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[].
Algorithm
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.
C++ 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.
Python Programming – Longest Common Subsequence – Dynamic Programming – LCS problem has optimal substructure property as main problem can be solved.
JAVA programming – Given a sorted array and a number x, find the pair in array whose sum is closest to x – Searching and sorting – Given a sorted array and a number x, find a pair in array whose sum is closest to x.
C++ programming – Given a sorted array and a number x, find the pair in array whose sum is closest to x – Searching and sorting – Given a sorted array and a number x, find a pair in array whose sum is closest to x.
Java Programming – Longest Common Subsequence – Dynamic Programming – LCS problem has optimal substructure property as main problem can be solved .
C++ Programming – Longest Common Subsequence – Dynamic Programming – LCS problem has optimal substructure property as main problem can be solved.