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Dsa – data structure and algorithms sorting | PPTX
Data Structure and
Algorithms-Sorting
Algorithms
Prepared By,
S.Sajini
AP/CSE
Sorting
• A sorting algorithm is an algorithm used to generate the
ordered list in a certain order.
• Sorting is defined as ordering of given data based on
different sorting technique
Unsorted list
Sorted list
Sorting Techniques
✔
Bubble sort
✔ Insertion sort
✔ Select sort
✔ Quick sort
✔ Merge sort
✔ Radix sort
Bubble Sort
✔
Bubble sort, is referred as sinking sort it is the simple sorting algorithm.
✔
Swapping with adjustment element in the list. Until no further swapping is
needed which denoted all the elements as sorted in the list
✔
The sorting order is small element to largest number like the bubble in the
given image
Algorithm
procedure bubbleSort( A : list of sortable items ) defined as:
do
swapped := false
for each i in 0 to length( A ) - 1 do:
if A[ i ] > A[ i + 1 ] then
swap( A[ i ], A[ i + 1 ] )
swapped := true
end if
end for
while swapped
end procedure
Time Complexities
Cases Big – O
Best O ( n )
Average O ( n2 )
Worst O ( n2 )
Insertion Sort
All the data items arranged in one at a time
using Insertion sort algorithm
Algorithm
insertionSort(array A)
for i = 1 to length[A]-1 do
begin
value = A[i]
j = i-1
while j >= 0 and A[j] > value do
begin
swap( A[j + 1], A[j] )
j = j-1
end
A[j+1] = value
end
Time Complexities
Cases Big – O
Best O ( n )
Average O ( n2 )
Worst O ( n2 )
Selection Sort
Selection sort worked based comparison
between the element
Algorithm
for i = 1:n,
k = i
for j = i+1:n, if a[j] < a[k], k = j
→ invariant: a[k] smallest of a[i..n]
swap a[i,k]
→ invariant: a[1..i] in final position
end
Time Complexities
Cases Big – O
Best O ( n2 )
Average O ( n2 )
Worst O ( n2 )
Quick Sort
• Element is picked is knows as pivot element .
partitions the given array based on pivot
element
There are many different versions of quickSort
that pick pivot in different ways.
1.Always pick first element as pivot.
2.Always pick last element as pivot (implemented
below)
3.Pick a random element as pivot.
4.Pick median as pivot.
Algorithm
function partition(array, left, right, pivotIndex)
pivotValue := array[pivotIndex]
swap array[pivotIndex] and array[right] // Move pivot to
end storeIndex := left
for i fromleft to right ? 1
if array[i] ? pivotValue
swap array[i] and array[storeIndex]
storeIndex := storeIndex + 1
swap array[storeIndex] and array[right] // Move pivot to its final
place return storeIndex
Algorithm
procedure quicksort(array, left, right)
if right > left
select a pivot index (e.g. pivotIndex := left)
pivotNewIndex := partition(array, left, right,
pivotIndex) quicksort(array, left, pivotNewIndex - 1)
quicksort(array, pivotNewIndex + 1, right)
• Quicksort(A[0….n-1],low,high)
• {
• If(low<high)
• {
• Mpartition(A[low….high])
• Quicksort(A[low….mid-1])
• Quicksort(A[])
• }
Partition(A[low…high]
Pivot
i
J
while(i<=j) do
{
while() do
while()
If(i<=j)then
Swap()
}
Swap()//when I crosses j
return j
Time complexity
• T(n)=T(n/2)+T(n/2)+f(n)
Time Complexities
Cases Big – O
Best O (n log n )
Average O (n log n )
Worst O ( n2 )
Merge Sort
“MergeSort is based on Divide and Conquer algorithm.
It divides given input array in to two halves, calls
itself for the two halves and then merges the two
sorted halves.”
Algorithm
function mergesort(m)
var list left, right, result
if length(m) ? 1
return m
var middle = length(m) / 2
for each x in m up to middle
add x to left
for each x in m after middle
add x to right
left = mergesort(left)
right = mergesort(right)
result = merge(left, right)
return result
Algorithm
function merge(left,right)
var list result
while length(left) > 0 and length(right) >
0 if first(left) ? first(right)
append first(left) to
result left = rest(left)
else
append first(right) to
result right = rest(right)
end while
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
Example
Time Complexities
Cases Big – O
Best O (n log n )
Average O (n log n )
Worst O (n log n )
Radix Sort
“Radix sort is a non-comparative integer sorting
algorithm that sorts data with integer keys by
grouping keys by the individual digits which
share the same significant position and value”
Algorithm
RADIX_SORT (A, d)
for i ← 1 to d do
use a stable sort to sort A on digit i
// counting sort will do the job
Time Complexities
Cases Big – O
Worst case time
complexity
O (n*k )
Worst Case space
complexity
O (n + k )
Example
Following example shows how Radix sort operates on seven 3-digits number.
Input 1st pass 2nd pass 3rd pass
329 720 720 329
457 355 329 355
657 436 436 436
839 457 839 457
436 657 355 657
720 329 457 720
355 839 657 839

Dsa – data structure and algorithms sorting

  • 1.
  • 2.
    Sorting • A sortingalgorithm is an algorithm used to generate the ordered list in a certain order. • Sorting is defined as ordering of given data based on different sorting technique Unsorted list Sorted list
  • 3.
    Sorting Techniques ✔ Bubble sort ✔Insertion sort ✔ Select sort ✔ Quick sort ✔ Merge sort ✔ Radix sort
  • 4.
    Bubble Sort ✔ Bubble sort,is referred as sinking sort it is the simple sorting algorithm. ✔ Swapping with adjustment element in the list. Until no further swapping is needed which denoted all the elements as sorted in the list ✔ The sorting order is small element to largest number like the bubble in the given image
  • 5.
    Algorithm procedure bubbleSort( A: list of sortable items ) defined as: do swapped := false for each i in 0 to length( A ) - 1 do: if A[ i ] > A[ i + 1 ] then swap( A[ i ], A[ i + 1 ] ) swapped := true end if end for while swapped end procedure
  • 10.
    Time Complexities Cases Big– O Best O ( n ) Average O ( n2 ) Worst O ( n2 )
  • 11.
    Insertion Sort All thedata items arranged in one at a time using Insertion sort algorithm
  • 13.
    Algorithm insertionSort(array A) for i= 1 to length[A]-1 do begin value = A[i] j = i-1 while j >= 0 and A[j] > value do begin swap( A[j + 1], A[j] ) j = j-1 end A[j+1] = value end
  • 15.
    Time Complexities Cases Big– O Best O ( n ) Average O ( n2 ) Worst O ( n2 )
  • 16.
    Selection Sort Selection sortworked based comparison between the element
  • 17.
    Algorithm for i =1:n, k = i for j = i+1:n, if a[j] < a[k], k = j → invariant: a[k] smallest of a[i..n] swap a[i,k] → invariant: a[1..i] in final position end
  • 20.
    Time Complexities Cases Big– O Best O ( n2 ) Average O ( n2 ) Worst O ( n2 )
  • 21.
    Quick Sort • Elementis picked is knows as pivot element . partitions the given array based on pivot element There are many different versions of quickSort that pick pivot in different ways. 1.Always pick first element as pivot. 2.Always pick last element as pivot (implemented below) 3.Pick a random element as pivot. 4.Pick median as pivot.
  • 22.
    Algorithm function partition(array, left,right, pivotIndex) pivotValue := array[pivotIndex] swap array[pivotIndex] and array[right] // Move pivot to end storeIndex := left for i fromleft to right ? 1 if array[i] ? pivotValue swap array[i] and array[storeIndex] storeIndex := storeIndex + 1 swap array[storeIndex] and array[right] // Move pivot to its final place return storeIndex
  • 23.
    Algorithm procedure quicksort(array, left,right) if right > left select a pivot index (e.g. pivotIndex := left) pivotNewIndex := partition(array, left, right, pivotIndex) quicksort(array, left, pivotNewIndex - 1) quicksort(array, pivotNewIndex + 1, right)
  • 25.
    • Quicksort(A[0….n-1],low,high) • { •If(low<high) • { • Mpartition(A[low….high]) • Quicksort(A[low….mid-1]) • Quicksort(A[]) • }
  • 26.
  • 27.
  • 28.
    Time Complexities Cases Big– O Best O (n log n ) Average O (n log n ) Worst O ( n2 )
  • 29.
    Merge Sort “MergeSort isbased on Divide and Conquer algorithm. It divides given input array in to two halves, calls itself for the two halves and then merges the two sorted halves.”
  • 30.
    Algorithm function mergesort(m) var listleft, right, result if length(m) ? 1 return m var middle = length(m) / 2 for each x in m up to middle add x to left for each x in m after middle add x to right left = mergesort(left) right = mergesort(right) result = merge(left, right) return result
  • 31.
    Algorithm function merge(left,right) var listresult while length(left) > 0 and length(right) > 0 if first(left) ? first(right) append first(left) to result left = rest(left) else append first(right) to result right = rest(right) end while if length(left) > 0 append rest(left) to result if length(right) > 0 append rest(right) to result return result
  • 32.
  • 33.
    Time Complexities Cases Big– O Best O (n log n ) Average O (n log n ) Worst O (n log n )
  • 34.
    Radix Sort “Radix sortis a non-comparative integer sorting algorithm that sorts data with integer keys by grouping keys by the individual digits which share the same significant position and value”
  • 35.
    Algorithm RADIX_SORT (A, d) fori ← 1 to d do use a stable sort to sort A on digit i // counting sort will do the job
  • 36.
    Time Complexities Cases Big– O Worst case time complexity O (n*k ) Worst Case space complexity O (n + k )
  • 37.
    Example Following example showshow Radix sort operates on seven 3-digits number. Input 1st pass 2nd pass 3rd pass 329 720 720 329 457 355 329 355 657 436 436 436 839 457 839 457 436 657 355 657 720 329 457 720 355 839 657 839