CSE 2123 Sortingweb.cse.ohio-state.edu/cse2123/sp2018/slides/Lecture11_Sorting.pdf · Selection...
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CSE 2123 Sorting
Jeremy Morris
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Problem Specification: Sorting
Given a list of values, put them in some kind of sorted order Need to know:
Which order? Increasing? Decreasing?
What does sorted order mean? integers, doubles – numerical order Strings, characters – alphabetical order Other objects? Depends on the object StudentGrade – By name? By grade?
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Problem Specification: Sorting
Note that values are stored in a list Need to use a data structure where order is
important Sets, Maps – no real concept of “ordering”
Additionally, these algorithms use a data structure where random access is important We will use arrays and ArrayLists for our examples
Random access Order is obvious
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Problem Specification: Sorting
For our lecture examples, we will make a few assumptions: Underlying collection type: simple array Items to be sorted: integers Order to be sorted: increasing numerical order
Note that all of the sorting algorithms are
extensible to other data types, collection types, and decreasing order Need only minor modifications
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Basic Sorting Tools
All sorting algorithms use these two basic ideas: Swap
Switch two values in the array tmp = a[i];
a[i] = a[j];
a[j] = tmp;
Compare Determine if two values are out of order
(a[i] < a[j])
(a[i] > a[j])
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Swap – Java Code
public static void swap(int [] a, int i, int j) {
int tmp = a[i];
a[i] = a[j];
a[j] = tmp;
}
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Comparing Sorting Algorithms
How can we tell if one algorithm (A) is better than another one (B)? Count how many swaps and comparisons it takes
A to sort a list Count how many swaps and comparisons it takes
B to sort a list Which one took fewer steps? To be accurate, we need to consider worst case
performance for both algorithms
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Bubble Sort
Algorithm: 1. Start from the left side of the list 2. Visit each adjacent pair of list items in left-to-right
order and swap if their values are out of order 3. Go back to step 1
A single execution of steps 1 and 2 is called a pass
When do we stop? Example: 6 8 7 5 4 3
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Bubble Sort – Sort Property
At pass i the following property holds: All entries from a[(n – i +1)] … a[n] are sorted,
where n is the index of the last element in the list
i = 2 n = 5 (index starts at zero!) Items between index (n-i+1)=4 and n=5 are sorted
6 5 4 3 7 8
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Sorted Unsorted
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Bubble Sort – Java Code
public static void bubbleSort(int [] a) {
for (int i=0; i<a.length-1; i++) { // For each pass
for (int j=0; j<a.length-1; j++) { // Traverse the list
if (a[j]>a[j+1]) { // if out of order
swap(a,j,j+1); // SWAP
// - see “Tools” slide
}
}
}
}
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Bubble Sort – Stopping Conditions
Can we stop this algorithm sooner? Think about our sort property The inner for loop only needs to traverse to the
end of the currently unsorted portion of the list We can stop our sort sooner on each pass
What if we make no swaps on the portion that is
currently supposed to be unsorted? Can we stop if we have a pass where we make no
swaps?
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Selection Sort
Algorithm: 1. Start from the first position in the list – call it i 2. Find the smallest value in the list starting from position i – call it
j 3. Swap the value at i with the value at j 4. Make i = i + 1 5. Go back to step 2
Here a pass is a single execution of steps 2-4 When do we stop? Example: 6 8 7 5 4 3
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Selection Sort – Sort Property
At pass i the following property holds: All entries from a[0] … a[i-1] are sorted, where n is
the index of the last element in the list
i = 2 Items between index 0 and 1 are sorted
3 4 7 5 8 6
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Sorted Unsorted
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Selection Sort – Java Code
public static void selectionSort(int [] a) {
for (int i=0; i<a.length-1; i++) { // For each pass
int minIndex = i;
for (int j=i+1; j<a.length; j++) { // Traverse the list
if (a[j] < a[minIndex]) { // if list item smaller
minIndex = j; // make it the minimum }
}
swap(a,i,minIndex); // SWAP current and min.
}
}
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Insertion Sort
Algorithm: 1. Start from the second position in the list – call it i 2. Find where in the list to the left of i to insert the value at i 3. Shift values to the right of the insertion point to insert this value 4. Make i = i + 1 5. Go back to step 2
Here a pass is a single execution of steps 2-4 We will perform n-1 passes for an array of size n Example: 6 8 7 5 4 3
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Insertion Sort – Sort Property
At pass i the following property holds: All entries from a[0] … a[i] are sorted
i = 3 Items between index 0 and 3 are sorted
5 6 7 8 4 3
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Sorted Unsorted
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Insertion Sort – Java Code
public static void insertionSort(int [] a) {
for (int i=1; i<a.length; i++) { // For each pass
int insert = a[i];
int scan = i;
while (scan>0 && array[scan-1]>insert) {
// Traverse the sorted side of the list to find the
// insertion point
a[scan]=a[scan-1];
scan=scan-1;
}
a[scan]=insert; // insert the unsorted value
}
}
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Quicksort
Algorithm: 1. Select a pivot element 2. Partition the list around the pivot element
1. Move elements less than the pivot to the left of the pivot (unsorted) 2. Move element greater than the pivot to the right of the pivot (unsorted)
3. Recursively call quicksort on the left and right lists
Example: 6 8 7 5 4 3
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Quicksort – Java Code
public static void quickSort(int [] a, int start, int end) {
if (start<end) { // general case
int pivot = partition(a, start, end);
// sort left sublist
quicksort(a,start,pivot-1);
// sort the right sublist
quicksort(a,pivot+1,end);
}
}
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Quicksort – Java Code (continued) public static int partition(int [] a, int start, int end) {
int pivot;
int endOfLeft;
int midIndex = (start+end)/2;
swap(a,start,midIndex);
pivot=a[start];
endOfLeft=start;
for (int i=start+1; i<=end; i++) {
if (a[i]<pivot) {
endOfLeft=endOfLeft+1;
swap(a,endOfLeft,i);
}
}
swap(a,start,endOfLeft);
return endOfLeft;
}
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Mergesort
Algorithm: 1. Partition the list at the middle to define two sublists 2. Recursively sort each sublist 3. Merge the two sorted sublists into one list
What is our base case? General case?
Example: 6 8 7 5 4 3
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Mergesort – Java Code
public static int[] mergeSort(int [] a, int start, int end) {
if (start<end) { // general case
int mid=(start+end)/2;
int[] left = mergeSort(a,start,mid);
int[] right = mergeSort(a,mid+1,end);
return merge(left, right);
}
else {
int[] arr = new int[1];
arr[0] = a[end];
return arr;
}
}
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Merge Step
Simple case – compare both values
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mergeSort {6, 5}
mergeSort {6}
mergeSort {5}
{5, 6} merge {6} {5}
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Merge Step Large lists – traverse sublists and compare
values
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mergeSort {6, 2, 5, 1}
mergeSort {6, 2}
mergeSort {5,1}
{1,5}
merge {2,6} {1,5}
{2,6}
1 < 2 : {1}
2 < 5 : {1,2}
5 < 6 : {1,2, 5}
6 : {1,2, 5, 6}
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Merge Step
Think of it as combining two stacks of cards Remove lowest card shown on top and place it on
new stack
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A B A B A B A B A B A 2 1 2 3 6 3 6 4 6 5 6 6 3 6 4 7 4 7 5 7 7 7 4 7 5 8 5 8 8 8 8 5 8
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Merge Step
Think of it as combining two stacks of cards Remove lowest card shown on top and place it on
new stack
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A B A B A B A B A B A 2 1 2 3 6 3 6 4 6 5 6 6 3 6 4 7 4 7 5 7 7 7 4 7 5 8 5 8 8 8 8 5 8
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Merge Step
Think of it as combining two stacks of cards Remove lowest card shown on top and place it on
new stack
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A B A B A B A B A B A 2 1 2 3 6 3 6 4 6 5 6 6 3 6 4 7 4 7 5 7 7 7 4 7 5 8 5 8 8 8 8 5 8
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Merge Step
Think of it as combining two stacks of cards Remove lowest card shown on top and place it on
new stack
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A B A B A B A B A B A 2 1 2 3 6 3 6 4 6 5 6 6 3 6 4 7 4 7 5 7 7 7 4 7 5 8 5 8 8 8 8 5 8
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Merge Step
Think of it as combining two stacks of cards Remove lowest card shown on top and place it on
new stack
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A B A B A B A B A B A 2 1 2 3 6 3 6 4 6 5 6 6 3 6 4 7 4 7 5 7 7 7 4 7 5 8 5 8 8 8 8 5 8
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Merge Step
Think of it as combining two stacks of cards Remove lowest card shown on top and place it on
new stack
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A B A B A B A B A B A 2 1 2 3 6 3 6 4 6 5 6 6 3 6 4 7 4 7 5 7 7 7 4 7 5 8 5 8 8 8 8 5 8
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Mergesort – Java Code (Merge step) public static int[] merge(int [] left, int[] right) {
int lIndex=0;
int rIndex=0;
int newIndex=0;
int[] list = new int[left.length+right.length];
while (lIndex<left.length && rIndex<right.length) {
if (left[lIndex]<=right[rIndex]) {
list[newIndex]=left[lIndex];
lIndex=lIndex+1;
}
else {
list[newIndex]=right[rIndex];
rIndex=rIndex+1;
}
newIndex=newIndex+1;
}
while (lIndex<left.length) {
list[newIndex]=left[lIndex]; lIndex=lIndex+1; newIndex=newIndex+1;
}
while (rIndex<right.length) {
list[newIndex]=right[rindex]; rIndex=rIndex+1; newIndex=newIndex+1;
}
return list;
}
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