Testing Strategy
Tests exist to let you change code fearlessly. A suite you don't trust, don't run, or that breaks on every refactor provides negative value. Optimize for bugs caught per minute of maintenance, not coverage percentage.
What to test — priority order (spend your budget top-down)
- Money and state-machine paths: anything computing totals, tax, discounts, stock, balances, status transitions. These get exhaustive unit tests including the ugly inputs (zero, negative, rounding boundaries, max values, illegal transitions).
- Authorization: for each protected route, at least one test proving the wrong principal is refused — wrong tenant's object (the IDOR test), insufficient role, no auth. These tests are cheap and catch breaches.
- The golden paths, end-to-end-ish: one integration test per core user journey (signup→login, create invoice→stock decrements→payment records). Through the real API surface against a real (containerized) database — this is where wiring bugs live.
- Regression pins: every production bug you fix gets a test that fails on the old code, forever. This is the highest-signal test category that exists; never skip it.
- Contract edges: validation rejects what it should; error envelope shape is stable; pagination boundaries.
Below the line (test only with a reason): getters, framework glue, UI cosmetics, third-party libraries' own behavior.
Which level — the honest trade
- Unit (pure logic, no I/O): milliseconds, pinpoint failures — put all calculation and decision logic here, which is an argument for extracting logic from I/O (see code-quality). If testing a function needs 5 mocks, the function's design is the finding.
- Integration (service + real DB): the default level for CRUD apps — most real bugs are query/transaction/constraint bugs that mocks hide. Use a real disposable database (Docker); an in-memory fake with different semantics tests a different app.
- E2E (browser/UI): few, only golden paths, because they're slow and flaky. They answer "is the product alive?", not "is the logic right?".
Mock only at system boundaries you don't own (SMS, payment gateway, clock, external HTTP) — that's what adapter interfaces are for (architecture-design). Mocking your own internals welds the test to the implementation: every refactor breaks tests without catching bugs.
Writing tests that stay trustworthy
- Test behavior through the public surface, not private internals. Assert outcomes (response, DB state, emitted event) not call sequences.
- Each test: one behavior, named as a sentence (
test_payment_over_balance_is_rejected), arrange-act-assert visible, independent of other tests and of execution order.
- Test data: build minimal explicit fixtures per test; shared mega-fixtures rot into "nobody knows what depends on this".
- Determinism is non-negotiable: inject the clock, seed randomness, never
sleep-and-hope (wait on conditions), never depend on network or wall-clock date (an Apr–Mar financial-year bug that only fails in April is a test bug too).
Flaky tests — the policy
A flaky test is a broken alarm: quarantine it same-day (skip with a ticket), fix the root cause (real race? test race? shared state?) within days, or delete it honestly. Re-running until green trains the team to ignore red — after that, the suite is decoration.
TDD, pragmatically
Red-green-refactor shines for algorithmic/rule-heavy code (write the pricing test first) and for bug fixes (reproduce first — mandatory). It's ceremony for exploratory UI work. Either way, the invariant holds: watch each new test fail once — a test you've never seen fail may be asserting nothing (this catches ~1 in 10 AI-written tests).
Definition of tested (for a feature to be called done)
- New logic: units for the decisions, one integration test for the wiring.
- The failure paths are tested, not just success — the catch blocks, the validation rejections, the insufficient-permission case.
- Suite runs green from a clean checkout with one command; the command is documented.
- You ran it. "Tests written" without a passing run reported is not tested (report the actual output).
1---2name: testing-strategy3description: Deciding what to test, at which level, and how to keep tests trustworthy. Use when writing tests, setting up a test suite, reviewing test coverage, fixing flaky tests, doing TDD, or when the user says "test", "coverage", "unit test", "integration test", "e2e", or "how do I test this".4---56# Testing Strategy78Tests exist to let you change code fearlessly. A suite you don't trust, don't run, or that breaks on every refactor provides negative value. Optimize for **bugs caught per minute of maintenance**, not coverage percentage.910## What to test — priority order (spend your budget top-down)11121. **Money and state-machine paths**: anything computing totals, tax, discounts, stock, balances, status transitions. These get exhaustive unit tests including the ugly inputs (zero, negative, rounding boundaries, max values, illegal transitions).132. **Authorization**: for each protected route, at least one test proving the wrong principal is refused — wrong tenant's object (the IDOR test), insufficient role, no auth. These tests are cheap and catch breaches.143. **The golden paths, end-to-end-ish**: one integration test per core user journey (signup→login, create invoice→stock decrements→payment records). Through the real API surface against a real (containerized) database — this is where wiring bugs live.154. **Regression pins**: every production bug you fix gets a test that fails on the old code, forever. This is the highest-signal test category that exists; never skip it.165. **Contract edges**: validation rejects what it should; error envelope shape is stable; pagination boundaries.1718Below the line (test only with a reason): getters, framework glue, UI cosmetics, third-party libraries' own behavior.1920## Which level — the honest trade2122- **Unit** (pure logic, no I/O): milliseconds, pinpoint failures — put all *calculation and decision* logic here, which is an argument for extracting logic from I/O (see code-quality). If testing a function needs 5 mocks, the function's design is the finding.23- **Integration** (service + real DB): the default level for CRUD apps — most real bugs are query/transaction/constraint bugs that mocks hide. Use a real disposable database (Docker); an in-memory fake with different semantics tests a different app.24- **E2E** (browser/UI): few, only golden paths, because they're slow and flaky. They answer "is the product alive?", not "is the logic right?".2526Mock only at *system boundaries you don't own* (SMS, payment gateway, clock, external HTTP) — that's what adapter interfaces are for (architecture-design). Mocking your own internals welds the test to the implementation: every refactor breaks tests without catching bugs.2728## Writing tests that stay trustworthy2930- Test behavior through the public surface, not private internals. Assert outcomes (response, DB state, emitted event) not call sequences.31- Each test: one behavior, named as a sentence (`test_payment_over_balance_is_rejected`), arrange-act-assert visible, independent of other tests and of execution order.32- Test data: build minimal explicit fixtures per test; shared mega-fixtures rot into "nobody knows what depends on this".33- Determinism is non-negotiable: inject the clock, seed randomness, never `sleep`-and-hope (wait on conditions), never depend on network or wall-clock date (an Apr–Mar financial-year bug that only fails in April is a test bug too).3435## Flaky tests — the policy3637A flaky test is a broken alarm: quarantine it same-day (skip with a ticket), fix the root cause (real race? test race? shared state?) within days, or delete it honestly. Re-running until green trains the team to ignore red — after that, the suite is decoration.3839## TDD, pragmatically4041Red-green-refactor shines for algorithmic/rule-heavy code (write the pricing test first) and for bug fixes (reproduce first — mandatory). It's ceremony for exploratory UI work. Either way, the invariant holds: **watch each new test fail once** — a test you've never seen fail may be asserting nothing (this catches ~1 in 10 AI-written tests).4243## Definition of tested (for a feature to be called done)4445- New logic: units for the decisions, one integration test for the wiring.46- The failure paths are tested, not just success — the catch blocks, the validation rejections, the insufficient-permission case.47- Suite runs green from a clean checkout with one command; the command is documented.48- You ran it. "Tests written" without a passing run reported is not tested (report the actual output).
05-deepak-patidar