Practice : Test Coverage Analysis

Purpose and Strategic Importance

Test Coverage Analysis is the practice of measuring how much of your codebase is exercised by automated tests. It helps teams identify untested code paths, improve confidence in code changes, and maintain quality across growing systems.

Used effectively, coverage analysis drives more meaningful testing - not just quantity, but targeted validation of risk areas. It supports better decision-making in test prioritisation and helps teams build safer, more maintainable software.

Description of the Practice

  • Coverage tools measure which lines, branches, or paths of code are executed during test runs.
  • Results are reported as percentages and visualised in reports or dashboards.
  • Coverage data is collected automatically during CI runs and reviewed in code reviews.
  • Analysis helps identify dead code, untested logic, or blind spots in high-risk areas.
  • Coverage thresholds can be enforced to maintain or improve test health over time.

How to Practise It (Playbook)

1. Getting Started

  • Integrate a coverage tool appropriate for your language (e.g. Istanbul, Jacoco, Coverage.py).
  • Run coverage checks during every CI build and publish reports for visibility.
  • Review coverage reports to identify critical gaps in logic or branches.
  • Focus on improving test quality, not just raising the percentage.

2. Scaling and Maturing

  • Set team-defined minimum thresholds based on code criticality.
  • Highlight risky areas with low coverage during planning and refactoring.
  • Pair coverage tools with mutation testing to assess test effectiveness.
  • Tag test gaps with TODOs or tech debt backlog items for prioritisation.
  • Automate fail conditions in pipelines when coverage falls below agreed standards.

3. Team Behaviours to Encourage

  • Treat coverage as a guide, not a goal - value meaningful tests over vanity metrics.
  • Discuss low-coverage areas during code reviews and planning sessions.
  • Use coverage insights to drive better architecture and decoupling.
  • Celebrate improvements in high-impact test coverage.

4. Watch Out For…

  • Chasing high coverage without meaningful assertions.
  • Blindly enforcing 100% coverage - not all code requires exhaustive testing.
  • Test suites that touch code but don’t validate outcomes.
  • Neglecting coverage of glue code, integrations, and edge cases.

5. Signals of Success

  • Teams understand what is and isn’t tested - and why.
  • Coverage reports are visible, reviewed, and used to guide improvements.
  • High-risk code paths are well-covered and regularly verified.
  • Test failures are meaningful, and regressions are caught early.
  • Software quality improves as testing strategy becomes more deliberate.