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Test Strategy

A useful test strategy names what evidence is needed and why shallow coverage is not enough.

For bijux-proteomics-lab, the test story should show how planning intent, outcome capture, and durable records stay aligned under real operator pressure.

Strategy Model

flowchart TB
    workflow["planning and outcome workflow"]
    promotion["promotion and prerequisite tests"]
    records["repository and serialization proof"]
    operators["operator-facing scenarios"]
    release["release confidence"]

    workflow --> promotion
    promotion --> records
    records --> operators
    operators --> release

This page should show why lab tests are not generic workflow checks. They are there to prove that durable records and operator decisions still tell the same story after change.

Review Rules

  • favor planning, promotion, repository, and serialization proof over generic coverage claims
  • cover dependency and prerequisite cases that operators actually hit
  • treat persisted lab records as first-class quality surfaces

First Proof Check

  • packages/bijux-proteomics-lab/tests
  • src/bijux_proteomics_lab/planning.py and outcomes.py
  • src/bijux_proteomics_lab/repositories.py and serialization.py

Design Pressure

The easy mistake is to validate successful execution while leaving promotion history, prerequisite handling, or record meaning underexplained.