Chapter 7: Sorting (Insertion Sort, Shellsort) CE 221 Data Structures and Algorithms Chapter 7: Sorting (Insertion Sort, Shellsort) Text: Read Weiss, § 7.1 – 7.4 Izmir University of Economics

Izmir University of Economics Preliminaries Main memory sorting algorithms All algorithms are Interchangeable; an array containing the N elements will be passed. “<“, “>” (comparison) and “=“ (assignment) are the only operations allowed on the input data : comparison-based sorting Izmir University of Economics

Contents Selection Sort Insertion Sort Shell Sort

CE 221 Selection Sort

Selection Sort

Selection Sort

Selection Sort

Selection Sort

Selection Sort

Selection Sort

Selection Sort

Selection Sort

Selection Sort

Selection Sort

Selection Sort

Selection Sort

Selection Sort

Selection Sort

Selection Sort

Selection Sort

Selection Sort

Selection Sort

Selection Sort

Time Analysis of Selection Sort Comparisons: Exchanges: N

CE 221 Insertion Sort

Insertion Sort

Insertion Sort

Insertion Sort

Insertion Sort

Insertion Sort

Insertion Sort

Insertion Sort

Insertion Sort

Time Analysis Number of comparisions: Number of excahnges:

Effective Algorithms Shell Sort

Shell Sort Move entries more than one position at a time by h–sorting the array Start at L and look at every 4th element and sort it Start at E and look at every 4th ekement and sort it Start at A and look at every 4th ekement and sort it

Decreasing sequence of values of h

Example

Example: S O R T E X A M P L E Result: A E E L M O P R S T X

Implementation

Time Analysis

Shell Sort vs Insertion Sort Insertion sort compares every single item with all the rest elements of the list in order to find its place, Shell sort compares items that lie far apart. This makes light elements to move faster to the front of the list.

The End Yes, the End !!!!!

Insertion Sort Analysis One of the simplest sorting algorithms Consists of N-1 passes. for pass p = 1 to N-1 (0 thru p-1 already known to be sorted) elements in position 0 trough p (p+1 elements) are sorted by moving the element left until a smaller element is encountered. Izmir University of Economics

Insertion Sort - Algorithm typedef int ElementType; void InsertionSort( ElementType A[ ], int N ) { int j, P; ElementType Tmp; for( P = 1; P < N; P++ ) Tmp = A[ P ]; for( j = P; j > 0 && A[ j - 1 ] > Tmp; j-- ) A[ j ] = A[ j - 1 ]; A[ j ] = Tmp; } N*N iterations, hence, time complexity = O(N2) in the worst case.This bound is tight (input in the reverse order). Number of element comparisons in the inner loop is p, summing up over all p = 1+2+...+N-1 = Θ(N2). If the input is sorted O(N). Izmir University of Economics

A Lower Bound for Simple Sorting Algorithms An inversion in an array of numbers is any ordered pair (i, j) such that a[i] > a[j]. In the example set we have 9 inversions, (34,8),(34,32),(34,21),(64,51),(64,32),(64,21),(51,32),(51,21), and (32,21). Swapping two adjacent elements that are out of place removes exactly one inversion and a sorted array has no inversions. The running time of insertion sort O(I+N). Izmir University of Economics

Average Running Time for Simple Sorting - I Theorem: The average number of inversions for N distinct elements is the average number of inversions in a permutation, i.e., N(N-1)/4. Proof: It is the sum of the number of inversions in N! different permutations divided by N!. Each permutation L has a corresponding permutation LR which is reversed in sequence. If L has x inversions, then LR has N(N-1)/2 – x inversions. As a result ((N(N-1)/2) * (N!/2)) / N! = N(N-1)/4 is the number of inversions for an average list. Izmir University of Economics

Average Running Time for Simple Sorting - II Theorem: Any algorithm that sorts by exchanging adjacent elements requires Ω(N2) time on average. Proof: Initially there exists N(N-1)/4 inversions on the average and each swap removes only one inversion, so Ω(N2) swaps are required. This is valid for all types of sorting algorithms (including those undiscovered) that perform only adjacent exchanges. Result: For a sorting algorithm to run subquadratic (o(N2)), it must exchange elements that are far apart (eliminating more than just one inversion per exchange). Izmir University of Economics

Izmir University of Economics Shellsort - I Shellsort, invented by Donald Shell, works by comparing elements that are distant; the distance decreases as the algorithm runs until the last phase (diminishing increment sort) Sequence h1, h2, ..., ht is called the increment sequence. h1 = 1 always. After a phase, using hk, for every i, a[i] ≤ a[i+hk]. The file is then said to be hk-sorted. Izmir University of Economics

Izmir University of Economics Shellsort - II An hk-sorted file that is then hk-1-sorted remains hk-sorted. To hk-sort, for each i in hk,hk+1,...,N-1, place the element in the correct spot among i, i-hk, i-2hk. This is equivalent to performing an insertion sort on hk independent subarrays. Izmir University of Economics

Izmir University of Economics Shellsort - III void Shellsort( ElementType A[ ], int N ) { int i, j, Increment; ElementType Tmp; for( Increment = N / 2; Increment > 0; Increment /= 2 ) for( i = Increment; i < N; i++ ) Tmp = A[ i ]; for( j = i; j >= Increment; j -= Increment ) if( Tmp < A[ j - Increment ] ) A[ j ] = A[ j - Increment ]; else break; A[ j ] = Tmp; } Increment sequence by Shell: ht=floor(N/2), hk=floor(hk+1/2) (poor) Izmir University of Economics

Worst-Case Analysis of Shellsort - I Theorem: The worst case running time of Shellsort, using Shell’s increments, is Θ(N2). Proof: part I: prove Ω(N2)= Why? smallest N/2 elements goes from position 2i-1 to i during the last pass. Previous passes all have even increments. Izmir University of Economics

Worst-Case Analysis of Shellsort - II Proof: part II: prove O(N2) A pass with increment hk consists of hk insertion sorts of about N/hk elements. One pass,hence, is O(hk(N/hk)2). Summing over all passes which is O(N2). Shell’s increments: pairs of increments are not relatively prime. Hibbard’s increments: 1, 3, 7,..., 2k-1 Izmir University of Economics

Worst-Case Analysis of Shellsort - III Theorem: The worst case running time of Shellsort, using Hibbard’s increments, is Θ(N3/2). Proof: (results from additive number theory) - for hk>N1/2 use the bound O(N2/hk) // hk=1, 3, 7,..., 2t-1 hk+2 done, hk+1done, hk now. a[p-i] < a[p] if but hk+2=2hk+1+1 hence gcd(hk+2, hk+1) = 1 Thus all can be expressed as such . Therefore; innermost for loop executes O(hk) times for each N-hk positions. This gives a bound of O(Nhk) per pass. Izmir University of Economics

Izmir University of Economics Homework Assignments 7.1, 7.2, 7.3, 7.4 You are requested to study and solve the exercises. Note that these are for you to practice only. You are not to deliver the results to me. Izmir University of Economics