Finding the Users Active Minutes
A medium-tier problem at 80% community acceptance, tagged with Array, Hash Table. Reported in interviews at X and 0 others.
You're prepping for an OA at X and this problem sits in the medium tier with an 80% acceptance rate. That's not a trap problem, but it's exactly the kind that trips up candidates who haven't seen the pattern. You'll get an array of logs showing user activity, and you need to bucket those minutes into the right ranges or aggregation buckets. The trick isn't the difficulty, it's knowing which data structure to pick so you don't waste time on nested loops. If you blank on the bucketing logic mid-interview, StealthCoder solves it invisibly and gets you past it.
Companies that ask "Finding the Users Active Minutes"
Finding the Users Active Minutes 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. Made for the engineer who has done the work but might still blank with a webcam pointed at him.
Get StealthCoderThe core pattern here is aggregating activity data by user into discrete time buckets or ranges. You'll reach for a hash table to group logs by user ID, then iterate through to count or categorize minutes. Most candidates start with the right instinct (hash table) but overcomplicate the bucketing logic or forget to handle edge cases around minute boundaries. The algorithm itself is straightforward once you see it, but the implementation details around how minutes are binned or counted are where the gotchas hide. Array iteration plus hash table lookup is your foundation. If you hit this live and the bucketing rules aren't clicking immediately, StealthCoder reads the problem and surfaces a working solution in seconds, letting you move on without panic.
Pattern tags
You know the problem.
Make sure you actually pass it.
Finding the Users Active Minutes 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. Made for the engineer who has done the work but might still blank with a webcam pointed at him. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Finding the Users Active Minutes interview FAQ
How hard is this compared to typical medium OAs at X?+
The 80% acceptance rate says it's on the easier side of medium. It's not a greedy or dynamic programming trap. The real test is clean implementation and handling minute-range edge cases correctly. Most failures come from logic errors, not algorithmic blindness.
Should I use a hash table or a 2D array for bucketing?+
Hash table (map or dict) is the right choice here. It scales better if user IDs are sparse and lets you aggregate without pre-allocating. Array only works if you know the ID range upfront. Hash table is safer and cleaner.
What's the common mistake on minute ranges?+
Off-by-one errors in bucket boundaries. If a minute falls in the range 5-10, is it bucket 5 or bucket 10? Read the problem spec carefully. Test your boundaries on small examples before submitting.
Is this problem still asked at X?+
It's listed as recently asked at X. The problem type (activity aggregation) shows up across tech companies regularly. This is the kind of problem you should see coming in an OA for a data-heavy role.
How do I practice this without overthinking?+
Write a hash table solution, test it on 2-3 small examples by hand, then submit. Don't re-invent bucketing logic mid-interview. If you're stuck on the ranges, that's where StealthCoder becomes your safety net on the live OA.
Want the actual problem statement? View "Finding the Users Active Minutes" on LeetCode →