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34 Chap. 2 Mathematical Preliminari
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36 Chap. 2 Mathematical Preliminari
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38 Chap. 2 Mathematical Preliminari
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40 Chap. 2 Mathematical Preliminari
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42 Chap. 2 Mathematical Preliminari
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44 Chap. 2 Mathematical Preliminari
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46 Chap. 2 Mathematical Preliminari
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48 Chap. 2 Mathematical Preliminari
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50 Chap. 2 Mathematical Preliminari
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52 Chap. 2 Mathematical Preliminari
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54 Chap. 2 Mathematical Preliminari
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56 Chap. 2 Mathematical Preliminari
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58 Chap. 3 Algorithm Analysisrun th
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60 Chap. 3 Algorithm Analysisseen s
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62 Chap. 3 Algorithm Analysis1400n!
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64 Chap. 3 Algorithm Analysisn valu
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66 Chap. 3 Algorithm Analysisf(n) n
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68 Chap. 3 Algorithm Analysiswhen w
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70 Chap. 3 Algorithm Analysissequen
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72 Chap. 3 Algorithm Analysismany a
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74 Chap. 3 Algorithm Analysisbecaus
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76 Chap. 3 Algorithm Analysissum1 =
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78 Chap. 3 Algorithm AnalysisPositi
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80 Chap. 3 Algorithm AnalysisBubble
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82 Chap. 3 Algorithm Analysisgoing
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84 Chap. 3 Algorithm AnalysisThe an
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86 Chap. 3 Algorithm Analysisof its
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88 Chap. 3 Algorithm Analysisto hav
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90 Chap. 3 Algorithm Analysis3.12 F
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92 Chap. 3 Algorithm Analysis(b) Wh
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94 Chap. 3 Algorithm Analysis3.17 G
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PART IIFundamental Data Structures9
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100 Chap. 4 Lists, Stacks, and Queu
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102 Chap. 4 Lists, Stacks, and Queu
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104 Chap. 4 Lists, Stacks, and Queu
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106 Chap. 4 Lists, Stacks, and Queu
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108 Chap. 4 Lists, Stacks, and Queu
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110 Chap. 4 Lists, Stacks, and Queu
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112 Chap. 4 Lists, Stacks, and Queu
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114 Chap. 4 Lists, Stacks, and Queu
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116 Chap. 4 Lists, Stacks, and Queu
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118 Chap. 4 Lists, Stacks, and Queu
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120 Chap. 4 Lists, Stacks, and Queu
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122 Chap. 4 Lists, Stacks, and Queu
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124 Chap. 4 Lists, Stacks, and Queu
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126 Chap. 4 Lists, Stacks, and Queu
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128 Chap. 4 Lists, Stacks, and Queu
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130 Chap. 4 Lists, Stacks, and Queu
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132 Chap. 4 Lists, Stacks, and Queu
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134 Chap. 4 Lists, Stacks, and Queu
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136 Chap. 4 Lists, Stacks, and Queu
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138 Chap. 4 Lists, Stacks, and Queu
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140 Chap. 4 Lists, Stacks, and Queu
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142 Chap. 4 Lists, Stacks, and Queu
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144 Chap. 4 Lists, Stacks, and Queu
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146 Chap. 4 Lists, Stacks, and Queu
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148 Chap. 4 Lists, Stacks, and Queu
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150 Chap. 4 Lists, Stacks, and Queu
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152 Chap. 4 Lists, Stacks, and Queu
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154 Chap. 5 Binary TreesABCDEFGHIFi
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156 Chap. 5 Binary TreesAny number
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158 Chap. 5 Binary Trees/** ADT for
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160 Chap. 5 Binary TreesFunction pr
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162 Chap. 5 Binary Trees205040 7520
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164 Chap. 5 Binary Trees/** Binary
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166 Chap. 5 Binary Treespublic inte
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168 Chap. 5 Binary Treespublic inte
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170 Chap. 5 Binary TreesIf P = D, t
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172 Chap. 5 Binary Trees012345 678
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174 Chap. 5 Binary Treesimport java
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176 Chap. 5 Binary Trees37244273240
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178 Chap. 5 Binary Treessubroot105
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180 Chap. 5 Binary Treesin the case
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182 Chap. 5 Binary TreesMin-heaps a
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184 Chap. 5 Binary Trees/** Put ele
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186 Chap. 5 Binary Trees172 34645 6
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188 Chap. 5 Binary Treeswhen search
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190 Chap. 5 Binary TreesLetter C D
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192 Chap. 5 Binary Trees3060 1120 1
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194 Chap. 5 Binary Treesclass HuffT
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196 Chap. 5 Binary TreesLetter Freq
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198 Chap. 5 Binary Treesits occurri
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200 Chap. 5 Binary Treesprints the
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202 Chap. 5 Binary Trees5.29 What w
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204 Chap. 5 Binary Trees5.5 Impleme
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206 Chap. 6 Non-Binary TreesRootRAn
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208 Chap. 6 Non-Binary TreesRABCD E
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210 Chap. 6 Non-Binary Treesobjects
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212 Chap. 6 Non-Binary TreesRWABXYZ
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214 Chap. 6 Non-Binary Treesusing t
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216 Chap. 6 Non-Binary Trees5 0 0 5
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218 Chap. 6 Non-Binary TreesRA BC D
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220 Chap. 6 Non-Binary TreesRVal Si
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222 Chap. 6 Non-Binary TreesRARCBAB
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224 Chap. 6 Non-Binary TreesABCDEFG
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226 Chap. 6 Non-Binary Treeswill us
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228 Chap. 6 Non-Binary Trees6.9 Dev
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230 Chap. 6 Non-Binary Trees6.8 Pro
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PART IIISorting and Searching233
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236 Chap. 7 Internal Sortingand Qui
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238 Chap. 7 Internal Sorting4220171
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240 Chap. 7 Internal Sorting4220171
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242 Chap. 7 Internal Sorting4220171
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244 Chap. 7 Internal Sorting7.3 She
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246 Chap. 7 Internal SortingSome ch
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248 Chap. 7 Internal Sortingsubarra
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250 Chap. 7 Internal Sortingsort ro
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252 Chap. 7 Internal Sortingstatic
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254 Chap. 7 Internal Sortinghappens
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256 Chap. 7 Internal SortingA simpl
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258 Chap. 7 Internal SortingOrigina
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260 Chap. 7 Internal Sortingthat ea
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262 Chap. 7 Internal SortingAs with
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264 Chap. 7 Internal SortingOne cou
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266 Chap. 7 Internal SortingSort 10
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268 Chap. 7 Internal Sortingcompari
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270 Chap. 7 Internal Sortingcompare
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272 Chap. 7 Internal Sorting7.11 Ex
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274 Chap. 7 Internal Sorting7.13 Gr
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276 Chap. 7 Internal Sortingcan sto
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8File Processing and ExternalSortin
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Sec. 8.1 Primary versus Secondary S
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Sec. 8.2 Disk Drives 283of the data
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Sec. 8.2 Disk Drives 285the informa
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Sec. 8.2 Disk Drives 287Intersector
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Sec. 8.3 Buffers and Buffer Pools 2
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Sec. 8.3 Buffers and Buffer Pools 2
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Sec. 8.3 Buffers and Buffer Pools 2
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Sec. 8.3 Buffers and Buffer Pools 2
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Sec. 8.4 The Programmer’s View of
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Sec. 8.5 External Sorting 299block
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Sec. 8.5 External Sorting 3018.5.1
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Sec. 8.5 External Sorting 303quenti
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Sec. 8.5 External Sorting 305InputF
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Sec. 8.5 External Sorting 307Fallin
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Sec. 8.7 Exercises 311A great discu
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Sec. 8.7 Exercises 313(a) The file
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Sec. 8.8 Projects 315processing is
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9SearchingOrganizing and retrieving
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Sec. 9.1 Searching Unsorted and Sor
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Sec. 9.1 Searching Unsorted and Sor
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Sec. 9.1 Searching Unsorted and Sor
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Sec. 9.2 Self-Organizing Lists 325A
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Sec. 9.2 Self-Organizing Lists 327n
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Sec. 9.3 Bit Vectors for Representi
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Sec. 9.4 Hashing 331are many approa
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Sec. 9.4 Hashing 3331. Natural dist
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Sec. 9.4 Hashing 335For example, be
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Sec. 9.4 Hashing 337010009530123301
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Sec. 9.4 Hashing 339the desired key
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Sec. 9.4 Hashing 341number of recor
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Sec. 9.4 Hashing 343sequence that c
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Sec. 9.4 Hashing 345found. Alternat
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Sec. 9.4 Hashing 347/** Dictionary
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Sec. 9.4 Hashing 34954InsertDelete3
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Sec. 9.5 Further Reading 351occupie
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Sec. 9.6 Exercises 353list ordered
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Sec. 9.7 Projects 355Be sure to ind
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10IndexingMany large-scale computin
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Sec. 10.1 Linear Indexing 359Linear
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Sec. 10.2 ISAM 361whose records hav
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Sec. 10.2 ISAM 363In-memoryTable of
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Sec. 10.3 Tree-based Indexing 365is
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Sec. 10.4 2-3 Trees 36718331223 30
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Sec. 10.4 2-3 Trees 36918331223 304
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Sec. 10.5 B-Trees 373/** Add a new
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Sec. 10.5 B-Trees 375examining the
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Sec. 10.5 B-Trees 3773318234810 12
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Sec. 10.5 B-Trees 3793318 23 481012
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Sec. 10.5 B-Trees 381required (beca
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Sec. 10.7 Exercises 383(a) Assume t
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Sec. 10.8 Projects 38510.8 Projects
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11GraphsGraphs provide the ultimate
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Sec. 11.1 Terminology and Represent
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Sec. 11.1 Terminology and Represent
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Sec. 11.2 Graph Implementations 395
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Sec. 11.2 Graph Implementations 397
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Sec. 11.3 Graph Traversals 399// Ad
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Sec. 11.3 Graph Traversals 401speci
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Sec. 11.3 Graph Traversals 403ACall
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Sec. 11.3 Graph Traversals 405ABABC
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Sec. 11.4 Shortest-Paths Problems 4
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Sec. 11.4 Shortest-Paths Problems 4
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Sec. 11.5 Minimum-Cost Spanning Tre
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Sec. 11.6 Further Reading 417Exampl
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Sec. 11.7 Exercises 419class Kruska
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Sec. 11.8 Projects 421MST, show the
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12Lists and Arrays RevisitedSimple
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Sec. 12.1 Multilists 425L1L2L3bcdL4
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Sec. 12.2 Matrix Representations 42
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Sec. 12.2 Matrix Representations 42
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Sec. 12.3 Memory Management 431/**
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Sec. 12.3 Memory Management 433that
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Sec. 12.3 Memory Management 437assu
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Sec. 12.3 Memory Management 439Hand
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Sec. 12.3 Memory Management 441and
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Sec. 12.4 Further Reading 4431a3b42
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Sec. 12.6 Projects 44512.9 Write me
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13Advanced Tree StructuresThis chap
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Sec. 13.1 Tries 4490012 70102403201
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Sec. 13.1 Tries 451000xxxx00xxxxx0x
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Sec. 13.2 Balanced Trees 453If we a
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Sec. 13.2 Balanced Trees 455SXDYAYX
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Sec. 13.2 Balanced Trees 457PSSCAPA
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Sec. 13.3 Spatial Data Structures 4
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Sec. 13.3 Spatial Data Structures 4
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Sec. 13.4 Further Reading 473Spatia
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Sec. 13.6 Projects 47513.15 (a) Sho
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Sec. 13.6 Projects 47713.11 Impleme
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14Analysis TechniquesThis book cont
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Sec. 14.1 Summation Techniques 483c
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Sec. 14.1 Summation Techniques 485O
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Sec. 14.2 Recurrence Relations 487n
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Sec. 14.2 Recurrence Relations 489t
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Sec. 14.2 Recurrence Relations 491u
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Sec. 14.2 Recurrence Relations 493W
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Sec. 14.2 Recurrence Relations 495T
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Sec. 14.3 Amortized Analysis 49714.
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Sec. 14.3 Amortized Analysis 499A s
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Sec. 14.5 Exercises 50114.4 Use sub
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Sec. 14.5 Exercises 50314.21 One ap
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Sec. 14.6 Projects 50514.6 Projects
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508 Chap. 15 Lower Boundsbounds on
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510 Chap. 15 Lower Boundsobserve th
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512 Chap. 15 Lower BoundsABCGDEFFig
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514 Chap. 15 Lower Boundsbetter tha
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516 Chap. 15 Lower Boundsfor a tota
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518 Chap. 15 Lower BoundsIn the Han
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520 Chap. 15 Lower BoundsFor exampl
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522 Chap. 15 Lower Bounds... i-1...
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524 Chap. 15 Lower BoundsT(n) ≤ T
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526 Chap. 15 Lower BoundsABAorAFigu
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528 Chap. 15 Lower Bounds15.2 Singl
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530 Chap. 15 Lower Bounds15.18 Writ
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532 Chap. 16 Patterns of Algorithms
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534 Chap. 16 Patterns of Algorithms
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536 Chap. 16 Patterns of Algorithms
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538 Chap. 16 Patterns of Algorithms
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540 Chap. 16 Patterns of Algorithms
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542 Chap. 16 Patterns of Algorithms
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544 Chap. 16 Patterns of Algorithms
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546 Chap. 16 Patterns of Algorithms
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548 Chap. 16 Patterns of Algorithms
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550 Chap. 16 Patterns of Algorithms
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552 Chap. 16 Patterns of Algorithms
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554 Chap. 16 Patterns of Algorithms
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556 Chap. 16 Patterns of Algorithms
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17Limits to ComputationThis book de
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Sec. 17.1 Reductions 56123421793881
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Sec. 17.1 Reductions 563the records
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Sec. 17.1 Reductions 565SORTING:Int
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Sec. 17.2 Hard Problems 567The Towe
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Sec. 17.2 Hard Problems 5693EA8224B
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Sec. 17.2 Hard Problems 571There is
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Sec. 17.2 Hard Problems 573SATISFIA
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Sec. 17.2 Hard Problems 575For the
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Sec. 17.2 Hard Problems 577x 1x 2x
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Sec. 17.2 Hard Problems 579tree. In
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Sec. 17.3 Impossible Problems 58117
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Sec. 17.3 Impossible Problems 583ar
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Sec. 17.3 Impossible Problems 5851
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Sec. 17.3 Impossible Problems 587an
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Sec. 17.5 Exercises 58917.3 Use a r
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Sec. 17.6 Projects 59117.14 The las
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Bibliography[AG06] Ken Arnold and J
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BIBLIOGRAPHY 595[GI91] Zvi Galil an
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BIBLIOGRAPHY 597[Ski98] Steven S. S
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IndexJava, xiv-xvii, 19-21generic,
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INDEX 601composite, see design patt
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INDEX 603constant, 60, 69exponentia
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INDEX 605logical representation, se
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INDEX 607199, 200, 203, 247, 249, 2
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INDEX 609units of measure, 29, 49UN