What are the limitations of code coverage?
Assesses fundamental understanding of Software Testing & QA conventions, runtime behavior, and memory/performance considerations.
Hiring managers look for precision, avoidance of ambiguous jargon, and ability to explain trade-offs under real production conditions.
Code coverage measures which lines, branches or paths tests execute. It is useful for finding untested code and spotting dead code, and it prevents coverage from silently dropping.
Its limits are important. Coverage says nothing about whether assertions are meaningful. A test can execute every line and assert nothing. It does not prove all input partitions or boundary cases are covered, and high coverage can coexist with serious bugs, including security and concurrency defects. Chasing a number also encourages trivial tests that touch code without checking behaviour.
coverage: did we execute it?
tests: did we verify it?
Use coverage as a diagnostic and a trend, not a target. A common approach is a modest gate, for example 70 to 80 percent on changed code, plus review of whether critical paths and branches are genuinely tested. Branch and mutation coverage give stronger quality signals, and some code such as generated files should be excluded.
Candidate Response Strategy & Interview Tips
- Start with a concise one-sentence summary: Deliver a direct, confident answer first before expanding into nuances.
- Demonstrate real-world trade-offs: Discuss where this approach excels and when you would avoid it in production systems.
- Discuss complexity & edge cases: Proactively explain time/space complexity or boundary conditions (null values, scale limits).
- Prepare for interviewer follow-ups: Technical hiring panels frequently probe deeper into concurrency, backward compatibility, or alternative libraries.