LeetCode #2038 — MEDIUM

Remove Colored Pieces if Both Neighbors are the Same Color

Move from brute-force thinking to an efficient approach using math strategy.

Solve on LeetCode
The Problem

Problem Statement

There are n pieces arranged in a line, and each piece is colored either by 'A' or by 'B'. You are given a string colors of length n where colors[i] is the color of the ith piece.

Alice and Bob are playing a game where they take alternating turns removing pieces from the line. In this game, Alice moves first.

  • Alice is only allowed to remove a piece colored 'A' if both its neighbors are also colored 'A'. She is not allowed to remove pieces that are colored 'B'.
  • Bob is only allowed to remove a piece colored 'B' if both its neighbors are also colored 'B'. He is not allowed to remove pieces that are colored 'A'.
  • Alice and Bob cannot remove pieces from the edge of the line.
  • If a player cannot make a move on their turn, that player loses and the other player wins.

Assuming Alice and Bob play optimally, return true if Alice wins, or return false if Bob wins.

Example 1:

Input: colors = "AAABABB"
Output: true
Explanation:
AAABABB -> AABABB
Alice moves first.
She removes the second 'A' from the left since that is the only 'A' whose neighbors are both 'A'.

Now it's Bob's turn.
Bob cannot make a move on his turn since there are no 'B's whose neighbors are both 'B'.
Thus, Alice wins, so return true.

Example 2:

Input: colors = "AA"
Output: false
Explanation:
Alice has her turn first.
There are only two 'A's and both are on the edge of the line, so she cannot move on her turn.
Thus, Bob wins, so return false.

Example 3:

Input: colors = "ABBBBBBBAAA"
Output: false
Explanation:
ABBBBBBBAAA -> ABBBBBBBAA
Alice moves first.
Her only option is to remove the second to last 'A' from the right.

ABBBBBBBAA -> ABBBBBBAA
Next is Bob's turn.
He has many options for which 'B' piece to remove. He can pick any.

On Alice's second turn, she has no more pieces that she can remove.
Thus, Bob wins, so return false.

Constraints:

  • 1 <= colors.length <= 105
  • colors consists of only the letters 'A' and 'B'
Patterns Used

Roadmap

  1. Brute Force Baseline
  2. Core Insight
  3. Algorithm Walkthrough
  4. Edge Cases
  5. Full Annotated Code
  6. Interactive Study Demo
  7. Complexity Analysis
Step 01

Brute Force Baseline

Problem summary: There are n pieces arranged in a line, and each piece is colored either by 'A' or by 'B'. You are given a string colors of length n where colors[i] is the color of the ith piece. Alice and Bob are playing a game where they take alternating turns removing pieces from the line. In this game, Alice moves first. Alice is only allowed to remove a piece colored 'A' if both its neighbors are also colored 'A'. She is not allowed to remove pieces that are colored 'B'. Bob is only allowed to remove a piece colored 'B' if both its neighbors are also colored 'B'. He is not allowed to remove pieces that are colored 'A'. Alice and Bob cannot remove pieces from the edge of the line. If a player cannot make a move on their turn, that player loses and the other player wins. Assuming Alice and Bob play optimally, return true if Alice wins, or return false if Bob wins.

Baseline thinking

Start with the most direct exhaustive search. That gives a correctness anchor before optimizing.

Pattern signal: Math · Greedy

Example 1

"AAABABB"

Example 2

"AA"

Example 3

"ABBBBBBBAAA"

Related Problems

  • Longest Subarray With Maximum Bitwise AND (longest-subarray-with-maximum-bitwise-and)
Step 02

Core Insight

What unlocks the optimal approach

  • Does the number of moves a player can make depend on what the other player does? No
  • How many moves can Alice make if colors == "AAAAAA"
  • If a group of n consecutive pieces has the same color, the player can take n - 2 of those pieces if n is greater than or equal to 3
Interview move: turn each hint into an invariant you can check after every iteration/recursion step.
Step 03

Algorithm Walkthrough

Iteration Checklist

  1. Define state (indices, window, stack, map, DP cell, or recursion frame).
  2. Apply one transition step and update the invariant.
  3. Record answer candidate when condition is met.
  4. Continue until all input is consumed.
Use the first example testcase as your mental trace to verify each transition.
Step 04

Edge Cases

Minimum Input
Single element / shortest valid input
Validate boundary behavior before entering the main loop or recursion.
Duplicates & Repeats
Repeated values / repeated states
Decide whether duplicates should be merged, skipped, or counted explicitly.
Extreme Constraints
Upper-end input sizes
Re-check complexity target against constraints to avoid time-limit issues.
Invalid / Corner Shape
Empty collections, zeros, or disconnected structures
Handle special-case structure before the core algorithm path.
Step 05

Full Annotated Code

Source-backed implementations are provided below for direct study and interview prep.

// Accepted solution for LeetCode #2038: Remove Colored Pieces if Both Neighbors are the Same Color
class Solution {
    public boolean winnerOfGame(String colors) {
        int n = colors.length();
        int a = 0, b = 0;
        for (int i = 0, j = 0; i < n; i = j) {
            while (j < n && colors.charAt(j) == colors.charAt(i)) {
                ++j;
            }
            int m = j - i - 2;
            if (m > 0) {
                if (colors.charAt(i) == 'A') {
                    a += m;
                } else {
                    b += m;
                }
            }
        }
        return a > b;
    }
}
Step 06

Interactive Study Demo

Use this to step through a reusable interview workflow for this problem.

Press Step or Run All to begin.
Step 07

Complexity Analysis

Time
O(n log n)
Space
O(1)

Approach Breakdown

EXHAUSTIVE
O(2ⁿ) time
O(n) space

Try every possible combination of choices. With n items each having two states (include/exclude), the search space is 2ⁿ. Evaluating each combination takes O(n), giving O(n × 2ⁿ). The recursion stack or subset storage uses O(n) space.

GREEDY
O(n log n) time
O(1) space

Greedy algorithms typically sort the input (O(n log n)) then make a single pass (O(n)). The sort dominates. If the input is already sorted or the greedy choice can be computed without sorting, time drops to O(n). Proving greedy correctness (exchange argument) is harder than the implementation.

Shortcut: Sort + single pass → O(n log n). If no sort needed → O(n). The hard part is proving it works.
Coach Notes

Common Mistakes

Review these before coding to avoid predictable interview regressions.

Overflow in intermediate arithmetic

Wrong move: Temporary multiplications exceed integer bounds.

Usually fails on: Large inputs wrap around unexpectedly.

Fix: Use wider types, modular arithmetic, or rearranged operations.

Using greedy without proof

Wrong move: Locally optimal choices may fail globally.

Usually fails on: Counterexamples appear on crafted input orderings.

Fix: Verify with exchange argument or monotonic objective before committing.