What code coverage does and does not tell you

What it is

A coverage tool records which statements, and optionally which branches, ran while the tests executed, and reports the fraction per file and overall. Coverage.py, for example, supports statement and branch measurement and can list the lines that never ran.

Why it matters

Uncovered lines are a certain gap: no test would notice if they were deleted. Covered lines are not a certain success: a test may execute a line and assert nothing about its effect. Coverage therefore bounds test quality from one side only.

How to apply

• Read the uncovered lines, not the percentage; ask for each whether it is dead code, a missing test or acceptable.
• Enable branch coverage; a fully covered if with an untested else hides a real gap.
• Fail the build only on a coverage decrease for changed files, which pushes new code to be tested without forcing tests onto legacy code all at once.
• Combine with mutation testing or deliberate fault injection when you need evidence that tests would notice a change.

Pitfalls

A coverage target invites tests that execute code without asserting. Generated code and trivial accessors inflate the number. Coverage of integration tests is often high while the checks are shallow.