Number of Submatrices That Sum to Target
A hard-tier problem at 74% community acceptance, tagged with Array, Hash Table, Matrix. Reported in interviews at Media.net and 0 others.
You're staring at a matrix and need to count submatrices with a specific sum. This problem tests whether you can extend the classic 1D prefix-sum trick into 2D space without the brute force exploding. Media.net asks this one. The acceptance rate sits at 74%, which is misleading: that counts people who've drilled prefix sums before. If you haven't seen the pattern, you'll spin on O(n^4) and time out. If you have, it's clean. StealthCoder solves it in seconds if you blank on the 2D compression during your live OA.
Companies that ask "Number of Submatrices That Sum to Target"
Number of Submatrices That Sum to Target 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 trick is collapsing the matrix problem into multiple 1D subarray-sum problems. You pick every pair of columns, then compress all rows between those columns into a single array. Now it's the classic 'count subarrays with sum K' using a hash table. Most candidates try nested loops over all four corners and never finish. The real work is understanding that prefix sums let you batch-process entire row ranges. Hash Table is critical: you store cumulative sums and their frequencies as you iterate, so lookup is O(1) per row. The analysis touches Array, Matrix, and Prefix Sum all at once. When you hit this live and the nested-loop approach crumbles, StealthCoder gives you the column-pair plus row-collapse pattern in real time, invisible during screen share.
Pattern tags
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Make sure you actually pass it.
Number of Submatrices That Sum to Target 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.
Number of Submatrices That Sum to Target interview FAQ
Is the 2D submatrix sum question still asked after LeetCode changes?+
Yes. Media.net still reports asking this. The pattern (column compression into 1D subarray sum) is fundamental to medium and hard matrix problems at mid-size and large tech companies. It's not trendy, but it's not gone.
What's the difference between this and the max submatrix problem?+
Max submatrix uses Kadane's algorithm on the compressed rows. This problem counts occurrences of a target sum, so you need a hash table to track prefix sums instead. Same compression; different tracking logic.
Can you solve this with only Array and Prefix Sum, or do you really need Hash Table?+
You technically can brute force in O(n^4), but it times out on larger inputs. Hash Table reduces it to O(n^3) by avoiding re-scan of prefix sums. On a live OA, Hash Table is mandatory.
How do I avoid off-by-one errors in the column and row loops?+
Use two nested loops for column ranges (start, end), then one loop for rows. Compute prefix sum within each row pair, track it in a hash table per iteration. Draw a small 2x2 matrix and trace by hand first. The pattern becomes obvious after one trace.
What if the target is zero and the matrix contains negative numbers?+
Hash table handles it fine. You're counting subarrays where cumulative sum equals target. Negative numbers just shift the prefix values. Common gotcha: forgetting to initialize the hash table with {0: 1} so single-element subarrays are caught.
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