Python 3.8 (Coding): Longest Common Prefix Test

The goal of the problem is to find the longest common prefix string amongst an array of strings.

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  • English

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2 Skills measured

  • Sorting
  • Trie

Test Type

Coding Test

Duration

20 mins

Level

Beginner

Questions

1

Use of Python 3.8 (Coding): Longest Common Prefix Test

The solution approach of problem is to finds the longest common prefix among a vector of strings. Initializes an empty string ans that will store the longest common prefix. The solution sorts the vector of strings v using sort from the funtion. Sorting the strings ensures that the first and last strings in the sorted vector will have the smallest and largest lexicographical order, respectively.

The function obtains the first string in the sorted vector using v[0] and the last string using v[n-1], where n is the size of the vector.

A for loop is used to iterate over the characters of the first and last strings up to the minimum length between them (min(first.size(), last.size())).

Inside the loop, the solution checks if the character at the current index i in the first string is not equal to the character at the same index in the last string. If they are not equal, it means the common prefix ends at this point, so the ans is returned as the result.

If the characters at the current index i are equal, the character is appended to the ans string.

After iterating through all the characters, the ans string contains the longest common prefix, so it is returned as the result.

Skills measured

Sorting skill in the Longest Common Prefix problem involves sorting a list of strings in order to find the common prefix among them. This skill is important as it helps in efficiently comparing the strings in the list and identifying the longest common prefix. By sorting the strings, we can easily compare the characters in each string and find the common prefix without having to iterate through all characters in every string. This results in a more optimized and faster solution to the problem. Sorting also helps in organizing the data and simplifying the comparison process.

The Trie data structure is crucial in solving the Longest Common Prefix problem efficiently. Tries allow us to store and search for strings in a way that optimizes for common prefixes. By organizing strings in a Trie, we can quickly identify the longest common prefix among a set of strings by traversing the Trie nodes. This helps reduce the time complexity of the algorithm, making it more efficient and scalable for large datasets. The Trie skill is essential for solving string-related problems and is a fundamental concept in data structures and algorithms.

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