A Practical Introduction to Data Structures and Algorithm Analysis

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INDEX 607199, 200, 203, 247, 249, 273,275, 276, 442implemented by stack, 128–132,256replaced by iteration, 51, 130reduction, 268, 560–566, 586, 588, 589,591relation, 27–29, 50replacement selection, 182, 304–307,309, 314, 316, 481resource constraints, 5, 6, 17, 57, 58run (in sorting), 301run file, 301, 302running-time equation, 60satisfiability, 572–576, 578, 579search, 23, 86, 317–357binary, 31, 77–79, 93–95, 272, 320,352, 359, 360, 374, 493, 502defined, 317exact-match query, 7–8, 10, 317,318, 357in a dictionary, 320interpolation, 320–323, 352jump, 319–320methods, 317multi-dimensional, 459range query, 8, 10, 317, 330, 357,364sequential, 22, 59–60, 63–64, 69,77–79, 94, 95, 318–319, 328,352, 497sets, 329–330successful, 317unsuccessful, 317, 346search trees, 64, 180, 358, 363, 365,372, 452, 456, 459secondary index, 358secondary key, 358secondary storage, 279–288, 311–313sector, 283, 286, 288, 299seek, 285, 286Selection Sort, 241–243, 256, 266, 272self-organizing lists, see list,self-organizingsequence, 27, 30, 51, 100, 318, 329,359, 560, 561sequential search, see search, sequentialsequential tree implementations,223–226, 228, 229serialization, 223set, 25–29, 51, 330powerset, 26, 29search, 318, 329–330subset, superset, 26terminology, 25–26union, intersection, difference, 26,329, 353Shellsort, 239, 244–246, 266, 274shortest paths, 389, 407–411, 420simulation, 89skip list, xvSkip List, 539–545, 556, 557slide rule, 32, 551software engineering, xiii, 4, 20, 560sorting, 18, 22–24, 59, 64, 65, 79–80,83, 86, 235–277, 319, 328,560–563adaptive, 271comparing algorithms, 237,265–267, 309, 310exchange sorting, 243external, 171, 236, 257, 279,298–311, 314–316lower bound, 236, 267–271small data sets, 237, 255, 271, 275stable algorithms, 236, 272, 273
608 INDEXterminology, 236–237spatial data structure, 447, 459–473splay tree, 180, 199, 365, 447, 453,455–459, 473–476, 482, 539stable sorting alorithms, see sorting,stable algorithmsstack, 99, 107, 124–132, 149, 200, 203,256, 272, 273, 276, 401, 403,404, 498array-based, 124–125constructor, 124implementations compared, 128insert, 124linked, 127, 128pop, 124, 125, 127, 151push, 124, 125, 127, 151remove, 124terminology, 124top, 124–125, 127two in one array, 128, 149variable-size elements, 151Strassen’s algorithm, 548, 557strategy, see design pattern, strategysubclass, see object-orientedprogramming, class hierarchysubset, see set, subsetsuffix tree, 475summation, 33–34, 42–44, 53, 54, 75,76, 94, 180, 187, 254, 324,325, 427, 481–487, 492–495,497, 498, 500guess and test, 500list of solutions, 33, 34notation, 33shifting method, 483–487, 495,501swap, 30table, 318tape drive, 282, 283, 298text compression, 153, 188–198, 282,328–329, 351, 355Θ notation, 71–73, 93topological sort, 389, 404–407, 419total order, 29, 51, 181Towers of Hanoi, 37–39, 130, 559, 566tradeoff, xiv, 3, 13, 79, 286, 298disk-based space/time principle,86, 282, 349space/time principle, 84–86, 101,123, 188, 282, 349transportation network, 389, 407transpose, 327, 328, 353traveling salesman, 568–570, 578, 579,589, 592traversalbinary tree, 130, 153, 158–162,167, 172, 180, 199, 398enumeration, 158, 172, 223general tree, 207–208, 227graph, 389, 398–407treeheight balanced, 371, 372, 374, 539terminology, 153trie, 163, 265, 447–452, 473, 475alphabet, 449binary, 448PATRICIA, 451–452, 473tuple, 27Turing machine, 573two-coloring, 452-3 tree, 180, 358, 366–371, 374, 377,384, 385, 452, 502, 539type, 8uncountability, 582–584UNION/FIND, xv, 209, 417, 422, 482,505
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xviPrefacemake the examples as clea
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xviiiPrefaceOne of the most importa
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xxPrefaceOthers at Prentice Hall wh
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1Data Structures and AlgorithmsHow
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Sec. 1.1 A Philosophy of Data Struc
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Sec. 1.1 A Philosophy of Data Struc
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Sec. 1.2 Abstract Data Types and Da
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Sec. 1.2 Abstract Data Types and Da
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Sec. 1.3 Design Patterns 13Data Typ
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Sec. 1.3 Design Patterns 151.3.3 Co
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Sec. 1.4 Problems, Algorithms, and
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Sec. 1.5 Further Reading 194. It mu
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Sec. 1.6 Exercises 21If you want to
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Sec. 1.6 Exercises 231.12 Imagine t
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2Mathematical PreliminariesThis cha
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Sec. 2.1 Sets and Relations 27examp
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Sec. 2.2 Miscellaneous Notation 29x
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Sec. 2.3 Logarithms 31positive inte
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Sec. 2.4 Summations and Recurrences
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Sec. 2.4 Summations and Recurrences
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Sec. 2.5 Recursion 37factorial of n
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Sec. 2.6 Mathematical Proof Techniq
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Sec. 2.7 Estimating 47Example 2.17
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Sec. 2.8 Further Reading 49typical
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Sec. 2.9 Exercises 51(f) {〈2, 1
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Sec. 2.9 Exercises 532.17 Prove by
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Sec. 2.9 Exercises 552.38 When buyi
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3Algorithm AnalysisHow long will it
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Sec. 3.1 Introduction 59compiled wi
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Sec. 3.1 Introduction 61Example 3.3
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Sec. 3.2 Best, Worst, and Average C
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Sec. 3.3 A Faster Computer, or a Fa
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Sec. 3.4 Asymptotic Analysis 67comp
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Sec. 3.4 Asymptotic Analysis 69fast
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Sec. 3.4 Asymptotic Analysis 71Exam
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Sec. 3.4 Asymptotic Analysis 73Rule
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Sec. 3.5 Calculating the Running Ti
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Sec. 3.5 Calculating the Running Ti
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Sec. 3.6 Analyzing Problems 79binar
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Sec. 3.7 Common Misunderstandings 8
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Sec. 3.9 Space Bounds 83pixel. Assu
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Sec. 3.9 Space Bounds 85A classic e
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Sec. 3.10 Speeding Up Your Programs
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Sec. 3.11 Empirical Analysis 893.11
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Sec. 3.13 Exercises 913.3 Arrange t
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Sec. 3.13 Exercises 93(f) sum = 0;f
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Sec. 3.14 Projects 95a summation fo
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4Lists, Stacks, and QueuesIf your p
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Sec. 4.1 Lists 101The next step is
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Sec. 4.1 Lists 103mentations, asser
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Sec. 4.1 Lists 105/** Array-based l
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Sec. 4.1 Lists 107Insert 23:1312 20
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Sec. 4.1 Lists 109currtailheadFigur
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Sec. 4.1 Lists 111// Linked list im
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Sec. 4.1 Lists 113curr... 23 12 ...
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Sec. 4.1 Lists 115// Singly linked
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Sec. 4.1 Lists 117determined size.
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Sec. 4.1 Lists 119pointer to each e
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Sec. 4.1 Lists 121// Insert "it" at
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Sec. 4.1 Lists 123curr... 20curr23
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Sec. 4.2 Stacks 125/** Stack ADT */
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Sec. 4.2 Stacks 127// Linked stack
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Sec. 4.2 Stacks 129Currptr β 1Curr
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Sec. 4.2 Stacks 131Example 4.3 The
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Sec. 4.3 Queues 133/** Queue ADT */
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Sec. 4.3 Queues 135frontfront20 512
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Sec. 4.3 Queues 137// Array-based q
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Sec. 4.4 Dictionaries 139enqueue pl
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Sec. 4.4 Dictionaries 141Method cle
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Sec. 4.4 Dictionaries 143// Contain
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Sec. 4.4 Dictionaries 145/** Dictio
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Sec. 4.5 Further Reading 1474.5 Fur
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Sec. 4.6 Exercises 149(a) The data
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Sec. 4.7 Projects 1514.3 Use singly
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5Binary TreesThe list representatio
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Sec. 5.1 Definitions and Properties
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Sec. 5.1 Definitions and Properties
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Sec. 5.2 Binary Tree Traversals 159
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Sec. 5.2 Binary Tree Traversals 161
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Sec. 5.3 Binary Tree Node Implement
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Sec. 5.4 Binary Search Trees 171Thi
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Sec. 5.4 Binary Search Trees 173120
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Sec. 5.4 Binary Search Trees 175/**
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Sec. 5.4 Binary Search Trees 177min
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Sec. 5.4 Binary Search Trees 17937
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Sec. 5.5 Heaps and Priority Queues
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Sec. 5.6 Huffman Coding Trees 189Le
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Sec. 5.6 Huffman Coding Trees 191St
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Sec. 5.6 Huffman Coding Trees 193/*
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Sec. 5.6 Huffman Coding Trees 195//
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Sec. 5.6 Huffman Coding Trees 197A
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Sec. 5.8 Exercises 199Many techniqu
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Sec. 5.8 Exercises 2015.19 Write a
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Sec. 5.9 Projects 203(d) The record
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6Non-Binary TreesMany organizations
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Sec. 6.1 General Tree Definitions a
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Sec. 6.2 The Parent Pointer Impleme
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Sec. 6.3 General Tree Implementatio
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Sec. 6.3 General Tree Implementatio
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Sec. 6.4 K-ary Trees 221RRABABCDEFC
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Sec. 6.5 Sequential Tree Implementa
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Sec. 6.5 Sequential Tree Implementa
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Sec. 6.7 Exercises 2276.2 Write an
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Sec. 6.7 Exercises 229CAFBEHGDIFigu
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Sec. 6.8 Projects 231proved perform
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7Internal SortingWe sort many thing
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Sec. 7.2 Three Θ(n 2 ) Sorting Alg
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Sec. 7.3 Shellsort 24559 20 17 13 2
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Sec. 7.4 Mergesort 24736 20 17 13 2
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Sec. 7.5 Quicksort 249static
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Sec. 7.5 Quicksort 251static
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Sec. 7.5 Quicksort 253InitialPass 1
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Sec. 7.5 Quicksort 255The initial c
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Sec. 7.6 Heapsort 257and fast. The
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Sec. 7.7 Binsort and Radix Sort 259
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Sec. 7.8 An Empirical Comparison of
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Sec. 7.9 Lower Bounds for Sorting 2
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Sec. 7.9 Lower Bounds for Sorting 2
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Sec. 7.10 Further Reading 271• A
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Sec. 7.11 Exercises 2737.7 Recall t
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Sec. 7.12 Projects 2757.16 (a) Devi
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Sec. 7.12 Projects 277classmates? W
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280 Chap. 8 File Processing and Ext
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318 Chap. 9 SearchingThis and the f
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320 Chap. 9 Searchingelement in L,
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322 Chap. 9 SearchingThis is equal
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324 Chap. 9 Searching9.2 Self-Organ
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326 Chap. 9 SearchingWhen a frequen
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328 Chap. 9 Searchingand the total
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330 Chap. 9 SearchingThe set differ
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332 Chap. 9 Searchingprobability th
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334 Chap. 9 SearchingExample 9.6 A
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336 Chap. 9 Searchingand the next f
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338 Chap. 9 Searching01HashTable100
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340 Chap. 9 Searching/** Insert rec
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342 Chap. 9 Searching09050090501100
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344 Chap. 9 SearchingExample 9.9 Co
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346 Chap. 9 Searchingproject at the
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348 Chap. 9 SearchingIf N and M are
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350 Chap. 9 SearchingDepending on t
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352 Chap. 9 SearchingBentley et al.
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354 Chap. 9 Searching(c) How many s
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356 Chap. 9 Searching9.5 Implement
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358 Chap. 10 Indexingfile is create
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360 Chap. 10 Indexing1 2003 5894 10
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362 Chap. 10 IndexingSecondaryKeyJo
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364 Chap. 10 Indexingkey value for
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366 Chap. 10 IndexingFigure 10.7 Br
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368 Chap. 10 Indexing/** 2-3 tree n
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370 Chap. 10 Indexing18331223 30 48
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372 Chap. 10 Indexingprivate TTNode
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374 Chap. 10 Indexing24152033 45 48
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376 Chap. 10 Indexingvalues, but th
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378 Chap. 10 Indexing331012 233348
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380 Chap. 10 Indexing4845 4748 50 5
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382 Chap. 10 IndexingAs mentioned e
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384 Chap. 10 Indexing(b) Show the i
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PART IVAdvanced Data Structures387
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390 Chap. 11 Graphs04123147123(a)(b
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392 Chap. 11 Graphs0 1 2 3 40201 11
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394 Chap. 11 GraphsThe adjacency ma
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396 Chap. 11 Graphsedge list. Funct
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398 Chap. 11 Graphspublic int weigh
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400 Chap. 11 Graphs}// Store edge w
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402 Chap. 11 GraphsABABCCDDFFEE(a)(
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404 Chap. 11 Graphs// Breadth first
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406 Chap. 11 GraphsAInitial call to
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408 Chap. 11 Graphsstatic void tops
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410 Chap. 11 Graphs// Compute short
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412 Chap. 11 Graphs// Dijkstra’s
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414 Chap. 11 Graphs// Compute a min
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416 Chap. 11 GraphsMarkedVertices v
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418 Chap. 11 GraphsInitialA B C D E
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420 Chap. 11 Graphs2 511032041032 6
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422 Chap. 11 Graphstriangular matri
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424 Chap. 12 Lists and Arrays Revis
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448 Chap. 13 Advanced Tree Structur
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PART VTheory of Algorithms479
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482 Chap. 14 Analysis Techniquesthi
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484 Chap. 14 Analysis TechniquesExa
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486 Chap. 14 Analysis Techniquesthe
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488 Chap. 14 Analysis Techniquesof
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490 Chap. 14 Analysis TechniquesHow
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492 Chap. 14 Analysis Techniques= 2
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494 Chap. 14 Analysis TechniquesNot
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496 Chap. 14 Analysis Techniquesfro
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498 Chap. 14 Analysis Techniquesbit
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500 Chap. 14 Analysis Techniquesfro
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502 Chap. 14 Analysis Techniques14.
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504 Chap. 14 Analysis Techniques}G.
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15Lower BoundsHow do I know if I ha
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Sec. 15.1 Introduction to Lower Bou
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Sec. 15.2 Lower Bounds on Searching
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Sec. 15.3 Finding the Maximum Value
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Sec. 15.4 Adversarial Lower Bounds
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Sec. 15.4 Adversarial Lower Bounds
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Sec. 15.5 State Space Lower Bounds
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Sec. 15.5 State Space Lower Bounds
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Sec. 15.6 Finding the ith Best Elem
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Sec. 15.7 Optimal Sorting 525search
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Sec. 15.8 Further Reading 527Merge
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Sec. 15.9 Exercises 52915.10 Show t
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16Patterns of AlgorithmsThis chapte
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Sec. 16.1 Dynamic Programming 533dy
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Sec. 16.1 Dynamic Programming 535ar
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Sec. 16.2 Randomized Algorithms 537
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Sec. 16.3 Numerical Algorithms 545e
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Sec. 16.3 Numerical Algorithms 547d
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Sec. 16.3 Numerical Algorithms 549W
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Sec. 16.3 Numerical Algorithms 5511
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Sec. 16.3 Numerical Algorithms 553i
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Sec. 16.3 Numerical Algorithms 555b
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Page 613 and 614: 594 BIBLIOGRAPHY[BG00] Sara Baase a
Page 615 and 616: 596 BIBLIOGRAPHY[LLKS85] E.L. Lawle
Page 617 and 618: 598 BIBLIOGRAPHY[WMB99][Zei07]I.H.
Page 619 and 620: 600 INDEXbest fit, see memory manag
Page 621 and 622: 602 INDEXrelation, 27, 50estimating
Page 623 and 624: 604 INDEXinteger representation, 5,
Page 625: 606 INDEXpath compression, 215-216,
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A Practical Introduction to Data Structures and Algorithm Analysis

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