249
20.5. Dijkstra's algorithm 251
20.6. Illustrative problems 251
Chapter 21. Dynamic Programming 261
21.1. Introduction 261
21.2. 0/1 knapsack problem 263
21.3. Traveling salesperson problem 266
21.4. All-pairs shortest path problem 269
21.5. Optimal binary search trees 272
21.6. Illustrative problems 280
Chapter 22. P and NP Class of Problems 287
22.1. Introduction 287
22.2. Deterministic and nondeterministic algorithms 289
22.3. Satisfiability problem 292
22.4. NP-complete and NP-hard problems 297
22.5. Examples of NP-hard and NP-complete problems 300
22.6. Cook's theorem 302
22.7. The unsolved problem P (?/=) NP problem 303
22.8. Illustrative problems 304
References 311
Index 313
Summaries of other volumes 317
