Given two strings s1 and s2, return their longest common prefix
Example 1:
Input: s1 = "hello", s2 = "help" Output: "hel"
Example 2:
Input: s1 = "Andy", s2 = "Mircea" Output: ""
Example 3:
Input: s1 = "AlgoCademy", s2 = "Algo" Output: "Algo"
The core challenge of this problem is to find the longest common prefix between two given strings. This is a common problem in string processing and has applications in text editing, DNA sequencing, and more. A potential pitfall is assuming that the common prefix will always be non-empty, which is not the case as shown in Example 2.
To solve this problem, we can start by comparing characters of both strings one by one from the beginning until we find a mismatch or reach the end of one of the strings. This approach ensures that we only traverse the minimum length of the two strings, making it efficient.
A naive solution would involve nested loops to compare each character of the first string with each character of the second string. However, this is not optimal and has a time complexity of O(n*m), where n and m are the lengths of the two strings.
An optimized solution involves a single loop that runs until the end of the shorter string or until a mismatch is found. This approach has a time complexity of O(n), where n is the length of the shorter string.
def longest_common_prefix(s1, s2):
# Initialize the common prefix as an empty string
common_prefix = ""
# Find the minimum length of the two strings
min_length = min(len(s1), len(s2))
# Iterate through the characters up to the minimum length
for i in range(min_length):
# Compare characters at the same position
if s1[i] == s2[i]:
# Append the matching character to the common prefix
common_prefix += s1[i]
else:
# Break the loop if characters do not match
break
return common_prefix
# Test cases
print(longest_common_prefix("hello", "help")) # Output: "hel"
print(longest_common_prefix("Andy", "Mircea")) # Output: ""
print(longest_common_prefix("AlgoCademy", "Algo")) # Output: "Algo"
The time complexity of the optimized solution is O(n), where n is the length of the shorter string. The space complexity is O(1) as we are using a fixed amount of extra space.
Potential edge cases include:
Examples:
print(longest_common_prefix("", "")) # Output: ""
print(longest_common_prefix("abc", "")) # Output: ""
print(longest_common_prefix("abc", "def")) # Output: ""
print(longest_common_prefix("abc", "abc")) # Output: "abc"
To test the solution comprehensively, include a variety of test cases:
Using a testing framework like unittest
in Python can help automate and organize these tests.
When approaching such problems:
Understanding and solving the longest common prefix problem is essential for string processing tasks. By breaking down the problem and considering edge cases, you can develop efficient solutions. Practice and exploration of similar problems will further enhance your skills.