Test Planning

<objective> Create actionable test plans for sprints and releases. A test plan answers four questions: what to test, how deeply, who does it, and when it must be done. The output is a living document that tracks progress, not a bureaucratic artifact filed and forgotten. A plan that schedules 100% of available time fails the moment the first bug is found — buffer and prioritization are what make it survive contact with reality. </objective>

Quick Route

Discovery Questions

Before writing a test plan, gather context. Check .agents/qa-project-context.md first -- if it exists, use it as the foundation and skip questions already answered there.

Scope

• What is the scope? (single sprint, release, hotfix, feature)
• Which features are new vs. changed vs. unchanged?
• Which features are being released for the first time?
• Are there infrastructure or dependency changes (database migrations, API version bumps, third-party provider switches)?
• Is there a requirements document, PRD, or set of user stories to map against?

Time and Resources

• What is the testing window? (days, hours available)
• Who is available for testing? (SDETs, manual testers, developers)
• Are there shared resources that could bottleneck? (staging environments, test accounts, devices)
• Is there a hard deadline that cannot move, or is the release date flexible?

Risk Context

• Which areas changed the most in this cycle?
• What broke in the last release or sprint?
• Are there known fragile areas or tech debt that increase risk?
• For risk-based prioritization methodology, see risk-based-testing.

Existing Coverage

• What automated tests already exist for the in-scope features?
• What is the current pass rate of the automated suite?
• Are there known gaps in automation that require manual testing?
• When was the last exploratory testing session on these features?

Core Principles

1. Coverage-Driven: Map Every Requirement to at Least One Test

A test plan without traceability to requirements is a guess. Every user story, acceptance criterion, or requirement must map to at least one test case. Gaps in this mapping are untested requirements -- the most dangerous kind of risk.

2. Time-Boxed: Plan Fits the Available Window

Testing expands to fill available time if unbounded. Set a time box for each activity and stick to it. When the window is too short, the prioritization matrix determines what gets cut -- not gut feeling.

3. Prioritized: Not Everything Gets Equal Depth

A payment flow change and a tooltip fix do not deserve equal effort. Use the risk x effort matrix to allocate depth: some features get full regression, others a smoke test, some nothing if low-risk and unchanged.

4. Buffered: Leave Room for the Unexpected

Plans that schedule 100% of available time fail when bugs are found. Allocate only 70-80% of the testing window to planned work and explicitly reserve the remaining 20-30% for bug verification, re-testing, and unplanned investigation. If buffer is not a named line in the plan, you do not have one.

5. Visible: The Plan Is a Communication Tool

Developers need to know what gets tested to write testable code. Product managers need coverage visibility to make release decisions. Publish the plan where the team can see it.

6. Entry and Exit Criteria Are First-Class

The most-reused part of any plan is its gate. Make it explicit, not buried: entry = code-complete on staging + existing suite green + test data seeded; exit = every HIGH-risk area covered + no open P0/P1 + zero unexplained GAP rows in the coverage matrix. Everything else is detail around these two checkpoints.

Workflow

The six workflow steps each have a fill-in-the-blank scaffold. The decision prose stays here; the copy-paste templates (decomposition, coverage matrix, estimation worksheet, prioritization matrix, allocation table, schedule) live in references/workflow-templates.md.

Step 1: Feature Analysis and Decomposition

Break each in-scope feature into testable units. A "testable unit" is a specific behavior that can be verified with a clear pass/fail outcome. Walk every feature against these scenario categories so none gets skipped:

• Happy path — the primary success flow.
• Validation — required fields empty, format violations, boundary values.
• Error conditions — server 5xx, network timeout, rejected input.
• Edge cases — unicode, oversized payloads, unsupported formats.
• Concurrency / race conditions — two users edit the same record simultaneously, double-submit, retry-after-timeout. These hide the worst data-corruption bugs and are the category most often missed.
• Integration points — behavior across each boundary the feature crosses.

See references/workflow-templates.md for the decomposition template and a worked "User Profile Edit" example that exercises all six categories.

AI decomposition cross-check. When an agent decomposes features, have it immediately map its own scenarios back against the Step 2 coverage matrix. Any requirement with no scenario, or any scenario category above with no entry, is a decomposition gap the agent must surface before estimation — this is how you catch the agent's blind spots, not after CI does.

Step 2: Requirements-to-Test Coverage Mapping

Create a traceability matrix that maps every requirement to its test cases. See references/workflow-templates.md for the coverage matrix template.

Rules for the coverage matrix:

• Every requirement must appear in the matrix (target: 100% mapping)
• "GAP" status triggers a decision: write a test, accept the risk, or defer
• Automated tests get test IDs that link to the actual test file/function
• Manual tests reference the test case document or charter

Step 3: Effort Estimation

Estimate effort for each test type using historical data. If no historical data exists, use the reference estimates below and calibrate after the first sprint.

Estimation reference (per test case):

Write Time is authoring only. The "Setup & test data" row is the line planners most often omit — environment, fixtures, and mock configuration routinely run 20-40% of total effort, so budget it as a real line rather than discovering it mid-sprint.