Longest Common Substring in DSA C - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the Longest Common Substring problem?

It is the problem of finding the longest string that appears as a continuous sequence in two given strings.

intermediate

How does the dynamic programming approach help solve the Longest Common Substring problem?

It builds a table where each cell represents the length of the longest common suffix of substrings ending at those positions, allowing us to find the longest common substring efficiently.

beginner

In the DP table for Longest Common Substring, what does a zero value in a cell mean?

It means the characters at the current positions in the two strings do not match, so no common substring ends there.

intermediate

What is the difference between Longest Common Substring and Longest Common Subsequence?

Longest Common Substring requires the matching characters to be continuous, while Longest Common Subsequence allows characters to be non-continuous but in order.

intermediate

What is the time complexity of the dynamic programming solution for Longest Common Substring?

The time complexity is O(m*n), where m and n are the lengths of the two input strings.

What does the DP table cell represent in the Longest Common Substring problem?

A Total number of matching characters so far

B Length of longest common prefix starting at those positions

C Length of longest common suffix ending at those positions

D Length of longest common subsequence so far

Each cell stores the length of the longest common suffix of substrings ending at the current positions in the two strings.

If characters at positions i and j in two strings do not match, what is the DP table value at dp[i][j]?

A 1

B 0

C Maximum of dp[i-1][j] and dp[i][j-1]

D dp[i-1][j-1] + 1

When characters do not match, the longest common suffix ending there is zero.

Which of the following is true about Longest Common Substring?

A It is the same as Longest Common Subsequence

B Characters must appear in order but can be non-continuous

C It finds the longest sequence ignoring order

D Characters must be continuous and appear in both strings

Longest Common Substring requires the substring to be continuous in both strings.

What is the space complexity of the standard DP solution for Longest Common Substring?

A O(m*n)

B O(m+n)

C O(1)

D O(max(m,n))

The DP table requires space proportional to the product of the lengths of the two strings.

Which technique is commonly used to solve the Longest Common Substring problem efficiently?

A Dynamic programming

B Greedy algorithm

C Divide and conquer

D Backtracking

Dynamic programming is used to build solutions for smaller substrings to solve the problem efficiently.

Explain how to use dynamic programming to find the Longest Common Substring between two strings.

Think about building solutions for smaller parts and combining them.

Describe the difference between Longest Common Substring and Longest Common Subsequence.

Focus on continuity and order of characters.