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Stacks

Learn about abstract data types, specifically stacks and linked lists. Explore their operations, error conditions, and applications. Understand their implementations using arrays and how to handle exceptions.

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Stacks

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  1. Stacks Linked Lists

  2. 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 Example: ADT modeling a simple stock trading system The data stored are buy/sell orders The operations supported are order buy(stock, shares, price) order sell(stock, shares, price) void cancel(order) Error conditions: Buy/sell a nonexistent stock Cancel a nonexistent order Abstract Data Types (ADTs) Linked Lists

  3. 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 The Stack ADT (§4.2) Linked Lists

  4. Stack Interface in Java public interfaceStack{ public int size(); public boolean isEmpty(); public Object top()throwsEmptyStackException; public voidpush(Object o); public Object pop()throwsEmptyStackException;} • Java interface corresponding to our Stack ADT • Requires the definition of class EmptyStackException • Different from the built-in Java class java.util.Stack Linked Lists

  5. 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 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 Exceptions Linked Lists

  6. Applications of Stacks • Direct applications • Page-visited history in a Web browser • Undo sequence in a text editor • Chain of method calls in the Java Virtual Machine • Indirect applications • Auxiliary data structure for algorithms • Component of other data structures Linked Lists

  7. Method Stack in the JVM main() { int i = 5; foo(i); } foo(int j) { int k; k = j+1; bar(k); } bar(int m) { … } • The Java Virtual Machine (JVM) keeps track of the chain of active methods with a stack • When a method is called, the JVM pushes on the stack a frame containing • Local variables and return value • Program counter, keeping track of the statement being executed • When a method ends, its frame is popped from the stack and control is passed to the method on top of the stack • Allows for recursion bar PC = 1 m = 6 foo PC = 3 j = 5 k = 6 main PC = 2 i = 5 Linked Lists

  8. A simple way of implementing the Stack ADT uses an array We add elements from left to right A variable keeps track of the index of the top element Array-based Stack Algorithmsize() returnt +1 Algorithmpop() ifisEmpty()then throw EmptyStackException else tt 1 returnS[t +1] … S 0 1 2 t Linked Lists

  9. … S 0 1 2 t Array-based Stack (cont.) • The array storing the stack elements may become full • A push operation will then throw a FullStackException • Limitation of the array-based implementation • Not intrinsic to the Stack ADT Algorithmpush(o) ift=S.length 1then throw FullStackException else tt +1 S[t] o Linked Lists

  10. 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 Linked Lists

  11. Array-based Stack in Java public classArrayStackimplements Stack{ // holds the stack elementsprivate Object S[ ]; // index to top elementprivate int top = -1; // constructorpublicArrayStack(int capacity){S = new Object[capacity]);} public Object pop()throwsEmptyStackException{if isEmpty()throw newEmptyStackException(“Empty stack: cannot pop”);Object temp = S[top];// facilitates garbage collection S[top] =null; top = top – 1;returntemp;} Linked Lists

  12. Parentheses Matching • Each “(”, “{”, or “[” must be paired with a matching “)”, “}”, or “[” • correct: ( )(( )){([( )])} • correct: ((( )(( )){([( )])} • incorrect: )(( )){([( )])} • incorrect: ({[ ])} • incorrect: ( Linked Lists

  13. Parentheses Matching Algorithm Algorithm ParenMatch(X,n): Input: An array X of n tokens, each of which is either a grouping symbol, a variable, an arithmetic operator, or a number Output: true if and only if all the grouping symbols in X match Let S be an empty stack for i=0 to n-1 do if X[i] is an opening grouping symbol then S.push(X[i]) else if X[i] is a closing grouping symbol then if S.isEmpty() then return false {nothing to match with} if S.pop() does not match the type of X[i] then return false {wrong type} if S.isEmpty() then return true {every symbol matched} else return false {some symbols were never matched} Linked Lists

  14. <body> <center> <h1> The Little Boat </h1> </center> <p> The storm tossed the little boat like a cheap sneaker in an old washing machine. The three drunken fishermen were used to such treatment, of course, but not the tree salesman, who even as a stowaway now felt that he had overpaid for the voyage. </p> <ol> <li> Will the salesman die? </li> <li> What color is the boat? </li> <li> And what about Naomi? </li> </ol> </body> The Little Boat The storm tossed the little boat like a cheap sneaker in an old washing machine. The three drunken fishermen were used to such treatment, of course, but not the tree salesman, who even as a stowaway now felt that he had overpaid for the voyage. 1. Will the salesman die? 2. What color is the boat? 3. And what about Naomi? HTML Tag Matching • For fully-correct HTML, each <name> should pair with a matching </name> Linked Lists

  15. Tag Matching Algorithm • Is similar to parentheses matching: import java.util.StringTokenizer; import datastructures.Stack; import datastructures.NodeStack; import java.io.*; /** Simpli.ed test of matching tags in an HTML document. */ public class HTML { /** Nested class to store simple HTML tags */ public static class Tag { String name; // The name of this tag boolean opening; // Is true i. this is an opening tag public Tag() { // Default constructor name = ""; opening = false; } public Tag(String nm, boolean op) { // Preferred constructor name = nm; opening = op; } /** Is this an opening tag? */ public boolean isOpening() { return opening; } /** Return the name of this tag */ public String getName() {return name; } } /** Test if every opening tag has a matching closing tag. */ public boolean isHTMLMatched(Tag[ ] tag) { Stack S = new NodeStack(); // Stack for matching tags for (int i=0; (i<tag.length) && (tag[i] != null); i++) { if (tag[i].isOpening()) S.push(tag[i].getName()); // opening tag; push its name on the stack else { if (S.isEmpty()) // nothing to match return false; if (!((String) S.pop()).equals(tag[i].getName())) // wrong match return false; } } if (S.isEmpty()) return true; // we matched everything return false; // we have some tags that never were matched } Linked Lists

  16. Tag Matching Algorithm, cont. public final static int CAPACITY = 1000; // Tag array size upper bound /* Parse an HTML document into an array of html tags */ public Tag[ ] parseHTML(BufferedReader r) throws IOException { String line; // a line of text boolean inTag = false ; // true iff we are in a tag Tag[ ] tag = new Tag[CAPACITY]; // our tag array (initially all null) int count = 0 ; // tag counter while ((line = r.readLine()) != null) { // Create a string tokenizer for HTML tags (use < and > as delimiters) StringTokenizer st = new StringTokenizer(line,"<> \t",true); while (st.hasMoreTokens()) { String token = (String) st.nextToken(); if (token.equals("<")) // opening a new HTML tag inTag = true; else if (token.equals(">")) // ending an HTML tag inTag = false; else if (inTag) { // we have a opening or closing HTML tag if ( (token.length() == 0) | | (token.charAt(0) != ’/’) ) tag[count++] = new Tag(token, true); // opening tag else // ending tag tag[count++] = new Tag(token.substring(1), false); // skip the } // Note: we ignore anything not in an HTML tag } } return tag; // our array of tags } /** Tester method */ public static void main(String[ ] args) throws IOException { BufferedReader stdr; // Standard Input Reader stdr = new BufferedReader(new InputStreamReader(System.in)); HTML tagChecker = new HTML(); if (tagChecker.isHTMLMatched(tagChecker.parseHTML(stdr))) System.out.println("The input file is a matched HTML document."); else System.out.println("The input file is not a matched HTML document."); } } Linked Lists

  17. Computing Spans (not in book) • We show how to use a stack as an auxiliary data structure in an algorithm • Given an an array X, the span S[i] of X[i] is the maximum number of consecutive elements X[j] immediately preceding X[i] and such that X[j]  X[i] • Spans have applications to financial analysis • E.g., stock at 52-week high X S Linked Lists

  18. Quadratic Algorithm Algorithmspans1(X, n) Inputarray X of n integers Outputarray S of spans of X # S new array of n integers n fori0ton 1do n s 1n while s i X[i - s]X[i]1 + 2 + …+ (n 1) ss+ 11 + 2 + …+ (n 1) S[i]sn returnS 1 • Algorithm spans1 runs in O(n2) time Linked Lists

  19. Computing Spans with a Stack • We keep in a stack the indices of the elements visible when “looking back” • We scan the array from left to right • Let i be the current index • We pop indices from the stack until we find index j such that X[i] X[j] • We set S[i]i - j • We push x onto the stack Linked Lists

  20. Linear Algorithm • Each index of the array • Is pushed into the stack exactly one • Is popped from the stack at most once • The statements in the while-loop are executed at most n times • Algorithm spans2 runs in O(n) time Algorithmspans2(X, n)# S new array of n integers n A new empty stack 1 fori0ton 1do n while(A.isEmpty()  X[A.top()]X[i] )do n A.pop()n if A.isEmpty()thenn S[i] i +1 n else S[i]i - A.top()n A.push(i) n returnS 1 Linked Lists

  21. Queues Linked Lists

  22. 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 (§4.3) Linked Lists

  23. Queue Example Operation Output Q enqueue(5) – (5) enqueue(3) – (5, 3) dequeue() 5 (3) enqueue(7) – (3, 7) dequeue() 3 (7) front() 7 (7) dequeue() 7 () dequeue() “error” () isEmpty() true () enqueue(9) – (9) enqueue(7) – (9, 7) size() 2 (9, 7) enqueue(3) – (9, 7, 3) enqueue(5) – (9, 7, 3, 5) dequeue() 9 (7, 3, 5) Linked Lists

  24. 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 Linked Lists

  25. 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 Linked Lists

  26. Q 0 1 2 f r Q 0 1 2 r f Queue Operations Algorithmsize() return(N-f +r) mod N AlgorithmisEmpty() return(f=r) • We use the modulo operator (remainder of division) Linked Lists

  27. Q 0 1 2 f r Q 0 1 2 r f Queue Operations (cont.) Algorithmenqueue(o) ifsize()=N 1then throw FullQueueException else Q[r] o r(r + 1) mod N • Operation enqueue throws an exception if the array is full • This exception is implementation-dependent Linked Lists

  28. Q 0 1 2 f r Q 0 1 2 r f Queue Operations (cont.) Algorithmdequeue() ifisEmpty()then throw EmptyQueueException else oQ[f] f(f + 1) mod N returno • Operation dequeue throws an exception if the queue is empty • This exception is specified in the queue ADT Linked Lists

  29. Queue Interface in Java public interfaceQueue{ public int size(); public boolean isEmpty(); public Object front()throwsEmptyQueueException; public voidenqueue(Object o); public Object dequeue()throwsEmptyQueueException;} • Java interface corresponding to our Queue ADT • Requires the definition of class EmptyQueueException • No corresponding built-in Java class Linked Lists

  30. The Queue 2 . Service the 3 . Enqueue the 1 . Deque the next element serviced element next element Shared Service Application: Round Robin Schedulers • We can implement a round robin scheduler using a queue, Q, by repeatedly performing the following steps: • e = Q.dequeue() • Service element e • Q.enqueue(e) Linked Lists

  31. Linked Lists Linked Lists

  32. Singly Linked List (§ 4.4.1) • 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 Linked Lists

  33. The Node Class for List Nodes public class Node { // Instance variables: private Object element; private Node next; /** Creates a node with null references to its element and next node. */ public Node() { this(null, null); } /** Creates a node with the given element and next node. */ public Node(Object e, Node n) { element = e; next = n; } // Accessor methods: public Object getElement() { return element; } public Node getNext() { return next; } // Modifier methods: public void setElement(Object newElem) { element = newElem; } public void setNext(Node newNext) { next = newNext; } } Linked Lists

  34. Allocate a new node Insert new element Have new node point to old head Update head to point to new node Inserting at the Head Linked Lists

  35. Removing at the Head • Update head to point to next node in the list • Allow garbage collector to reclaim the former first node Linked Lists

  36. Inserting at the Tail • Allocate a new node • Insert new element • Have new node point to null • Have old last node point to new node • Update tail to point to new node Linked Lists

  37. Removing at the Tail • Removing at the tail of a singly linked list is not efficient! • There is no constant-time way to update the tail to point to the previous node Linked Lists

  38. Stack with a Singly Linked List • We can implement a stack with a singly linked list • The top element is stored at the first node of the list • The space used is O(n) and each operation of the Stack ADT takes O(1) time nodes t  elements Linked Lists

  39. Queue with a Singly Linked List • We can implement a queue with a singly linked list • The front element is stored at the first node • The rear element is stored at the last node • The space used is O(n) and each operation of the Queue ADT takes O(1) time r nodes f  elements Linked Lists

  40. Vectors and Array Lists Linked Lists

  41. 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 (§5.1) Linked Lists

  42. Applications of Vectors • Direct applications • Sorted collection of objects (elementary database) • Indirect applications • Auxiliary data structure for algorithms • Component of other data structures Linked Lists

  43. 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 Linked Lists

  44. 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 Linked Lists

  45. 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 Linked Lists

  46. 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 Linked Lists

  47. Growable Array-based Vector 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 Linked Lists

  48. Comparison of the Strategies • We compare the incremental strategy and the doubling strategy by analyzing the total time T(n) needed to perform a series of n push operations • We assume that we start with an empty stack represented by an array of size 1 • We call amortized time of a push operation the average time taken by a push over the series of operations, i.e., T(n)/n Linked Lists

  49. Incremental Strategy Analysis • We replace the array k = n/c times • The total time T(n) of a series of n push operations is proportional to n + c + 2c + 3c + 4c + … + kc = n + c(1 + 2 + 3 + … + k) = n + ck(k + 1)/2 • Since c is a constant, T(n) is O(n +k2),i.e., O(n2) • The amortized time of a push operation is O(n) Linked Lists

  50. geometric series 2 4 1 1 8 Doubling Strategy Analysis • We replace the array k = log2n times • The total time T(n) of a series of n push operations is proportional to n + 1 + 2 + 4 + 8 + …+ 2k= n+ 2k + 1-1 = 2n -1 • T(n) is O(n) • The amortized time of a push operation is O(1) Linked Lists

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