Largest Local Values in a Matrix
A easy-tier problem at 88% community acceptance, tagged with Array, Matrix. Reported in interviews at OpenAI and 1 others.
Largest Local Values in a Matrix is straightforward, but it shows up in live assessments at places like OpenAI and TCS. The acceptance rate sits near 88 percent, which tells you most people who attempt it walk away with a solve. The trick isn't hard, but the live coding environment and time pressure can wreck your rhythm if you haven't seen the exact pattern before. This is where StealthCoder steps in: if you blank on the grid traversal, it surfaces a working solution in seconds, invisible to the proctor, so you can move past it and keep your interview on track.
Companies that ask "Largest Local Values in a Matrix"
Largest Local Values in a Matrix is the kind of problem that decides whether you pass. StealthCoder reads the problem on screen and surfaces a working solution in under 2 seconds. Invisible to screen share. The proctor sees nothing. Built by an Amazon engineer who realized the OA tests how well you memorized 200 problems, not how well you code.
Get StealthCoderThe core pattern is straightforward once you see it. You iterate through a matrix and for each interior cell, you check if it's larger than all its neighbors. The pitfall most candidates hit is off-by-one errors in the loop bounds, or they try to over-engineer neighbor checking instead of just comparing a cell to its eight surrounding positions. The obvious brute-force approach works perfectly here: no DP trick, no mathematical insight needed, just clean nested loops and a comparison function. If you're weak on matrix navigation or haven't done index arithmetic recently, the live OA can feel messier than it is. StealthCoder handles the boilerplate and index logic so you don't trap yourself in boundary conditions.
Pattern tags
You know the problem.
Make sure you actually pass it.
Largest Local Values in a Matrix recycles across companies for a reason. It's easy-tier, and most candidates blank under the timer. StealthCoder is the hedge: an AI overlay invisible during screen share. It reads the problem and surfaces a working solution in under 2 seconds. Built by an Amazon engineer who realized the OA tests how well you memorized 200 problems, not how well you code. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Largest Local Values in a Matrix interview FAQ
Is this problem still asked at FAANG-tier companies?+
Yes. OpenAI and TCS both report asking it. The 88 percent acceptance rate means it's treated as a filter problem, not a differentiator. You're expected to solve it cleanly. If you can't, it's a red flag for coding fundamentals.
What's the main trick to avoid failing this live?+
Don't overthink neighbor checking. Write a simple loop over 8 directions or hardcode the eight surrounding cells. The real trap is loop bounds. Your inner iteration should start at 1 and end at rows-2 and cols-2 to stay interior. Off-by-one kills people here.
How does this problem relate to the Array and Matrix topics?+
It's pure 2D array traversal with a local comparison operation. You practice nested loops, index management, and reading matrix dimensions correctly. It's a foundation problem for any grid-based algorithms you'll see later.
Can you solve this with a one-liner or clever trick?+
Not really. The straightforward nested-loop approach is the intended solution. Any attempt to compress it tends to make it less readable and slower. Write clean, readable code and you'll pass.
What language should I use for this problem?+
The input doesn't specify. Use whatever language you're strongest in. This problem is language-agnostic. The logic is identical whether you code in Python, Java, or C++. Pick the one where you write loops fastest.
Want the actual problem statement? View "Largest Local Values in a Matrix" on LeetCode →