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 s<strong>to</strong>rage, 279–288, 311–313sec<strong>to</strong>r, 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, 124–125construc<strong>to</strong>r, 124implementations compared, 128insert, 124linked, 127, 128pop, 124, 125, 127, 151push, 124, 125, 127, 151remove, 124terminology, 124<strong>to</strong>p, 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 <strong>and</strong> 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, 93<strong>to</strong>pological sort, 389, 404–407, 419<strong>to</strong>tal 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. 2.8 Further Reading 49typical
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3Algorithm AnalysisHow long will it
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Sec. 3.1 Introduction 61Example 3.3
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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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330 Chap. 9 SearchingThe set differ
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336 Chap. 9 Searchingand the next f
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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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360 Chap. 10 Indexing1 2003 5894 10
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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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402 Chap. 11 GraphsABABCCDDFFEE(a)(
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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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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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426 Chap. 12 Lists and Arrays Revis
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428 Chap. 12 Lists and Arrays Revis
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430 Chap. 12 Lists and Arrays Revis
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432 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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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. 15.6 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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- Page 613 and 614: 594 BIBLIOGRAPHY[BG00] Sara Baase a
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