Advanced Debugging and Root Cause Analysis Questions

Systematic approaches to complex debugging scenarios: intermittent failures, race conditions, environment-dependent issues, infrastructure problems. Using logs, metrics, and instrumentation effectively. Differentiating between automation issues, environment issues, and application defects. Experience with advanced debugging tools and techniques.

EasyTechnical

23 practiced

Explain how a core dump (core file) and a stack trace help debug a crash. Describe practical steps to obtain a core dump on Linux for a crashed process inside a container, and how to map addresses to function names when binaries are stripped or optimized.

EasyTechnical

22 practiced

Explain the difference between Heisenbugs, Bohr bugs, and Mandelbugs in software systems. For each category provide a one-sentence concrete example, explain why it is (or isn't) reproducible, and list two debugging techniques you would try first when encountering an intermittent Heisenbug.

HardTechnical

26 practiced

Implement in Python a function that, given per-service event logs containing local timestamps and message send/receive events, reconstructs vector clocks to produce a consistent partial order. Input: list of events like {"service":"A","type":"send|receive|local","msg_id":opt,"local_ts":int}. Output: events annotated with vector clocks (dicts). Handle missing receives gracefully.

MediumSystem Design

28 practiced

Design an instrumentation plan for a new high-throughput microservice to make intermittent race conditions and request failures debuggable. Specify which metrics, logs, spans, sampling rates, cardinality limits, and how to expose on-demand deeper traces without imposing high production overhead.

EasyTechnical

23 practiced

What is fuzz testing (fuzzing)? Describe when you would apply fuzz testing in the development lifecycle, the types of bugs it commonly finds (e.g., memory corruption, panics), and give one concrete plan to integrate fuzzing for a file parser into CI.

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