A Practical Introduction to Data Structures and Algorithm Analysis

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Sec. 4.1 Lists 103mentations, assertions are used to enforce such preconditions. In a commercialimplementation, such violations would be best implemented by the Java exceptionmechanism.A list can be iterated through as shown in the following code fragment.for (L.moveToStart(); L.currPos()
104 Chap. 4 Lists, Stacks, and Queues4.1.1 Array-Based List ImplementationThere are two standard approaches to implementing lists, the array-based list, andthe linked list. This section discusses the array-based approach. The linked list ispresented in Section 4.1.2. Time and space efficiency comparisons for the two arediscussed in Section 4.1.3.Figure 4.2 shows the array-based list implementation, named AList. AListinherits from abstract class List and so must implement all of the member functionsof List.Class AList’s private portion contains the data members for the array-basedlist. These include listArray, the array which holds the list elements. BecauselistArray must be allocated at some fixed size, the size of the array must beknown when the list object is created. Note that an optional parameter is declaredfor the AList constructor. With this parameter, the user can indicate the maximumnumber of elements permitted in the list. If no parameter is given, then it takes thevalue defaultSize, which is assumed to be a suitably defined constant value.Because each list can have a differently sized array, each list must rememberits maximum permitted size. Data member maxSize serves this purpose. At anygiven time the list actually holds some number of elements that can be less than themaximum allowed by the array. This value is stored in listSize. Data membercurr stores the current position. Because listArray, maxSize, listSize,and curr are all declared to be private, they may only be accessed by methodsof Class AList.Class AList stores the list elements in contiguous array positions. Array positionscorrespond to list positions. In other words, the element at position i in thelist is stored at array cell i. The head of the list is always at position 0. This makesrandom access to any element in the list quite easy. Given some position in the list,the value of the element in that position can be accessed directly. Thus, access toany element using the moveToPos method followed by the getValue methodtakes Θ(1) time.Because the array-based list implementation is defined to store list elementsin contiguous cells of the array, the insert, append, and remove methodsmust maintain this property. Inserting or removing elements at the tail of the listis easy, and the append operation takes Θ(1) time. However, if we wish to insertan element at the head of the list, all elements currently in the list must shift oneposition toward the tail to make room, as illustrated by Figure 4.3. This processtakes Θ(n) time if there are n elements already in the list. If we wish to insert atposition i within a list of n elements, then n − i elements must shift toward thetail. Removing an element from the head of the list is similar in that all remaining
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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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Page 132 and 133: Sec. 4.1 Lists 113curr... 23 12 ...
Page 134 and 135: Sec. 4.1 Lists 115// Singly linked
Page 136 and 137: Sec. 4.1 Lists 117determined size.
Page 138 and 139: Sec. 4.1 Lists 119pointer to each e
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Page 144 and 145: Sec. 4.2 Stacks 125/** Stack ADT */
Page 146 and 147: Sec. 4.2 Stacks 127// Linked stack
Page 148 and 149: Sec. 4.2 Stacks 129Currptr β 1Curr
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Page 152 and 153: Sec. 4.3 Queues 133/** Queue ADT */
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Page 156 and 157: Sec. 4.3 Queues 137// Array-based q
Page 158 and 159: Sec. 4.4 Dictionaries 139enqueue pl
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Page 162 and 163: Sec. 4.4 Dictionaries 143// Contain
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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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334 Chap. 9 SearchingExample 9.6 A
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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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366 Chap. 10 IndexingFigure 10.7 Br
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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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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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488 Chap. 14 Analysis Techniquesof
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490 Chap. 14 Analysis TechniquesHow
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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 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 555b
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Sec. 16.6 Projects 55716.8 What is
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560 Chap. 17 Limits to Computations
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562 Chap. 17 Limits to Computationf
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594 BIBLIOGRAPHY[BG00] Sara Baase a
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596 BIBLIOGRAPHY[LLKS85] E.L. Lawle
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598 BIBLIOGRAPHY[WMB99][Zei07]I.H.
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600 INDEXbest fit, see memory manag
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602 INDEXrelation, 27, 50estimating
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604 INDEXinteger representation, 5,
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606 INDEXpath compression, 215-216,
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608 INDEXterminology, 236-237spatia
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A Practical Introduction to Data Structures and Algorithm Analysis

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