Count Failed Executions
Reported by candidates from Amazon's online assessment. Pattern, common pitfall, and the honest play if you blank under the timer.
Amazon's April 2025 OA included a counting problem that looks simple on the surface but trips up candidates who skip the setup. You're given execution records and need to count how many fail a condition. The trap: misreading what "failed" means in context, or iterating inefficiently over nested structures. StealthCoder can catch you if you blank on the edge case that separates a pass from a fail.
Pattern and pitfall
This is a counting problem dressed as a straightforward iteration. Most candidates iterate through records and apply a boolean check per item, which works. The real complexity lives in how "failed" is defined in the problem statement. Amazon often hides the condition inside business logic rather than algorithm complexity. The common pitfall is assuming a simple count when the failure condition depends on state, time windows, or cross-record relationships. If you start coding before parsing exactly what makes an execution failed, you'll rewrite halfway through. The pattern is fundamentally counting, but the implementation hinges on understanding the business rule first. StealthCoder reads the full problem and flags the actual condition immediately, so you don't waste time guessing.
Drill it cold or hedge it with StealthCoder. Either way, don't walk into the OA hoping you remember the trick.
You can drill Count Failed Executions cold, or you can hedge it. StealthCoder runs invisibly during screen share and surfaces a working solution in under 2 seconds. The proctor sees the IDE. They don't see what's behind it. Made for the candidate who got the OA invite this morning and has 72 hours, not six months.
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Count Failed Executions FAQ
Is this a hash-table or array problem?+
Probably neither. It's a linear scan with a filter condition. Hash tables help if you need to count by category or correlate records, but a single-pass count usually solves it. Read the problem first to see if you need to group or just tally.
What's the trick Amazon usually hides here?+
The trick is the definition of 'failed'. It might not be a single boolean flag. Check if failure depends on latency, error code, retry count, time window, or a combination. Missing that detail costs you correctness, not just speed.
How do I prepare for this in 48 hours?+
Don't memorize solutions. Instead, read three similar problems and pay attention to how the problem statement defines the edge case or condition. Train yourself to extract the rule before coding. That's what matters here.
Will they ask for optimization after the basic solution?+
Unlikely. If the input is just a list of records, O(n) is usually the bar. But they might ask you to explain why you chose your data structure or whether you'd cache anything for repeated queries.
Is this still a common Amazon OA pattern in 2025?+
Yes. Amazon uses counting and filtering problems constantly because they interview across all levels. It separates candidates who read carefully from those who rush. Don't skip the problem statement.