Maximal Square

Algorithms
Medium
Adobe
91.7K views

Given an $m \times n$ binary matrix, find the largest square containing only 1's and return its area. Use Dynamic Programming.

Why Interviewers Ask This

Adobe asks this problem to evaluate a candidate's ability to recognize overlapping subproblems and apply dynamic programming for optimization. They specifically test if you can transform a brute-force geometric check into an efficient O(mn) solution, demonstrating strong algorithmic thinking and spatial reasoning skills essential for their graphics and software engineering roles.

How to Answer This Question

1. Clarify the input constraints and edge cases immediately, such as empty matrices or all-zero grids. 2. Propose a brute-force approach first to show baseline understanding, then explicitly state its inefficiency (O(m^3)). 3. Introduce the DP state definition: dp[i][j] represents the side length of the largest square ending at position (i, j). 4. Derive the recurrence relation by explaining that a cell forms a larger square only if its top, left, and top-left neighbors are also part of squares. 5. Walk through a small matrix example on a virtual whiteboard to visualize how values propagate. 6. Conclude with time and space complexity analysis, suggesting space optimization to O(n) if asked.

Key Points to Cover

  • Demonstrating the transition from brute force to dynamic programming logic
  • Correctly identifying the recurrence relation involving min(top, left, top_left)
  • Handling boundary conditions and empty inputs gracefully
  • Clearly articulating O(mn) time and O(mn) space complexity
  • Using a concrete visual walkthrough to explain the state transitions

Sample Answer

To solve the Maximal Square problem efficiently, I would start by checking for edge cases like an empty matrix, returning zero immediately if found. A naive approach would check every possible square starting from each c…

Common Mistakes to Avoid

  • Failing to initialize the first row and column correctly in the DP table
  • Confusing the returned value as the side length instead of the calculated area
  • Attempting to use recursion without memoization, leading to Time Limit Exceeded errors
  • Neglecting to check if the current cell is '0' before applying the recurrence relation

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