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The brute force approach involves iterating over each possible starting position of the needle in the haystack and checking if the substring from that position matches the needle.
Time Complexity: O((m-n+1)*n), where m is the length of haystack and n is the length of needle.
Space Complexity: O(1).
1def strStr(haystack: str, needle: str) -> int:
2 m, n = len(haystack), len(needle)
3 if n == 0:
4 return 0
5 for i in range(m - n + 1):
6 if haystack[i:i+n] == needle:
7 return i
8 return -1
9
10print(strStr("sadbutsad", "sad")) # Output: 0This Python solution uses slicing to compare parts of the haystack with the needle.
The KMP (Knuth-Morris-Pratt) algorithm is a more efficient string-searching algorithm. It preprocesses the needle to create a longest prefix-suffix (LPS) array, which is used to skip unnecessary comparisons while searching in the haystack.
Time Complexity: O(m + n), where m is the length of haystack and n is the length of needle.
Space Complexity: O(n), due to the LPS array.
1
The Python code implements the KMP algorithm, using an LPS array to efficiently find the needle in the haystack.