Engineering Effectiveness
Testing & CI Modernization
A unified pytest-based test strategy that made a legacy computer-vision codebase safer to change.
Professional case studyProblem
The core service had fragmented test structures, limited automation, and only 10% coverage. Engineers had little confidence that changes to tracking, calibration, or configuration behavior would remain isolated.
Action
Replaced the legacy structure with a unified pytest-based approach, added integration coverage around critical workflows, and wired the suite into CI. Introduced conventions that made new tests easier to add and failures easier to interpret.
Outcome
Increased automated test coverage from 10% to 34% and created a stronger release signal for changes across the core Python platform.
Engineering takeaways
Reusable patterns from the work.
These notes focus on the judgment, tradeoffs, and working patterns behind the result.
- Focused coverage on risky behavior and integration boundaries, not a vanity percentage.
- Reduced the cost of adding tests by simplifying fixtures and conventions.
- Made verification part of the normal engineering workflow.
Stack