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Edge Case Handling and Debugging Questions

Covers the systematic identification, analysis, and mitigation of edge cases and failures across code and user flows. Topics include methodically enumerating boundary conditions and unusual inputs such as empty inputs, single elements, large inputs, duplicates, negative numbers, integer overflow, circular structures, and null values; writing defensive code with input validation, null checks, and guard clauses; designing and handling error states including network timeouts, permission denials, and form validation failures; creating clear actionable error messages and informative empty states for users; methodical debugging techniques to trace logic errors, reproduce failing cases, and fix root causes; and testing strategies to validate robustness before submission. Also includes communicating edge case reasoning to interviewers and demonstrating a structured troubleshooting process.

MediumTechnical
47 practiced
Write a SQL-based monitoring query that runs daily and flags tables whose row counts changed by more than 20% compared to the 7-day moving average. Explain edge cases your query must handle (new tables, partitioned tables, very small counts) and how to avoid false positives.
HardTechnical
49 practiced
Design a process and set of SQL tests to detect and reconcile outliers where a metric's value is orders of magnitude larger than historical maxima (possible integer overflow or mis-aggregation). Include how to create synthetic regression tests and how to safely rollback or backfill affected aggregates.
MediumTechnical
49 practiced
Explain how you'd use dbt to add automated tests that catch edge cases for a metric 'net_revenue' including NULLs, negative refunds, integer overflow, and late-arriving refunds. Provide examples of dbt schema tests and a custom SQL test you might write.
HardTechnical
40 practiced
Weekly spikes in active users are flagged by your anomaly system. A deeper look shows out-of-order events from mobile SDKs are causing the spikes. Explain a plan to reproduce the issue, add guards to event processing to handle out-of-order events, reprocess affected windows, and ensure retention and cohort calculations remain correct after reprocessing.
HardSystem Design
35 practiced
Design a CI/CD pipeline for BI artifacts (SQL models, LookML/Power BI reports, and tests) that prevents regressions from edge cases. Include unit tests, integration tests, data snapshotting, synthetic data generation for edge cases (NULLs, duplicates, skew), deployment gates, and rollback strategies. Specify tools and trade-offs.

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