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Stacks © 2004 Goodrich, Tamassia Stacks Stacks © 2004 Goodrich, Tamassia Stacks

Abstract Data Types (ADTs) An abstract data type (ADT) is an abstraction of a Abstract Data Types (ADTs) An abstract data type (ADT) is an abstraction of a data structure An ADT specifies: n n n Data stored Operations on the data Error conditions associated with operations © 2004 Goodrich, Tamassia Example: ADT modeling a simple stock trading system n n The data stored are buy/sell orders The operations supported are w order buy(stock, shares, price) w order sell(stock, shares, price) w void cancel(order) n Error conditions: w Buy/sell a nonexistent stock w Cancel a nonexistent order Stacks 2

The Stack ADT (§ 4. 2) The Stack ADT stores arbitrary objects Insertions and The Stack ADT (§ 4. 2) 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: n n push(object): inserts an element object pop(): removes and returns the last inserted element © 2004 Goodrich, Tamassia Stacks Auxiliary stack operations: n n n object top(): returns the last inserted element without removing it integer size(): returns the number of elements stored boolean is. Empty(): indicates whether no elements are stored 3

Stack Interface in Java interface corresponding to our Stack ADT Requires the definition of Stack Interface in Java interface corresponding to our Stack ADT Requires the definition of class Empty. Stack. Except ion Different from the built-in Java class java. util. Stack © 2004 Goodrich, Tamassia public interface Stack { public int size(); public boolean is. Empty(); public Object top() throws Empty. Stack. Exception; public void push(Object o); public Object pop() throws Empty. Stack. Exception; } Stacks 4

Exceptions Attempting the execution of an operation of ADT may sometimes cause an error Exceptions 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 © 2004 Goodrich, Tamassia Stacks 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 Empty. Stack. Exception 5

Applications of Stacks Direct applications n n n Page-visited history in a Web browser Applications of Stacks Direct applications n n n Page-visited history in a Web browser Undo sequence in a text editor Chain of method calls in the Java Virtual Machine Indirect applications n n Auxiliary data structure for algorithms Component of other data structures © 2004 Goodrich, Tamassia Stacks 6

Method Stack in the JVM The Java Virtual Machine (JVM) keeps track of the Method Stack in the JVM 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 main() { int i = 5; foo(i); } foo(int j) { int k; n Local variables and return value n Program counter, keeping track of k = j+1; the statement being executed bar(k); When a method ends, its frame } is popped from the stack and control is passed to the method bar(int m) { on top of the stack … Allows for recursion } Stacks © 2004 Goodrich, Tamassia bar PC = 1 m=6 foo PC = 3 j=5 k=6 main PC = 2 i=5 7

Array-based Stack A simple way of implementing the Stack ADT uses an array We Array-based Stack 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 Algorithm size() return t + 1 Algorithm pop() if is. Empty() then throw Empty. Stack. Exception else t t 1 return S[t + 1] … S 0 1 2 © 2004 Goodrich, Tamassia t Stacks 8

Array-based Stack (cont. ) The array storing the stack elements may become full A Array-based Stack (cont. ) The array storing the stack elements may become full A push operation will then throw a Full. Stack. Exception n n Algorithm push(o) if t = S. length 1 then throw Full. Stack. Exception else t t+1 Limitation of the array. S[t] o based implementation Not intrinsic to the Stack ADT … S 0 1 2 © 2004 Goodrich, Tamassia t Stacks 9

Performance and Limitations Performance n n n Let n be the number of elements Performance and Limitations Performance n n n Let n be the number of elements in the stack The space used is O(n) Each operation runs in time O(1) Limitations n n 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 © 2004 Goodrich, Tamassia Stacks 10

Array-based Stack in Java public class Array. Stack implements Stack { // holds the Array-based Stack in Java public class Array. Stack implements Stack { // holds the stack elements private Object S[ ]; // index to top element private int top = -1; // constructor public Array. Stack(int capacity) { S = new Object[capacity]); } © 2004 Goodrich, Tamassia public Object pop() throws Empty. Stack. Exception { if is. Empty() throw new Empty. Stack. Exception (“Empty stack: cannot pop”); Object temp = S[top]; // facilitates garbage collection S[top] = null; top = top – 1; return temp; Stacks 11

Parentheses Matching Each “(”, “{”, or “[” must be paired with a matching “)”, Parentheses Matching Each “(”, “{”, or “[” must be paired with a matching “)”, “}”, or “[” n n n correct: ( )(( )){([( )])} correct: ((( )){([( )])} incorrect: )(( )){([( )])} incorrect: ({[ ])} incorrect: ( © 2004 Goodrich, Tamassia Stacks 12

Parentheses Matching Algorithm Paren. Match(X, n): Input: An array X of n tokens, each Parentheses Matching Algorithm Paren. Match(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. is. Empty() 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. is. Empty() then return true {every symbol matched} else return false {some symbols were never matched} © 2004 Goodrich, Tamassia Stacks 13

HTML Tag Matching For fully-correct HTML, each <name> should pair with a matching </name> HTML Tag Matching For fully-correct HTML, each should pair with a matching

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?
© 2004 Goodrich, Tamassia 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? Stacks 14

Growable Array-based Stack In a push operation, when the Algorithm push(o) array is full, Growable Array-based Stack In a push operation, when the Algorithm push(o) array is full, instead of throwing if t = S. length 1 then an exception, we can replace A new array of the array with a larger one size … How large should the new array for i 0 to t do be? A[i] S[i] n incremental strategy: increase the size by a constant c S A n doubling strategy: double the size t t+1 S[t] o © 2004 Goodrich, Tamassia Stacks 15

Comparison of the Strategies We compare the incremental strategy and the doubling strategy by 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 © 2004 Goodrich, Tamassia Stacks 16

Incremental Strategy Analysis We replace the array k = n/c times The total time 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 + 2 c + 3 c + 4 c + … + kc = n + c(1 + 2 + 3 + … + k) = n + ck(k + 1)/2 Since c is a constant, T(n) is O(n + k 2), i. e. , O(n 2) The amortized time of a push operation is O(n) © 2004 Goodrich, Tamassia Stacks 17

Doubling Strategy Analysis We replace the array k = log 2 n times The Doubling Strategy Analysis We replace the array k = log 2 n times The total time T(n) of a series of geometric series n push operations is 2 proportional to 4 1 1 n + 1 + 2 + 4 + 8 + …+ 2 k = n + 2 k + 1 1 = 2 n 1 8 T(n) is O(n) The amortized time of a push operation is O(1) © 2004 Goodrich, Tamassia Stacks 18

Computing Spans (not in book) We show to use a stack as an auxiliary Computing Spans (not in book) We show 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 n E. g. , stock at 52 -week high © 2004 Goodrich, Tamassia Stacks X S 6 1 3 1 4 2 5 3 2 1 19

Quadratic Algorithm spans 1(X, n) Input array X of n integers Output array S Quadratic Algorithm spans 1(X, n) Input array X of n integers Output array S of spans of X S new array of n integers for i 0 to n 1 do s 1 while s i X[i s] X[i] s s+1 S[i] s return S # n n n 1 + 2 + …+ (n 1) n 1 Algorithm spans 1 runs in O(n 2) time © 2004 Goodrich, Tamassia Stacks 20

Computing Spans with a Stack We keep in a stack the indices of the 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 n n 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 © 2004 Goodrich, Tamassia Stacks 21

Linear Algorithm Each index of the array n n Is pushed into the stack Linear Algorithm Each index of the array n n 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 spans 2 runs in O(n) time © 2004 Goodrich, Tamassia Algorithm spans 2(X, n) S new array of n integers A new empty stack for i 0 to n 1 do while ( A. is. Empty() X[top()] X[i] ) do A. pop() if A. is. Empty() then S[i] i + 1 else S[i] i top() A. push(i) return S Stacks # n 1 n n n n 1 22