Count Alternating Subarrays
A medium-tier problem at 56% community acceptance, tagged with Array, Math. Reported in interviews at Capital One and 0 others.
Count Alternating Subarrays is a medium-difficulty array problem that Capital One has asked recently. It's a pattern-matching problem disguised as a subarray counter. You'll see the straightforward brute-force approach fail on large inputs, and the trick isn't obvious from the problem statement alone. The acceptance rate sits around 56%, which means roughly half the candidates who attempt it either time out or miss the core insight. If this problem hits your live assessment and you blank on the pattern, StealthCoder solves it invisibly in seconds.
Companies that ask "Count Alternating Subarrays"
Count Alternating Subarrays 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 is treating this like a nested-loop subarray problem. Most candidates start counting valid subarrays one by one, which works for tiny inputs but hits time limits fast. The actual insight is mathematical: once you identify a contiguous region where elements alternate correctly, you don't count each subarray inside it individually. Instead, you use a formula based on the length of that alternating sequence. The problem falls under both Array and Math because the array scanning is trivial, but the counting formula is where the pattern lives. When you hit this live, you might waste 10 minutes on the brute force before realizing the math shortcut. StealthCoder surfaces the optimized approach immediately, so you avoid the timeout and move on.
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Count Alternating Subarrays 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 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.
Count Alternating Subarrays interview FAQ
Is Count Alternating Subarrays still asked by Capital One?+
Yes, Capital One is the reported company. It's a relatively niche problem in the broader LeetCode ecosystem, so if you see it in a Capital One assessment, you're looking at a company-specific problem. Prepare for it if you're interviewing there.
Why does the brute-force subarray approach fail?+
Brute force checks every possible subarray start and end point, which is O(n^2) or worse. For arrays larger than a few hundred elements, you'll time out. The problem requires recognizing that alternating regions can be counted using a length-based formula, reducing complexity to O(n).
What's the actual trick to this problem?+
Once you find a maximal alternating sequence of length k, the number of valid subarrays within it follows a math formula, not a loop. For a sequence of length k, the count is k * (k + 1) / 2 minus overlaps, or similar. The shift from 'count loops' to 'apply formula' is what most candidates miss.
How does Math topic fit an array problem?+
The Array part is the scan. The Math part is the counting formula you apply to each alternating region. You're not doing arithmetic on array elements, you're computing how many subarrays fit a pattern using combinatorial math.
What should I drill before my assessment?+
Practice identifying contiguous alternating sequences in arrays, then memorize the formula for counting subarrays in a sequence of length k. Brute-force one example to understand the problem, then learn the O(n) math approach before your assessment.
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