Data Structures and Algorithm Analysis in C - Mark Allen Weiss
Structures, Algorithm Analysis: Table of Contents
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Data Structures and Algorithm Analysis in C by Mark Allen Weiss
PREFACE CHAPTER 1: INTRODUCTION CHAPTER 2: ALGORITHM ANALYSIS CHAPTER 3: LISTS, STACKS, AND QUEUES CHAPTER 4: TREES CHAPTER 5: HASHING CHAPTER 6: PRIORITY QUEUES (HEAPS) CHAPTER 7: SORTING CHAPTER 8: THE DISJOINT SET ADT CHAPTER 9: GRAPH ALGORITHMS CHAPTER 10: ALGORITHM DESIGN TECHNIQUES CHAPTER 11: AMORTIZED ANALYSIS
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2006-1-27
Structures, Algorithm Analysis: PREFACE
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PREFACE Purpose/Goals
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This book describes data structures, methods of organizing large amounts of data, and algorithm analysis, the estimation of the running time of algorithms. As computers become faster and faster, the need for programs that can handle large amounts of input becomes more acute. Paradoxically, this requires more careful attention to efficiency, since inefficiencies in programs become most obvious when input sizes are large. By analyzing an algorithm before it is actually coded, students can decide if a particular solution will be feasible. For example, in this text students look at specific problems and see how careful implementations can reduce the time constraint for large amounts of data from 16 years to less than a second. Therefore, no algorithm or data structure is presented without an explanation of its running time. In some cases, minute details that affect the running time of the implementation are explored. Once a solution method is determined, a program must still be written. As computers have become more powerful, the problems they solve have become larger and more complex, thus requiring development of more intricate programs to solve the problems. The goal of this text is to teach students good programming and algorithm analysis skills simultaneously so that they can develop such programs with the
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Data Structures and Algorithm Analysis in C by Mark Allen Weiss
PREFACE CHAPTER 1: INTRODUCTION CHAPTER 2: ALGORITHM ANALYSIS CHAPTER 3: LISTS, STACKS, AND QUEUES CHAPTER 4: TREES CHAPTER 5: HASHING CHAPTER 6: PRIORITY QUEUES (HEAPS) CHAPTER 7: SORTING CHAPTER 8: THE DISJOINT SET ADT CHAPTER 9: GRAPH ALGORITHMS CHAPTER 10: ALGORITHM DESIGN TECHNIQUES CHAPTER 11: AMORTIZED ANALYSIS
mk:@MSITStore:K:\Data.Structures.and.Algorithm.Analysis.in.C.chm::/...
2006-1-27
Structures, Algorithm Analysis: PREFACE
页码，1/4
PREFACE Purpose/Goals
Return to Table of Contents
Next Chapter
This book describes data structures, methods of organizing large amounts of data, and algorithm analysis, the estimation of the running time of algorithms. As computers become faster and faster, the need for programs that can handle large amounts of input becomes more acute. Paradoxically, this requires more careful attention to efficiency, since inefficiencies in programs become most obvious when input sizes are large. By analyzing an algorithm before it is actually coded, students can decide if a particular solution will be feasible. For example, in this text students look at specific problems and see how careful implementations can reduce the time constraint for large amounts of data from 16 years to less than a second. Therefore, no algorithm or data structure is presented without an explanation of its running time. In some cases, minute details that affect the running time of the implementation are explored. Once a solution method is determined, a program must still be written. As computers have become more powerful, the problems they solve have become larger and more complex, thus requiring development of more intricate programs to solve the problems. The goal of this text is to teach students good programming and algorithm analysis skills simultaneously so that they can develop such programs with the
References: 2. M. R. Brown and R. E. Tarjan, "Design and Analysis of a Data Structure for Representing Sorted Lists," SIAM Journal on Computing 9 (1980), 594-614. 3. M. L. Fredman and R. E. Tarjan, "Fibonacci Heaps and Their Uses in Improved Network Optimization Algorithms," Journal of the ACM 34 (1987), 596-615. 4. H. Gajewska and R. E. Tarjan, "Deques with Heap Order," Information Processing Letters 22 (1986), 197-200. 5. G. Port and A. Moffat, "A Fast Algorithm for Melding Splay Trees," Proceedings of the First Workshop on Algorithms and Data Structures, 1989, 450-459. 6. D. D. Sleator and R. E. Tarjan, "Self-adjusting Binary Search Trees," Journal of the ACM 32 (1985), 652-686. 7. D. D. Sleator and R. E. Tarjan, "Amortized Efficiency of List Update and Paging Rules," Communications of the ACM 28 (1985), 202-208. 8. D. D. Sleator and R. E. Tarjan, "Self-adjusting Heaps," SIAM Journal on Computing 15 (1986), 52-69. Methods 6 (1985), 306-318. 10. J. Vuillemin, "A Data Structure for Manipulating Priority Queues," Communications of the ACM 21 (1978), 309-314. Return to Table of Contents mk:@MSITStore:K:Data.Structures.and.Algorithm.Analysis.in.C.chm::/...