CSE 221/ICT221 Analysis and Design of Algorithms Lecture 05: Analysis of time Complexity of Sorting...

CSE 221/ICT221 CSE 221/ICT221 Analysis and Design of AlgorithmsAnalysis and Design of Algorithms

Lecture 05:Lecture 05:Analysis of time Complexity of Analysis of time Complexity of Sorting AlgorithmsSorting Algorithms

Dr.Surasak MungsingDr.Surasak MungsingE-mail: [email protected]

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Sorting AlgorithmsSorting Algorithms

Bin Sort Radix Sort Insertion Sort Shell Sort Selection Sort Heap Sort Bubble Sort Quick Sort Merge Sort

CSE221/ICT221 Analysis and Design of Algorithms

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Bin SortBin Sort

A 2 C 5B 4 J 3H 3 I 4D 4 E 3 F 0 G 4

F A EHJ

BDGI

CBin 0 Bin 1 Bin 2 Bin 3 Bin 4 Bin 5

F 0 E 3A 2 C 5G 4 I 4H 3 J 3 B 4 D 4

(a) Input chain

(b) Nodes in bins

(c) Sorted chain


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Radix Sort with r=10 and d=3Radix Sort with r=10 and d=3

216 521 425 116 91 515 124 34 96 24(a) Input chain

24 34 91 96 116 124 216 425 515 521

(d) Chain after sorting on most significant digit

515 216 116 521 124 24 425 34 91 96(c) Chain after sorting on second-least significant digit

521 91 124 34 24 425 515 216 116 96(b) Chain after sorting on least significant digit

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Insertion Sort Concept

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Shell Sort Algorithm


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Shell Sort Demohttp://e-learning.mfu.ac.th/mflu/1302251/demodemo//Chap03Chap03//ShellSortShellSort//

ShellSortShellSort..htmlhtml

http://e-learning.mfu.ac.th/mflu/1302251/demo/Chap03/ShellSort/ShellSort.html


















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Selection Sort Concept


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Heap Sort Algorithm


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Bubble Sort Concept

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Quick sortQuick sort

4313

8131

92

57

65

75

260

4313

8131

92

57

65

75

260

650

3113

26

5743

92 75

81

Select pivot

Partition

The fastest known sorting algorithm in practice.


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Quick sortQuick sort

0 3126 5743 9275 816513

650

3113

26

5743

92 75

81

0 3126 574313 65 9275 81

Quick sort small Quick sort large


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Quick sort

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Quick Sort Partitions


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Quick sort


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External Sort: A simple merge


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Merge Sort


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Merge Sort


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Analysis of Insertion SortAnalysis of Insertion Sort

for (int i = 1; i < a.length; i++){// insert a[i] into a[0:i-1] int t = a[i]; int j; for (j = i - 1; j >= 0 && t < a[j]; j--) a[j + 1] = a[j]; a[j + 1] = t;}


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ComplexityComplexity

Space/Memory Time

Count a particular operation Count number of steps Asymptotic complexity


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Comparison CountComparison Count

for (int i = 1; i < a.length; i++){// insert a[i] into a[0:i-1] int t = a[i]; int j; for (j = i - 1; j >= 0 && t < a[j]; j--) a[j + 1] = a[j]; a[j + 1] = t;}


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for (j = i - 1; j >= 0 && t < a[j]; j--) a[j + 1] = a[j];

How many comparisons are made?


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for (j = i - 1; j >= 0 && t < a[j]; j--) a[j + 1] = a[j];

number of compares depends on a[]s and t as well as on i


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Worst-case count = maximum countBest-case count = minimum countAverage count


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Worst-Case Comparison CountWorst-Case Comparison Count

for (j = i - 1; j >= 0 && t < a[j]; j--) a[j + 1] = a[j];

a = [1, 2, 3, 4] and t = 0 4 compares

a = [1,2,3,…,i] and t = 0 i compares


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Worst-Case Comparison CountWorst-Case Comparison Countfor (int i = 1; i < n; i++) for (j = i - 1; j >= 0 && t <

a[j]; j--) a[j + 1] = a[j];

total compares = 1 + 2 + 3 + … + (n-1)

= (n-1)n/2

= O(n2)

n

(i-1)i=2

T(n) =


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Average-Case Comparison Average-Case Comparison CountCount

for (int i = 1; i < n; i++)

for (j = i - 1; j >= 0 && t < a[j]; j--)

a[j + 1] = a[j];

n

i=2

T =i-1

2

= O(n2)


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4313

8131

92

57

65

75

260

4313

8131

92

57

65

75

260

650

3113

26

5743

92 75

81

Select pivot

Partition

Analysis of Quick Sort


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MainMainQuick SortQuick Sort

RoutineRoutine private static void quicksort( Comparable [ ] a, int left, int right ) {/* 1*/ if( left + CUTOFF <= right ) {/* 2*/ Comparable pivot = median3( a, left, right ); // Begin partitioning/* 3*/ int i = left, j = right - 1;/* 4*/ for( ; ; ) {/* 5*/ while( a[ ++i ].compareTo( pivot ) < 0 ) { }/* 6*/ while( a[ --j ].compareTo( pivot ) > 0 ) { }/* 7*/ if( i < j )/* 8*/ swapReferences( a, i, j ); else/* 9*/ break; }/*10*/ swapReferences( a, i, right - 1 ); // Restore pivot/*11*/ quicksort( a, left, i - 1 ); // Sort small elements/*12*/ quicksort( a, i + 1, right ); // Sort large elements } else // Do an insertion sort on the subarray/*13*/ insertionSort( a, left, right ); }


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Worst-Case AnalysisWorst-Case Analysisเวลาที่��ใช้ในการ run quick sort เที่�าก�บเวลาที่��ใช้ในการที่�า recursive call 2

คร��ง + linear time ที่��ใช้ในการเล�อก pivot ซึ่��งที่�าให้ basic quick sort relation

เที่�าก�บT(n) = T(i) + T(n-i-1) + cnในกรณี� Worst- case เช้�น การที่�� pivot มี�ค�านอยที่��สุ�ดเสุมีอ เวลาที่��

ใช้ในการที่�า recursion ค�อT(n) = T(n-1) + cn n>1T(n-1)= T(n-2)+c(n-1)T(n-2)= T(n-3)+c(n-2)

… T(2) = T(1)+c(2)

รวมีเวลาที่��งห้มีดT(n) = T(1) + c

n

i=2i = O(n2)


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The pivot is in the middle; T(n) = 2 T(n/2) + cn

Divide both sides by n;

Add all equations;

BestBest-Case Analysis-Case Analysis

T(n/2)

n/2

T(n)

n= + c

T(2)

2

T(1)

1= + c

T(n/4)

n/4

T(n/2)

n/2= + c

T(n/4)

n/4

T(n/8)

n/8= + c

…

T(n)

n

T(1)

1= + c log n

T(n) = c n logn + n = O(n log n)


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AverageAverage-Case Analysis (1/4)-Case Analysis (1/4)

2

N

N -1

j=0

T( j ) + cNT(N) =

NT(N) =

N -1

j=0

T( j ) + cN22

(N-1) T(N-1) = 2 + c(N – 1)2T( j )

N -2

j=0

Average time of T(i) and T(N-i-1) is 1

N

N -1

j=0

T( j )

Total time; T(N) = T(i) + T(N-i-1) + c N …………..(1)

Therefore

…………..(2)

…………..(3)

…………..(4)

…………..(5)


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AverageAverage-Case Analysis-Case Analysis (2/4)(2/4)

…………..(6)NT(N) – (N-1) T(N-1) = 2T(N-1) +2cN - c(5) – (4);

(7) divides by N(N+1);T(N)

N+1

T(N-1)

N

2c

N+1= + …………..(8)

Rearrange terms in equation and ignore c on the right-hand side;

NT(N) = (N+1) T(N-1) +2cN …………..(7)


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AverageAverage-Case Analysis-Case Analysis (3/4)(3/4)T(N)

N+1

T(N-1)

N

2c

N+1= +

T(N-2)

N-1

T(N-3)

N-2

2c

N-1= +

T(N-1)

N

T(N-2)

N-1

2c

N= +

…………..(8)

…………..(9)

…………..(10)...

T(2)

3

T(1)

2

2c

3= + …………..(11)

Sun equations (8) to (11); …………..(12)N +1

i=3

T(N)

N+1

T(1)

22c= +


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AverageAverage-Case Analysis-Case Analysis (4/4)(4/4)

N +1

i=3

T(N)

N+1

T(1)

22c= + …………..(12)

Sum in equation (12) ia approximately logC(N+1)+ - 3/2,

which is Euler’s constant 0.577

T(N) = O(Nlog N)

…………..(13)

and

T(N)

N+1= O(log N)therefore

…………..(14)

In summary, time complexity of Quick sort algorithm for Average-Case is

T(n) = O(n log n)


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CSE 221/ICT221 Analysis and Design of Algorithms Lecture 05: Analysis of time Complexity of Sorting...

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