Why Quick Sort preferred for Arrays and Merge Sort for Linked Lists? – Searching and Sorting – Quick Sort in its general form is an in-place sort. whereas merge sort requires O(N) extra storage, N denoting the array size which may be quite expensive.
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Insertion Sort for Singly Linked List – Searching and sorting – We have discussed Insertion Sort for arrays.In this article linked list is also discussed.
Binary Insertion Sort – Searching and Sorting – We can use binary search to reduce the number of comparisons in normal insertion sort. Binary Insertion Sort find use binary search to find the proper location to insert the selected item at each iteration.
C++ Programming-Searching for Patterns Set 1 Naive Pattern Searching – Searching and Sorting – Given a text txt[0..n-1] and a pattern pat[0..m-1], write a function search(char pat[], char txt[]) that prints all occurrences of pat[] in txt[].
JAVA Program Count 1’s in a sorted binary array – Searching and Sorting – A simple solution is to linearly traverse the array. The time complexity of the simple solution is O(n). We can use Binary Search to find count in O(Logn) time.
C Programming-Searching for Patterns Set 1 Naive Pattern Searching – Searching and Sorting – Given a text txt[0..n-1] and a pattern pat[0..m-1], write a function search(char pat[], char txt[]) that prints all occurrences of pat[] in txt[].
Digital Signatures and Certificates – Digital Electronics – Process of converting electronic data into another form, called cipher text.
PYHTON Programming-Searching for Patterns Set 1 Naive Pattern Searching – Searching and Sorting – Given a text txt[0..n-1] and a pattern pat[0..m-1], write a function search(char pat[], char txt[]) that prints all occurrences of pat[] in txt[].
python programming Tarjan’s Algorithm to find Strongly Connected Components – Graph – A directed graph is strongly connected
PYTHON Program Count 1’s in a sorted binary array – Searching and Sorting – A simple solution is to linearly traverse the array. The time complexity of the simple solution is O(n). We can use Binary Search to find count in O(Logn) time.