Chapter 2: Basic Data Structures

1. Chapter 2: Basic Data Structures

2. Basic Data Structures • Stacks • Queues • Vectors, Linked Lists • Trees • Priority Queues and Heaps • Dictionaries and Hash Tables CS 315

3. An abstract data type (ADT) is an abstraction of a data structure An ADT specifies: Data stored Operations on the data Error conditions associated with operations Abstract Data Types (ADTs) • Attempting the execution of an operation of ADT may sometimes cause an error condition, called an exception • Exceptions are said to be “thrown” by an operation that cannot be executed CS 315

4. The Stack ADT stores arbitrary objects Insertions and deletions follow the last-in first-out scheme Think of a spring-loaded plate dispenser Main stack operations: push(object): inserts an element object pop(): removes and returns the last inserted element Auxiliary stack operations: object top(): returns the last inserted element without removing it integer size(): returns the number of elements stored boolean isEmpty(): indicates whether no elements are stored Example: The Stack ADT CS 315

5. In the Stack ADT, operations pop and top cannot be performed if the stack is empty Attempting the execution of pop or top on an empty stack throws an EmptyStackException Stack Exceptions CS 315

6. Performance and Limitations • Performance • Let n be the number of elements in the stack • The space used is O(n) • Each operation runs in time O(1) • Limitations • The maximum size of the stack must be defined a priori and cannot be changed • Trying to push a new element into a full stack causes an implementation-specific exception CS 315

7. Growable Array-based Stack Algorithmpush(o) ift=S.length 1then A new array of size … fori0tot do A[i]  S[i] S A tt +1 S[t] o • In a push operation, when the array is full, instead of throwing an exception, we can replace the array with a larger one • How large should the new array be? • incremental strategy: increase the size by a constant c • doubling strategy: double the size Cost O(n) per op Cost O(1) per op CS 315

8. The Queue ADT stores arbitrary objects Insertions and deletions follow the first-in first-out scheme Insertions are at the rear of the queue and removals are at the front of the queue Main queue operations: enqueue(object): inserts an element at the end of the queue object dequeue(): removes and returns the element at the front of the queue Auxiliary queue operations: object front(): returns the element at the front without removing it integer size(): returns the number of elements stored boolean isEmpty(): indicates whether no elements are stored Exceptions Attempting the execution of dequeue or front on an empty queue throws an EmptyQueueException The Queue ADT All ops cost O(1) CS 315

9. Applications of Queues • Direct applications • Waiting lists, bureaucracy • Access to shared resources (e.g., printer) • Multiprogramming • Indirect applications • Auxiliary data structure for algorithms • Component of other data structures CS 315

10. Use an array of size N in a circular fashion Two variables keep track of the front and rear f index of the front element r index immediately past the rear element Array location r is kept empty Q 0 1 2 f r Q 0 1 2 r f Array-based Queue normal configuration wrapped-around configuration CS 315

11. Growable Array-based Queue • In an enqueue operation, when the array is full, instead of throwing an exception, we can replace the array with a larger one • Similar to what we did for an array-based stack • The enqueue operation has amortized running time • O(n) with the incremental strategy • O(1) with the doubling strategy CS 315

12. The Vector ADT extends the notion of array by storing a sequence of arbitrary objects An element can be accessed, inserted or removed by specifying its rank (number of elements preceding it) An exception is thrown if an incorrect rank is specified (e.g., a negative rank) Main vector operations: object elemAtRank(integer r): returns the element at rank r without removing it object replaceAtRank(integer r, object o): replace the element at rank with o and return the old element insertAtRank(integer r, object o): insert a new element o to have rank r object removeAtRank(integer r): removes and returns the element at rank r Additional operations size() and isEmpty() The Vector ADT CS 315

13. Applications of Vectors • Direct applications • Sorted collection of objects (elementary database) • Indirect applications • Auxiliary data structure for algorithms • Component of other data structures CS 315

14. Use an array V of size N A variable n keeps track of the size of the vector (number of elements stored) Operation elemAtRank(r) is implemented in O(1) time by returning V[r] Array-based Vector V 0 1 2 n r CS 315

15. Insertion • In operation insertAtRank(r, o), we need to make room for the new element by shifting forward the n - r elements V[r], …, V[n -1] • In the worst case (r =0), this takes O(n) time V 0 1 2 n r V 0 1 2 n r V o 0 1 2 n r CS 315

16. V 0 1 2 n r V 0 1 2 n r V o 0 1 2 n r Deletion • In operation removeAtRank(r), we need to fill the hole left by the removed element by shifting backward the n - r -1 elements V[r +1], …, V[n -1] • In the worst case (r =0), this takes O(n) time CS 315

17. Performance • In the array based implementation of a Vector • The space used by the data structure is O(n) • size, isEmpty, elemAtRankand replaceAtRankrun in O(1) time • insertAtRankand removeAtRankrun in O(n) time • If we use the array in a circular fashion, insertAtRank(0)and removeAtRank(0)run in O(1) time • In an insertAtRankoperation, when the array is full, instead of throwing an exception, we can replace the array with a larger one CS 315

18. Singly Linked List • A singly linked list is a concrete data structure consisting of a sequence of nodes • Each node stores • element • link to the next node next node elem  A B C D CS 315

19. The Position ADT models the notion of place within a data structure where a single object is stored It gives a unified view of diverse ways of storing data, such as a cell of an array a node of a linked list Just one method: object element(): returns the element stored at the position Position ADT CS 315

20. The List ADT models a sequence of positions storing arbitrary objects It establishes a before/after relation between positions Generic methods: size(), isEmpty() Query methods: isFirst(p), isLast(p) Accessor methods: first(), last() before(p), after(p) Update methods: replaceElement(p, o), swapElements(p, q) insertBefore(p, o), insertAfter(p, o), insertFirst(o), insertLast(o) remove(p) List ADT CS 315

21. Doubly Linked List prev next • A doubly linked list provides a natural implementation of the List ADT • Nodes implement Position and store: • element • link to the previous node • link to the next node • Special trailer and header nodes elem node trailer nodes/positions header elements CS 315

22. Insertion p • We visualize operation insertAfter(p, X), which returns position q A B C p q A B C X p q A B X C CS 315

23. p A B C D Deletion • We visualize remove(p), where p = last() A B C p D A B C CS 315

24. Performance • In the implementation of the List ADT by means of a doubly linked list • The space used by a list with n elements is O(n) • The space used by each position of the list is O(1) • All the operations of the List ADT run in O(1) time • Operation element() of the Position ADT runs in O(1) time CS 315

25. The Sequence ADT is the union of the Vector and List ADTs Elements accessed by Rank, or Position Generic methods: size(), isEmpty() Vector-based methods: elemAtRank(r), replaceAtRank(r, o), insertAtRank(r, o), removeAtRank(r) List-based methods: first(), last(), before(p), after(p), replaceElement(p, o), swapElements(p, q), insertBefore(p, o), insertAfter(p, o), insertFirst(o), insertLast(o), remove(p) Bridge methods: atRank(r), rankOf(p) Sequence ADT CS 315

26. Applications of Sequences • The Sequence ADT is a basic, general-purpose, data structure for storing an ordered collection of elements • Direct applications: • Generic replacement for stack, queue, vector, or list • small database (e.g., address book) • Indirect applications: • Building block of more complex data structures CS 315

27. We use a circular array storing positions A position object stores: Element Rank Indices f and l keep track of first and last positions Array-based Implementation elements 0 1 2 3 positions S f l CS 315

28. Sequence Implementations CS 315

29. An iterator abstracts the process of scanning through a collection of elements Methods of the ObjectIterator ADT: object object() boolean hasNext() object nextObject() reset() Extends the concept of Position by adding a traversal capability Implementation with an array or singly linked list An iterator is typically associated with an another data structure We can augment the Stack, Queue, Vector, List and Sequence ADTs with method: ObjectIterator elements() Two notions of iterator: snapshot: freezes the contents of the data structure at a given time dynamic: follows changes to the data structure Iterators CS 315

30. Tree ADT • Query methods: • boolean isInternal(p) • boolean isExternal(p) • boolean isRoot(p) • Update methods: • swapElements(p, q) • object replaceElement(p, o) • Additional update methods may be defined by data structures implementing the Tree ADT • We use positions to abstract nodes • Generic methods: • integer size() • boolean isEmpty() • objectIterator elements() • positionIterator positions() • Accessor methods: • position root() • position parent(p) • positionIterator children(p) CS 315

31. Preorder Traversal AlgorithmpreOrder(v) visit(v) foreachchild w of v preorder (w) • A traversal visits the nodes of a tree in a systematic manner • In a preorder traversal, a node is visited before its descendants • Application: print a structured document 1 Make Money Fast! 2 5 9 1. Motivations 2. Methods References 6 7 8 3 4 2.3 BankRobbery 2.1 StockFraud 2.2 PonziScheme 1.1 Greed 1.2 Avidity CS 315

32. Postorder Traversal AlgorithmpostOrder(v) foreachchild w of v postOrder (w) visit(v) • In a postorder traversal, a node is visited after its descendants • Application: compute space used by files in a directory and its subdirectories 9 cs16/ 8 3 7 todo.txt1K homeworks/ programs/ 4 5 6 1 2 Robot.java20K h1c.doc3K h1nc.doc2K DDR.java10K Stocks.java25K CS 315

33. Binary Tree • Applications: • arithmetic expressions • decision processes • searching • A binary tree is a tree with the following properties: • Each internal node has two children • The children of a node are an ordered pair • We call the children of an internal node left child and right child • Alternative recursive definition: a binary tree is either • a tree consisting of a single node, or • a tree whose root has an ordered pair of children, each of which is a binary tree A B C D E F G H I CS 315

34. +   2 - 3 b a 1 Arithmetic Expression Tree • Binary tree associated with an arithmetic expression • internal nodes: operators • external nodes: operands • Example: arithmetic expression tree for the expression (2  (a - 1) + (3  b)) CS 315

35. Properties of Binary Trees • Properties: • e = i +1 • n =2e -1 • h  i • h  (n -1)/2 • e 2h • h log2e • h log2 (n +1)-1 • Notation n number of nodes e number of external nodes i number of internal nodes h height CS 315

36. The BinaryTree ADT extends the Tree ADT, i.e., it inherits all the methods of the Tree ADT Additional methods: position leftChild(p) position rightChild(p) position sibling(p) Update methods may be defined by data structures implementing the BinaryTree ADT BinaryTree ADT CS 315

37. Euler Tour Traversal • Generic traversal of a binary tree • Includes as special cases the preorder, postorder and inorder traversals • Walk around the tree and visit each node three times: • on the left (preorder) • from below (inorder) • on the right (postorder) +   L R B 2 - 3 2 5 1 CS 315

38.  Data Structure for Trees • A node is represented by an object storing • Element • Parent node • Sequence of children nodes • Node objects implement the Position ADT B   A D F B A D F   C E C E CS 315

39. D C A B E Data Structure for Binary Trees  • A node is represented by an object storing • Element • Parent node • Left child node • Right child node • Node objects implement the Position ADT   B A D     C E CS 315