How do you approach Minimum Window Substring?

Use a sliding window with two pointers.

What is the time complexity of Minimum Window Substring?

Time complexity: O(m + n). Space complexity: O(k) where k is the unique characters in t.

What are common mistakes on Minimum Window Substring?

Shrinking with if instead of while - one removal is often not enough to restore the invariant. Recomputing the window's contents each step, which puts back the O(n²) the pattern exists to remove. Never recording the answer for a window that ends at the last index.

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Minimum Window Substring

HardAlgorithms

Description

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 <= 10^5 - s and t consist of uppercase and lowercase English letters.

Minimum Window Substring: approach, complexity and pitfalls

A hard sliding window problem, graded against 6 test cases (3 of them hidden).

The pattern: Sliding Window

A moving window over a contiguous run, expanding and contracting to hold an invariant.

Reach for it when you see: "Longest/shortest contiguous subarray or substring satisfying X."

If you are stuck

Show the 3-step hint ladder

Use a sliding window with two pointers.
Expand the window until all characters in t are covered.
Then contract from the left to find the minimum window.

The optimal approach

Show the approach: Sliding Window

Use two pointers (left, right) to define a window. Expand right until all characters are covered, then shrink left while maintaining coverage.

Time: O(m + n)
Space: O(k) where k is the unique characters in t

The full reference solution in every supported language stays in the editor above - reveal it there once you have had a real attempt.

Common Sliding Window mistakes

These apply to the pattern as a whole, not just this problem.

Shrinking with `if` instead of `while` - one removal is often not enough to restore the invariant.
Recomputing the window's contents each step, which puts back the O(n²) the pattern exists to remove.
Never recording the answer for a window that ends at the last index.