← MathWorks Interview Insights

MathWorks·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Coded for MathWorks as a software engineer candidate and got a binary search problem dressed up in a security-themed wrapper. Pretty clean round overall, nothing too surprising.

Questions Asked (1)

Q1

Given an array of integers representing server security values and a number k, you can increment any value by 1 per operation. After exactly k operations, what is the maximum possible minimum value across the array?

Algorithms & Data Structures
Author's notes

Binary search on the answer.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Restate the problem to confirm understanding, then propose a binary search on the answer to find the maximum possible minimum value. Explain how to check if a candidate minimum is feasible by summing the required increments and comparing to k.

Pro tip: Mention that the answer is monotonic: if a minimum value m is achievable, any smaller value is also achievable, which justifies binary search. Also, note that the required increments can be computed efficiently by summing max(0, m - arr[i]) and that this sum can be large, so use 64-bit integers.

1. Clarify the problem

Confirm that you can increment any element by 1 per operation, exactly k operations must be used, and you want to maximize the minimum value in the array.

2. Identify monotonicity

Observe that if a minimum value m is achievable, then any value less than m is also achievable, enabling binary search on the answer.

3. Define feasibility check

For a candidate minimum m, compute the total increments needed as sum(max(0, m - arr[i])). If this sum ≤ k, then m is feasible.

4. Binary search bounds

Set low to the current minimum of the array and high to the current minimum plus k (or a safe upper bound). Perform binary search to find the largest feasible m.

5. Analyze complexity

The binary search runs in O(log(range)) iterations, each requiring O(n) time to compute the sum, resulting in O(n log(range)) time and O(1) extra space.

Key Points to Mention

  • Binary search on the answer (the minimum value)
  • Feasibility condition: total required increments ≤ k
  • Monotonic property: if m is feasible, all smaller values are feasible
  • Time complexity: O(n log(max_value + k))
  • Space complexity: O(1)
  • Use of 64-bit integers to avoid overflow when summing increments

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.