Minimum Number of Visited Cells in a Grid
A hard-tier problem at 23% community acceptance, tagged with Array, Dynamic Programming, Stack. Reported in interviews at Huawei and 2 others.
Minimum Number of Visited Cells in a Grid is a hard problem with a 22.7% acceptance rate, asked by Huawei, WorldQuant, and DE Shaw. You start at the top-left corner of a grid and can move right or down by a distance equal to the cell's value. The goal is to reach the bottom-right corner visiting the fewest cells possible. It's the kind of problem where the greedy or naive DP approach gets you partway, then hits a wall. If this lands in your live assessment and you blank on the pattern, StealthCoder solves it in seconds, invisible to the proctor.
Companies that ask "Minimum Number of Visited Cells in a Grid"
Minimum Number of Visited Cells in a Grid 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 engineer who got tired of watching his cohort grind for six months and still get filtered at the OA stage.
Get StealthCoderThe trap here is thinking greedy or standard DP will work. From each cell, you can jump 1 to k steps in one direction, which creates an enormous branching factor. Naive recursion or tabular DP times out. The actual solution uses a monotonic stack or priority queue to prune unreachable states in linear time per row or column. You track which cells are still "active" candidates and discard those that are suboptimal. It's a structural insight most candidates don't find without prior exposure. The topics span Array, DP, Stack, BFS, Union Find, Heap, and Matrix for a reason: multiple valid approaches exist, but only one scales. StealthCoder is the hedge when the pattern doesn't click during the live OA.
Pattern tags
You know the problem.
Make sure you actually pass it.
Minimum Number of Visited Cells in a Grid recycles across companies for a reason. It's hard-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 engineer who got tired of watching his cohort grind for six months and still get filtered at the OA stage. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Minimum Number of Visited Cells in a Grid interview FAQ
Is this really a hard problem or just underrated?+
Both. The 22.7% acceptance rate reflects genuine difficulty, not just ambiguous wording. The state space is large and naive solutions fail silently by timing out. It requires algorithmic insight beyond standard DP or BFS templates.
Do Huawei, WorldQuant, and DE Shaw actually ask this?+
Yes. All three have reportedly asked it in coding assessments. It's not ultra-common, but it appears in their rotation. If you see it, it's a real company signal, not a warm-up.
Which approach is fastest to code: monotonic stack or heap?+
Heap (priority queue) is more intuitive to implement but can be slower in practice. Monotonic stack is harder to reason about but more elegant. Under time pressure in a live OA, start with the approach you've drilled; both work if coded correctly.
What's the biggest pitfall candidates hit?+
Trying to solve it with pure DP or BFS without pruning. The branching factor explodes and execution times out. You must realize you need a data structure like a stack or heap to track only promising states, not all reachable ones.
How does this relate to the other topics listed?+
Array and Matrix are the input format. DP and BFS are false-start approaches. Union Find, Stack, and Heap are the actual tools. It's a problem where knowing what NOT to use is as important as knowing what to use.
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