Data Structures and Algorithm Analysis - Computer Science at ...

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BIBLIOGRAPHY 571[SJH93] Clifford A. Shaffer, Ramana Juvvadi, and Lenwood S. Heath. A generalizedcomparison of quadtree and bintree storage requirements. Imageand Vision Computing, 11(7):402–412, September 1993.[Ski10] Steven S. Skiena. The Algorithm Design Manual. Springer Verlag,New York, NY, second edition, 2010.[SM83] Gerard Salton and Michael J. McGill. Introduction to Modern InformationRetrieval. McGraw-Hill, New York, NY, 1983.[Sol09] Daniel Solow. How to Read and Do Proofs: An Introduction to MathematicalThought Processes. John Wiley & Sons, New York, NY, fifthedition, 2009.[ST85] D.D. Sleator and Robert E. Tarjan. Self-adjusting binary search trees.Journal of the ACM, 32:652–686, 1985.[Sta11a] William Stallings. Operating Systems: Internals and Design Principles.Prentice Hall, Upper Saddle River, NJ, seventh edition, 2011.[Sta11b] Richard M. Stallman. GNU Emacs Manual. Free Software Foundation,Cambridge, MA, sixteenth edition, 2011.[Ste90] Guy L. Steele. Common Lisp: The Language. Digital Press, Bedford,MA, second edition, 1990.[Sto88] James A. Storer. Data Compression: Methods and Theory. ComputerScience Press, Rockville, MD, 1988.[SU92] Clifford A. Shaffer and Mahesh T. Ursekar. Large scale editing andvector to raster conversion via quadtree spatial indexing. In Proceedingsof the 5th International Symposium on Spatial Data Handling,pages 505–513, August 1992.[SW94] Murali Sitaraman and Bruce W. Weide. Special feature: Componentbasedsoftware using resolve. Software Engineering Notes, 19(4):21–67, October 1994.[SWH93] Murali Sitaraman, Lonnie R. Welch, and Douglas E. Harms. Onspecification of reusable software components. International Journalof Software Engineering and Knowledge Engineering, 3(2):207–229,June 1993.[Tan06] Andrew S. Tanenbaum. Structured Computer Organization. PrenticeHall, Upper Saddle River, NJ, fifth edition, 2006.[Tar75] Robert E. Tarjan. On the efficiency of a good but not linear set mergingalgorithm. Journal of the ACM, 22(2):215–225, April 1975.[Wel88] Dominic Welsh. Codes and Cryptography. Oxford University Press,Oxford, 1988.[WL99] Arthur Whimbey and Jack Lochhead. Problem Solving & Comprehension.Lawrence Erlbaum Associates, Mahwah, NJ, sixth edition,1999.
572 BIBLIOGRAPHY[WMB99][Zei07]I.H. Witten, A. Moffat, and T.C. Bell. Managing Gigabytes. MorganKaufmann, second edition, 1999.Paul Zeitz. The Art and Craft of Problem Solving. John Wiley & Sons,New York, NY, second edition, 2007.
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Data Structures and AlgorithmAnalys
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ivContents2.6.1 Direct Proof 372.6.
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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. 1.2 Abstract Data Types and Da
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Sec. 1.3 Design Patterns 13that tra
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Sec. 1.3 Design Patterns 15will cal
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Sec. 1.4 Problems, Algorithms, and
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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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Sec. 2.3 Logarithms 29Unfortunately
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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 35(a)(b)Figure 2
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Sec. 2.6 Mathematical Proof Techniq
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Sec. 2.8 Further Reading 45one inch
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Sec. 2.9 Exercises 47(c) For nonzer
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Sec. 2.9 Exercises 492.16 Write a r
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Sec. 2.9 Exercises 512.38 How many
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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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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 633.4
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Sec. 3.4 Asymptotic Analysis 65If s
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Sec. 3.4 Asymptotic Analysis 67it i
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Sec. 3.5 Calculating the Running Ti
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Sec. 3.7 Common Misunderstandings 7
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Sec. 3.8 Multiple Parameters 77the
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Sec. 3.9 Space Bounds 79A data stru
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Sec. 3.10 Speeding Up Your Programs
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Sec. 3.11 Empirical Analysis 833.11
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Sec. 3.13 Exercises 853.13 Exercise
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Sec. 3.13 Exercises 87(f) sum = 0;f
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Sec. 3.14 Projects 893.24 Prove tha
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4Lists, Stacks, and QueuesIf your p
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Sec. 4.1 Lists 95list ADT. Interfac
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Sec. 4.1 Lists 97for (L.moveToStart
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Sec. 4.1 Lists 99public void moveTo
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Sec. 4.1 Lists 101/** Singly linked
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Sec. 4.1 Lists 103headcurrtailhead2
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Sec. 4.1 Lists 105/** Set curr at l
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Sec. 4.1 Lists 107curr...23 10 12(a
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Sec. 4.1 Lists 109/** Singly linked
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Sec. 4.1 Lists 111Array-based lists
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Sec. 4.1 Lists 113headcurrtail20 23
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Sec. 4.1 Lists 115/** Insert "it" a
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Sec. 4.2 Stacks 117The principle be
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Sec. 4.2 Stacks 119/** Array-based
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Sec. 4.2 Stacks 121top1top2Figure 4
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Sec. 4.2 Stacks 123you might want t
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Sec. 4.3 Queues 125/** Queue ADT */
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Sec. 4.3 Queues 127frontfront20 512
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Sec. 4.3 Queues 129/** Array-based
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Sec. 4.4 Dictionaries 1314.3.3 Comp
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Sec. 4.4 Dictionaries 133not get at
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Sec. 4.4 Dictionaries 135/** Contai
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Sec. 4.4 Dictionaries 137}/** @retu
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Sec. 4.6 Exercises 139(b) L2.append
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Sec. 4.7 Projects 1414.16 Re-implem
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Sec. 4.7 Projects 143‘a’ ‘b
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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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158 Chap. 5 Binary Treesto its call
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160 Chap. 5 Binary Trees5.3.2 Space
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162 Chap. 5 Binary Trees012345 678
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164 Chap. 5 Binary Trees12037422442
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166 Chap. 5 Binary Trees37244273240
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168 Chap. 5 Binary Treessubroot105
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170 Chap. 5 Binary Treesin the case
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172 Chap. 5 Binary Treessynonymous
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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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192 Chap. 5 Binary Trees(c) What is
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194 Chap. 5 Binary Trees5.7 Complet
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196 Chap. 6 Non-Binary TreesRootRAn
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198 Chap. 6 Non-Binary TreesRABCD E
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200 Chap. 6 Non-Binary Trees/** Gen
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202 Chap. 6 Non-Binary Treesspond t
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204 Chap. 6 Non-Binary Treesditiona
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206 Chap. 6 Non-Binary Treeslence o
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208 Chap. 6 Non-Binary TreesR’RA
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210 Chap. 6 Non-Binary TreesRRABABC
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212 Chap. 6 Non-Binary Trees(a)(b)F
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214 Chap. 6 Non-Binary Treestwo chi
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216 Chap. 6 Non-Binary Treeschild v
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218 Chap. 6 Non-Binary TreesCAFBEHG
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220 Chap. 6 Non-Binary Treestree af
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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 231Insertion Bub
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Sec. 7.4 Mergesort 233static
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Sec. 7.4 Mergesort 235static
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Sec. 7.5 Quicksort 237Quicksort is
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Sec. 7.5 Quicksort 239static
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Sec. 7.5 Quicksort 241is still unli
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Sec. 7.6 Heapsort 243subarray, only
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Sec. 7.7 Binsort and Radix Sort 245
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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 257• Eq
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Sec. 7.11 Exercises 259algorithm to
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Sec. 7.12 Projects 2617.18 Which of
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Sec. 7.12 Projects 2637.6 It has be
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266 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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306 Chap. 9 SearchingWe now show th
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308 Chap. 9 Searchingrecords by exp
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310 Chap. 9 SearchingThis is potent
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312 Chap. 9 Searchingand the total
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314 Chap. 9 SearchingThis method of
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316 Chap. 9 Searchingbirthday is si
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318 Chap. 9 Searching45674567319692
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320 Chap. 9 Searching01000953012330
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322 Chap. 9 Searching01HashTable100
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324 Chap. 9 Searching/** Insert rec
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326 Chap. 9 Searching09050090501100
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328 Chap. 9 SearchingExample 9.9 Co
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330 Chap. 9 Searching/** Dictionary
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332 Chap. 9 SearchingThe cost for a
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334 Chap. 9 Searchingthat is not in
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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. 10.1 Linear Indexing 345JonesA
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Sec. 10.2 ISAM 347In−memoryTable
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Sec. 10.3 Tree-based Indexing 349Fi
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Sec. 10.4 2-3 Trees 351/** 2-3 tree
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Sec. 10.4 2-3 Trees 35318331223 30
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Sec. 10.5 B-Trees 355private TTNode
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Sec. 10.5 B-Trees 361331012 233348
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Sec. 10.5 B-Trees 3634845 4748 50 5
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Sec. 10.6 Further Reading 365at mos
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Sec. 10.8 Projects 36710.7 Prove th
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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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376 Chap. 11 Graphstime. This is a
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378 Chap. 11 GraphsIt is reasonably
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380 Chap. 11 Graphs}/** @return an
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382 Chap. 11 Graphs}/** Set the wei
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384 Chap. 11 GraphsABABCCDDFFEE(a)(
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386 Chap. 11 Graphs/** Breadth firs
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388 Chap. 11 Graphs/** Recursive to
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390 Chap. 11 GraphsA103B2205D11C15E
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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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396 Chap. 11 GraphsPrim’s algorit
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398 Chap. 11 GraphsInitialA B C D E
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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. 12.2 Matrix Representations 40
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Sec. 12.2 Matrix Representations 41
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Sec. 12.3 Memory Management 413/**
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Sec. 12.3 Memory Management 415Smal
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Sec. 12.3 Memory Management 417Tag
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Sec. 12.3 Memory Management 419tend
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Sec. 12.3 Memory Management 421is e
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Sec. 12.3 Memory Management 423AaBc
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Sec. 12.4 Further Reading 4251a3b42
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Sec. 12.6 Projects 42712.7 Write a
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13Advanced Tree StructuresThis chap
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Sec. 13.1 Tries 4310101010120001240
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Sec. 13.1 Tries 433000xxxx00xxxxx0x
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Sec. 13.2 Balanced Trees 4353737244
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Sec. 13.2 Balanced Trees 437that is
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Sec. 13.2 Balanced Trees 439GPDSASP
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Sec. 13.3 Spatial Data Structures 4
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Sec. 13.4 Further Reading 45313.3.4
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Sec. 13.6 Projects 455(c) Show the
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Sec. 13.6 Projects 45713.11 Select
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14Analysis TechniquesOften it is ea
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Sec. 14.1 Summation Techniques 463w
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Sec. 14.1 Summation Techniques 465B
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Sec. 14.2 Recurrence Relations 4671
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Sec. 14.2 Recurrence Relations 469n
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Sec. 14.2 Recurrence Relations 471E
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Sec. 14.2 Recurrence Relations 473N
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Sec. 14.2 Recurrence Relations 475T
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Sec. 14.3 Amortized Analysis 477(ch
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Sec. 14.4 Further Reading 479compar
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Sec. 14.5 Exercises 48114.14 For th
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Sec. 14.6 Projects 48314.24 Use mat
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486 Chap. 15 Lower Boundsthe concep
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488 Chap. 15 Lower Boundsat least o
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490 Chap. 15 Lower BoundsABCGDEFFig
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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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498 Chap. 15 Lower BoundsThis recur
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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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Sec. 16.1 Dynamic Programming 513on
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Sec. 16.2 Randomized Algorithms 515
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Page 546 and 547: Sec. 16.3 Numerical Algorithms 527B
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Page 586 and 587: Bibliography[AG06] Ken Arnold and J
Page 588 and 589: BIBLIOGRAPHY 569[GI91] Zvi Galil an
Page 592 and 593: Index80/20 rule, 309, 333abstract d
Page 594 and 595: INDEX 575image space, 430key space,
Page 596 and 597: INDEX 577building, 172-177for memor
Page 598 and 599: INDEX 579octree, 451Ω notation, 65
Page 600 and 601: INDEX 581comparing algorithms, 224-
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