Leetflex Banned Accounts
A medium-tier problem at 62% community acceptance, tagged with Database. Reported in interviews at Audible and 0 others.
Audible asks this one. You're given activity logs for user accounts and need to identify which ones violated policy and when they should be banned. It's a database problem that looks straightforward until you realize the filtering logic is wrong or your join strategy tanks performance. The acceptance rate hovers around 62 percent, which means a lot of candidates are getting tripped up by either misunderstanding the ban logic or writing inefficient SQL. This is exactly the kind of problem where StealthCoder becomes your safety net if you blank on the optimal query structure during the live assessment.
Companies that ask "Leetflex Banned Accounts"
Leetflex Banned Accounts 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 realized the OA tests how well you memorized 200 problems, not how well you code.
Get StealthCoderThe core trick is figuring out what 'banned' means from the problem statement and then executing the query efficiently. Most candidates either misread the ban condition (applying it too broadly or too narrowly) or write a nested query that times out. The pattern usually involves filtering accounts by activity type or threshold, calculating a ban date, then joining back to exclude or flag them. Where people stumble is conflating the account ID with the transaction or activity record. You need to think in sets: which accounts meet the condition, from what date onward are they banned, which rows do I actually return. If you're writing a query that feels messy or you're unsure whether your join is correct, that's the moment StealthCoder surfaces a clean, tested solution in seconds during your assessment.
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Leetflex Banned Accounts 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 realized the OA tests how well you memorized 200 problems, not how well you code. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Leetflex Banned Accounts interview FAQ
Is this problem still asked at Audible?+
Yes. Audible has a confirmed history of asking this problem. It's a database-focused role staple, not a one-time question. If you're interviewing there, this pattern is worth understanding end-to-end.
What's the main trick I'm missing?+
Understanding the exact moment an account becomes banned and how that filters your result set. Most candidates write the ban logic but don't correctly join it back to identify or exclude the affected records. The secondary trick is avoiding expensive subqueries or Cartesian products.
Should I expect a performance constraint?+
Database problems at this level often care about query efficiency. If your solution works on small test cases but you suspect it won't scale, you're probably missing an index opportunity or using an expensive join. Rewrite to minimize nested queries.
How does this relate to real database work?+
This is exactly what data compliance teams do. You're auditing accounts, applying business rules retroactively, and reporting violations. The SQL skills here apply directly to fraud detection, policy enforcement, and data cleanup in production systems.
What SQL concepts do I need to nail?+
You need joins (likely LEFT JOIN or INNER JOIN depending on logic), window functions or GROUP BY for aggregation, date filtering, and possibly CASE logic to compute the ban date. Test your GROUP BY carefully to avoid duplicate rows.
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