Minimum Window Substring

Minimum Window Substring is a Hard Data Structures and Algorithms interview problem you can solve, run and submit on Thita.ai. It belongs to the Sliding Window pattern, in the Variable Size (Condition-Based) subpattern.

Problem statement

Given two strings s and t of lengths m and n respectively, return the minimum window substring of s such that every character in t (including duplicates) is included in the window. If there is no such substring, return the empty string "".

The testcases will be generated such that the answer is unique.

Example 1:

Input: s = "ADOBECODEBANC", t = "ABC" Output: "BANC" Explanation: The minimum window substring "BANC" includes 'A', 'B', and 'C' from string t.

Example 2:

Input: s = "a", t = "a" Output: "a" Explanation: The entire string s is the minimum window.

Example 3:

Input: s = "a", t = "aa" Output: "" Explanation: Both 'a's from t must be included in the window. Since the largest window of s only has one 'a', return empty string.

Constraints:

- m == s.length

- n == t.length

- 1 <= m, n <= 105

- s and t consist of uppercase and lowercase English letters.

Follow up: Could you find an algorithm that runs in O(m + n) time?

Topics and companies

Topics: Hash Table, String, Sliding Window.

Reported in interviews at Adobe, Airbnb, Amazon, Apple, Bloomberg, ByteDance, Facebook, Goldman Sachs, Google, LinkedIn, Lyft, Microsoft and others.

How to practise Minimum Window Substring on Thita.ai

Starter code is provided in C, C#, C++, Go, Java, JavaScript and Python. Your solution runs against 5 test cases for this problem, with the AI coach available for a hint when you are stuck rather than a finished answer. The reference solution runs in O(n) time and O(k) space.

Open Minimum Window Substring in the code editor, or read the Minimum Window Substring editorial for a worked solution with its approach and complexity analysis.

Where Minimum Window Substring sits in the DSA pattern sheet

Problems related to Minimum Window Substring

Other problems that use the same Variable Size (Condition-Based) and Sliding Window techniques:

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