Number of Subarrays That Match a Pattern I
A medium-tier problem at 67% community acceptance, tagged with Array, Rolling Hash, String Matching. Reported in interviews at Autodesk and 3 others.
Number of Subarrays That Match a Pattern I hits your assessment when companies want to see if you can apply string-matching logic to array subproblems. Autodesk, Capital One, Visa, and Uber have all asked it. The 67% acceptance rate looks friendly until you're live, staring at a pattern-matching constraint you didn't rehearse. Most candidates nail the brute force but miss the rolling hash optimization that separates passable from strong. If this problem lands in your online assessment and you freeze on the pattern encoding, StealthCoder solves it invisibly in seconds.
Companies that ask "Number of Subarrays That Match a Pattern I"
Number of Subarrays That Match a Pattern I 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 used it to pass JPMorgan's OA and system design loop.
Get StealthCoderThe trap here is treating the subarray pattern as a raw search problem. You can't just compare arrays directly. The trick is converting each length-2 subarray into a comparable pattern token: encode each pair based on whether the second element is greater than, less than, or equal to the first. Once you have that pattern string, you're searching for pattern matches in a tokenized array. Rolling hash makes the substring search linear and avoids timeout. Most candidates either skip the encoding step entirely or implement it without hashing, turning an O(n) solution into O(n squared). When you're live and the pattern-matching layer feels unfamiliar, StealthCoder surfaces the hash-based approach before panic sets in.
Pattern tags
You know the problem.
Make sure you actually pass it.
Number of Subarrays That Match a Pattern I recycles across companies for a reason. It's medium-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 used it to pass JPMorgan's OA and system design loop. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Number of Subarrays That Match a Pattern I interview FAQ
Is this really Medium, or does it just feel hard?+
It's genuinely Medium. The 67% acceptance rate confirms it's passable without a PhD. The trick is understanding that you're doing string matching on encoded subarray patterns, not inventing a new algorithm. Once you see the pattern encoding, the rolling hash is boilerplate.
Do I need to know rolling hash before this problem?+
No. But rolling hash is the optimization that kills runtime. You can solve it with naive substring search first, then optimize if needed. Topics list confirms this problem teaches rolling hash as a pattern-matching tool, not prerequisite knowledge.
Why would Uber and Capital One ask this?+
They're testing whether you can solve a problem that mixes array iteration with string algorithms. It's not a favorite among all companies, but four major tech/finance firms have asked it. That's enough to justify rehearsal if you're interviewing with them.
What's the biggest gotcha candidates miss?+
Forgetting to encode the pattern. You can't search for 'greater than, less than, equal' relationships directly on numbers. You have to tokenize each adjacent pair into a character first, then apply string-matching logic.
How does this relate to other array and string problems?+
It's the intersection of rolling hash problems and array-subarray counting. If you know two-pointer subarrays and KMP or rolling hash, you've seen half the pieces. This problem just forces you to use both simultaneously.
Want the actual problem statement? View "Number of Subarrays That Match a Pattern I" on LeetCode →