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In this approach, you start with the first string as a reference and gradually compare it with each subsequent string in the array. The reference prefix is shortened until it matches the prefixes of all strings.
Time Complexity: O(S), where S is the sum of all characters in all strings.
Space Complexity: O(1), as we are using constant extra space.
1class Solution:
2 def longestCommonPrefix(self, strs):
3 if not strs:
4 return ""
5 prefix = strs[0]
6 for s in strs[1:]:
7 while not s.startswith(prefix):
8 prefix = prefix[:-1]
9 if not prefix:
10 return ""
11 return prefix
12
13if __name__ == "__main__":
14 sol = Solution()
15 print(sol.longestCommonPrefix(["flower", "flow", "flight"]))Python readily facilitates string manipulation. Using startswith, we efficiently trim the prefix for each string until a match is found or it becomes empty.
This approach involves dividing the array of strings into two halves, recursively finding the longest common prefix for each half, and merging the results. The merge step compares characters from the two strings to find the common prefix.
Time Complexity: O(S), where S is the sum of all characters in the strings.
Space Complexity: O(M*logN), where M is the length of the common prefix and N is the number of strings.
1
This C solution reduces the problem into finding the longest common prefix of smaller sections, leading to a combination of results using a helper function to merge prefixes by character comparison.