Step 16: Dynamic Programming [Patterns and Problems]›DP on Strings
Longest common substring
HardFunction: longestCommonSubstring()
ASCI Mission Breakdown • Simple as Hell
"Master Longest common substring: Take `s` (string), execute an optimal dp on strings strategy, and return string with clean edge-case handling."
Real-World Metaphor:
Think of Longest common substring as an everyday real-world challenge: you receive input data, inspect its elements in sequence without making unnecessary duplicate passes, and transform the collection to reach the exact target without wasting computer memory.
Interactive Visual WalkthroughBINARY-TREE
Step 1 / 3
StatusInitialized
ModeScanning
Evaluating
1. Initialize State for Longest common substring
Load inputs and initialize algorithmic registers.
How to Think About This (Mental Model)
Unpack the problem parameters (`s` (string)) and clarify what is given vs what must be returned.
Identify the optimal data structure or pattern (e.g. pointers, hash map, or stack) to avoid redundant recalculations.
Walk through state transitions, handle edge cases (empty collections, single items, negative numbers), and return the verified result.
Given a string `s`, implement an optimal algorithmic solution for **Longest common substring**.
Your solution should aim for optimal time complexity and handle all edge cases such as empty strings and character frequencies.
Examples
Example 1
Input: s = "racecar"
Output: "racecar"
Example 2
Input: s = "hello"
Output: "olleh"
Constraints
1 <= s.length <= 10^5
s consists of lowercase English letters and printable characters.
Topic Tags:
Dynamic Programming [Patterns and Problems]DP on StringslongestCommonSubstring