INDEX 575image space, 430key space, 430object space, 429depth-first search, 371, 383–385, 400,424, 482deque, 141dequeue, see queue, dequeuedesign p<strong>at</strong>tern, xiv, 12–16, 19composite, 14–15, 158, 451flyweight, 13, 158, 192, 450–451str<strong>at</strong>egy, 15–16, 138visitor, 13–14, 152, 383, 402Deutsch-Schorr-Waite algorithm, 425,428dictionary, xiv, 163, 329, 431ADT, 131–137, 301, 339, 368, 509Dijkstra’s algorithm, 390–394, 400,401, 514Diminishing Increment Sort, seeShellsortdirected acyclic graph (DAG), 373, 384,400, 406, 424discrete m<strong>at</strong>hem<strong>at</strong>ics, xiv, 45disjoint, 145disjoint set, see equivalence classdisk drive, 9, 265, 268–297access cost, 272–274, 295cylinder, 269, 347organiz<strong>at</strong>ion, 268–271disk processing, see file processingdivide <strong>and</strong> conquer, 237, 240, 242, 304,467, 472–474document retrieval, 314, 335double buffering, 275, 287, 288dynamic array, see array, dynamicdynamic memory alloc<strong>at</strong>ion, 100dynamic programming, 509–515, 532,553efficiency, xiii, 3–5element, 23homogeneity, 94, 112implement<strong>at</strong>ion, 111–112Emacs text editor, 423, 425encapsul<strong>at</strong>ion, 9enqueue, see queue, enqueueentry-sequenced file, 341enumer<strong>at</strong>ion, see traversalequ<strong>at</strong>ion, represent<strong>at</strong>ion, 155equivalence, 25–26class, 25, 195, 200–206, 215, 216,219, 397, 398, 401, 403, 456rel<strong>at</strong>ion, 25, 46estim<strong>at</strong>ion, 23, 44–46, 50, 51, 53–55,63exact-m<strong>at</strong>ch query, see search,exact-m<strong>at</strong>ch queryexponential growth r<strong>at</strong>e, see growthr<strong>at</strong>e, exponentialexpression tree, 154–158extent, 271external sorting, see sorting, externalfactorial function, 27, 32, 34, 43, 47,71, 79, 85, 123, 254, 257, 562Stirling’s approxim<strong>at</strong>ion, 27, 257Fibonacci sequence, 32, 47–49, 89,469–470, 509FIFO list, 125file access, 282–283file manager, 268, 270, 274, 414, 415,421file processing, 80, 224, 295file structure, 9, 267, 341, 365first fit, see memory management, firstfitfloor function, 28floppy disk drive, 269Floyd’s algorithm, 513–515, 532, 535flyweight, see design p<strong>at</strong>tern, flyweightfragment<strong>at</strong>ion, 271, 274, 415, 419–421external, 415internal, 271, 415free store, 107–108
576 INDEXfree tree, 373, 393, 399freelist, 117, 120full binary tree theorem, 147–149, 160,189, 213function, m<strong>at</strong>hem<strong>at</strong>ical, 16garbage collection, 106general tree, 195–219ADT, 196–197, 216converting to binary tree, 210, 217dynamic implement<strong>at</strong>ions, 217implement<strong>at</strong>ion, 206–210left-child/right-sibling, 206, 207,217list of children, 206, 217, 373parent pointer implement<strong>at</strong>ion,199–206, 437terminology, 195–196traversal, see traversalgenerics, xvi, 12, 95Geographic Inform<strong>at</strong>ion System, 7–8geometric distribution, 308, 519, 522gigabyte, 27graph, xv, 22, 371–403, 407adjacency list, 371, 373, 374, 381,400adjacency m<strong>at</strong>rix, 371, 373, 374,378, 379, 400, 408ADT, 371, 376, 378connected component, 373, 402,482edge, 372implement<strong>at</strong>ion, 371, 376–378modeling of problems, 371, 380,384, 389, 390, 393parallel edge, 372represent<strong>at</strong>ion, 373–376self loop, 372terminology, 371–373traversal, see traversal, graphundirected, 372, 408vertex, 372gre<strong>at</strong>est common divisor, see largestcommon factorgreedy algorithm, 183, 396, 397growth r<strong>at</strong>e, 53, 56–58, 85asymptotic, 63constant, 56, 64exponential, 58, 62, 536, 541–555linear, 58, 61, 63, 80quadr<strong>at</strong>ic, 58, 61, 62, 80, 81halting problem, 555–561Hamiltonian cycle, 563Harmonic Series, 31, 309, 475hashing, 7, 10, 29, 60, 302, 314–335,341, 342, 355, 409, 453, 481analysis of, 331–334bucket, 321–323, 339closed, 320–329, 338collision resolution, 315, 321–329,334, 335deletion, 334–335, 338double, 329, 338dynamic, 335hash function, 315–320, 337home position, 321linear probing, 324–326, 329, 333,334, 337, 339load factor, 331open, 320–321perfect, 315, 335primary clustering, 326–329probe function, 324, 325, 327–329probe sequence, 324–329, 331–335pseudo-r<strong>and</strong>om probing, 327, 329quadr<strong>at</strong>ic probing, 328, 329, 337,338search, 324table, 314tombstone, 334header node, 120, 128heap, 145, 147, 161, 170–177, 188, 191,193, 243–244, 262, 391, 397
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Data Structures and AlgorithmAnalys
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viContents6.1 General Tree Definiti
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viiiContents10.5.2 B-Tree Analysis
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xContents15.7 Optimal Sorting 50115
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PrefaceWe study data structures so
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PrefacexvA sophomore-level class wh
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Prefacexviithe form ofcalls to meth
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PrefacexixFor the second edition, I
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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. 1.5 Further Reading 19vides po
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Sec. 1.6 Exercises 21than 10,000 of
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2Mathematical PreliminariesThis cha
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Sec. 2.1 Sets and Relations 25A seq
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Sec. 2.2 Miscellaneous Notation 27E
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3Algorithm AnalysisHow long will it
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Sec. 3.1 Introduction 55efficient.
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Sec. 3.1 Introduction 57n! 2 n2n 25
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4Lists, Stacks, and QueuesIf your p
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Sec. 4.1 Lists 101/** Singly linked
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Sec. 4.2 Stacks 121top1top2Figure 4
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Sec. 4.3 Queues 125/** Queue ADT */
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146 Chap. 5 Binary TreesABCDEFGHIFi
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148 Chap. 5 Binary TreesAny number
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150 Chap. 5 Binary Trees/** ADT for
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152 Chap. 5 Binary Treestends to be
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154 Chap. 5 Binary Trees5.3 Binary
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156 Chap. 5 Binary TreesABCDEFGHIFi
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160 Chap. 5 Binary Trees5.3.2 Space
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174 Chap. 5 Binary Trees/** Heapify
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176 Chap. 5 Binary TreesRH1H2Figure
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178 Chap. 5 Binary Trees5.6 Huffman
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180 Chap. 5 Binary TreesLetter C D
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182 Chap. 5 Binary Trees/** Huffman
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184 Chap. 5 Binary Trees/** Build a
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186 Chap. 5 Binary Treesa reverse p
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188 Chap. 5 Binary Trees18 bits, mo
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190 Chap. 5 Binary Trees5.12 Write
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196 Chap. 6 Non-Binary TreesRootRAn
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200 Chap. 6 Non-Binary Trees/** Gen
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7Internal SortingWe sort many thing
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266 Chap. 8 File Processing and Ext
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300 Chap. 8 File Processing and Ext
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302 Chap. 9 Searchingintroduced in
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304 Chap. 9 Searchingvalue in L gre
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308 Chap. 9 Searchingrecords by exp
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336 Chap. 9 SearchingA good introdu
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338 Chap. 9 Searching9.16 Assume th
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10IndexingMany large-scale computin
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Sec. 10.1 Linear Indexing 343Linear
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Sec. 10.2 ISAM 347In−memoryTable
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PART IVAdvanced Data Structures369
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372 Chap. 11 Graphs04123147123(a)(b
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374 Chap. 11 Graphs0 1 2 3 40201 11
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392 Chap. 11 Graphs/** Dijkstra’s
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394 Chap. 11 GraphsA7 5CB91 26ED 21
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400 Chap. 11 Graphs(a) IF an undire
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402 Chap. 11 Graphs11.8 Projects11.
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12Lists and Arrays RevisitedSimple
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Sec. 12.1 Multilists 407L1L2L3bcdL4
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Sec. 12.3 Memory Management 413/**
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13Advanced Tree StructuresThis chap
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14Analysis TechniquesOften it is ea
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486 Chap. 15 Lower Boundsthe concep
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492 Chap. 15 Lower BoundsProof 1: T
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494 Chap. 15 Lower BoundsFigure 15.
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496 Chap. 15 Lower BoundsTo minimiz
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500 Chap. 15 Lower BoundsFigure 15.
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502 Chap. 15 Lower Boundsnot only t
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504 Chap. 15 Lower Bounds1234Figure
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506 Chap. 15 Lower Bounds(a) Assume
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16Patterns of AlgorithmsThis chapte
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Sec. 16.1 Dynamic Programming 511Dy
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