Engineering Effectiveness · Technical Leadership
Test Foundation & Modular Architecture
A unified pytest/CI foundation and a coordinated modular refactor that made a legacy computer-vision codebase safer to change.
Professional case studyProblem
The core service had fragmented tests, only 10% coverage, and no automated pull-request validation, so engineers had little confidence that changes stayed isolated. Core behavior had also grown across duplicated paths, making changes risky and obscuring the boundary around proprietary components needed for a patent application.
Action
Replaced the legacy tests with a unified pytest structure for unit and integration coverage and, because corporate security blocked GitHub Actions, built a Jenkins CI workflow on AWS EC2 to validate pull requests before approval. I then defined target module boundaries, sequenced the refactor into incremental changes, and mentored three engineers through it — removing duplicated logic and isolating proprietary components behind clearer interfaces while keeping the service operable.
Outcome
Increased automated test coverage from 10% to 34% with automated pull-request validation, and delivered a more modular core with a cleaner technical boundary for patent-related work.
How it was measured: Automated coverage reported by the pytest suite in CI, measured before and after the test-structure rebuild.
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.
- Used architecture as a coordination tool, sequencing the refactor to protect delivery.
- Translated testing and patent requirements into enforceable module boundaries.
Stack