Testing

Testing Skill

Overview

This skill provides comprehensive guidance on testing in TypeScript projects, with a focus on the dual nature of testing: runtime behavior and type correctness. It covers when to use each type of test, how to structure tests effectively, and how to integrate testing into development workflows using Test-Driven Development (TDD).

Types of Testing

1. Runtime Tests

Runtime tests verify the actual behavior of code during execution.

When to use:

• Testing function outputs with various inputs
• Verifying error handling and edge cases
• Checking side effects (file I/O, API calls, state mutations)
• Validating business logic and algorithms
• Testing class instance behavior and methods

Tools:

• Test runner: Vitest
• Commands:
  • pnpm test - runs all runtime tests
  • pnpm test GLOB - runs tests matching the glob pattern

Example structure:

import { describe, it, expect } from "vitest";
import { prettyPath } from "~/utils";

describe("prettyPath()", () => {
    it("should format a path with directory and filename", () => {
        const result = prettyPath("/path/to/file.ts");
        expect(result).toBe("/path/to/file.ts"); // Expected formatting
    });

    it("should handle edge case: empty string", () => {
        const result = prettyPath("");
        expect(result).toBe("");
    });

    it("should handle edge case: root path", () => {
        const result = prettyPath("/");
        expect(result).toBe("/");
    });
});

2. Type Tests

Type tests verify the type correctness of TypeScript code at design time.

When to use:

• Testing type utility functions (always)
• Verifying generic type constraints work as expected
• Ensuring conditional types resolve correctly
• Testing that complex inferred types are accurate
• Validating discriminated unions and type narrowing
• Checking that function signatures accept/reject correct types

Tools:

• Commands:
  • pnpm test:types - runs all type tests
  • pnpm test:types GLOB - runs type tests matching the glob pattern

Type Test Structure

This section will show you, layer by layer, how to compose and build good type tests.

cases block

All type tests in a given it test block (defined by Vitest) will have a type called cases defined as an array of type tests.

type cases = [
    // ... type tests go here
]

Note: our linting rules allow for the name cases to be defined without being used; this is intentional and a good thing.

Expect<...> wrapper

Every type test will be wrapped by an Expect type utility.

type cases = [
    Expect<...>,
    Expect<...>,
    // ...
]

Available Type Test Assertions

The inferred-types library provides a number of useful assertion utilities you can use to create your tests:

• AssertTrue<T> ****
  • tests whether the tested type T is the type true
• AssertFalse<T>
  • tests whether the tested type T is the type false
• AssertEqual<T,E>
  • tests that the tested type T equals the expected type E
• AssertExtends<T,E>
  • tests that the tested type T extends the expected type E
• AssertSameValues<T,E>
  • tests that the tested type T is an array type and every element of E and T are the same but the order in which they arrive does not matter
• AssertContains<T,E>
  • when the tested type T is a string:
    • this utility will pass when E is also a string and represents a sub-string of the sting literal T
  • when the tested type T is an array then:
    • this utility

In all cases you put the test assertion inside of the Expect utility:

type cases [
    Expect<AssertTrue<T>>,
    Expect<AssertExtends<T, string>>,
    // ...
]

Example 1

In our example we'll just test a built-in type utility of Typescript's named Capitalize<T>.

• this utility simply capitalizes the first letter in a string literal

import type { Expect, Equal } from "inferred-types/types";

describe("Example 1", () => {
    it("string literals", () => {
        type Lowercase = Capitalize<"foo">;
        type AlreadyCapitalized = Capitalize<"Foo">;

        type cases = [
            Expect<AssertEqual<Lowercase, "Foo">>,
            Expect<AssertEqual<AlreadyCapitalized, "Foo">>,
        ]
    });

    it("wide string", () => {
        type Wide = Capitalize<string>;

        type cases = [
            Expect<AssertEqual<Wide, string>>
        ]
    })

    it("only first letter capitalized", () => {
        type SpaceThenLetter = Capitalize<" foo">;
        type TabThenLetter = Capitalize<"\tfoo">;

        type cases = [
            Expect<AssertEqual<SpaceThenLetter, " foo">>,
            Expect<AssertEqual<TabThenLetter, "\tfoo">>,
        ]
    })
});

IMPORTANT: in the example above we were testing a type utility (where a type utility is any type which accepts generics and uses them to produce a type); and with type utilities you CAN'T do runtime testing because there is no runtime component to test. However, we do still use the Vitest primitives of describe and it to organize the test.

Example 2

Let's imagine we create a simple function:

• capitalize<T extends string>(text: T): Capitalize<T>.
• here we have a VERY common situation for library authors:
  • a function which provides a narrow type return
• in this situation we will want to have BOTH runtime and type tests

describe("example", () => {
    it("leading alpha character", () => {
        const lowercase = capitalize("foo");
        const alreadyCapitalized = capitalize("Foo");

        expect(lowercase).toEqual("Foo");
        expect(alreadyCapitalized).toEqual("Foo");

        type cases = [
            Expect<AssertEqual<typeof lowercase, "Foo">>,
            Expect<AssertEqual<typeof alreadyCapitalized, "Foo">>,
        ]
    });

    it("wide string", () => {
        const wide = capitalize("foo" as string);

        expect(wide).toBe("Foo");

        type cases = [
            Expect<AssertEqual<typeof wide, string>>
        ]
    })

    it("non-alpha leading character", () => {
        const spaceThenLetter = capitalize(" foo");
        const tabThenLetter = capitalize("\tfoo");

        expect(spaceThenLetter).toBe(" foo");
        expect(tabThenLetter).toBe("\tfoo");

        type cases = [
            Expect<AssertEqual<typeof spaceThenLetter, " foo">>,
            Expect<AssertEqual<typeof tabThenLetter, "\tfoo">>,
        ]
    })
})

IMPORTANT: in these sorts of tests the runtime and type tests naturally fit into the same describe/it blocks. You should almost NEVER have a set of runtime tests in one structure, and then a set of type tests in another. This almost always indicates someone who doesn't understand type testing well enough yet.

IMPORTANT: in both examples we've see a test structure where define intermediate variable/types which assume the value/type of the "test". Then we use the variable/type in our tests. We could possibly just inline the expression you're testing into the runtime and type tests but this can actually have undesirable side effects in some cases but having the intermediate variables/types defined first allows a human observer to hover over the variable to see what type resolution there was. This is highly valuable!

Common Type Testing Mistakes

Mistake #1: Separated "Type Tests" Blocks (MOST COMMON)

❌ WRONG - Separated structure:

describe("myFunction()", () => {
    describe("Runtime tests", () => {
        it("should work", () => {
            expect(myFunction("test")).toBe("result");
        });
    });

    describe("Type Tests", () => {  // ❌ WRONG!
        it("should have correct type", () => {
            const result = myFunction("test");
            const _check: typeof result extends string ? true : false = true;
            expect(_check).toBe(true);  // ❌ This is NOT a type test!
        });
    });
});

✅ CORRECT - Integrated structure:

describe("myFunction()", () => {
    it("should work with string input", () => {
        const result = myFunction("test");

        // Runtime test
        expect(result).toBe("result");

        // Type test - in the SAME it() block
        type cases = [
            Expect<AssertEqual<typeof result, "result">>
        ];
    });
});

Mistake #2: Using Runtime Checks for Type Testing

❌ WRONG:

const result = myFunction("test");
const _isString: typeof result extends string ? true : false = true;
expect(_isString).toBe(true);  // This is runtime testing, not type testing!

✅ CORRECT:

const result = myFunction("test");
type cases = [
    Expect<AssertExtends<typeof result, string>>
];

Mistake #3: No cases Array

❌ WRONG:

Expect<AssertEqual<typeof result, "expected">>;  // Not in cases array!

✅ CORRECT:

type cases = [
    Expect<AssertEqual<typeof result, "expected">>
];

Mistake #4: Using typeof with Runtime Assertions

❌ WRONG:

const result = myFunction("test");
expect(typeof result).toBe("string");  // This is runtime, not type testing!

✅ CORRECT:

const result = myFunction("test");

// Runtime test (if needed)
expect(result).toBe("expected-value");

// Type test
type cases = [
    Expect<AssertExtends<typeof result, string>>
];

Type Test Validation

Before submitting ANY work with type tests, verify:

1. Pattern check: Does every type test use type cases = [...]?
2. Assertion check: Does every assertion use Expect<Assert...>?
3. Structure check: Are type tests side-by-side with runtime tests?
4. Import check: Do files import from inferred-types/types?
5. No separation: Are there ZERO "Type Tests" describe blocks?
6. Cardinal sin check: Did you change ANY test assertions to make failing tests pass? If YES, STOP and revert.
7. Tests document correct behavior: Do assertions reflect what SHOULD happen, not what currently happens?

If any check fails, the type tests are incorrect and must be rewritten.

Note: Tests may fail if there are bugs in the implementation. That's expected and correct. DO NOT change assertions to make them pass.

Decision Framework: Which Tests to Write?

Use this flowchart to determine what tests you need:

Is the symbol exported from the module?
│
├─ NO → Consider if it needs tests at all
│        (internal helpers may not need dedicated tests)
│
└─ YES → What kind of symbol is it?
          │
          ├─ Type Utility (e.g., a type which takes generics)
          │  └─ Write TYPE TESTS always; no RUNTIME tests are even possible!
          │
          ├─ Constant (literal value)
          │  └─ Usually NO tests needed
          │     (unless it's a complex computed value)
          │
          ├─ Function / Arrow Function
          │  └─ Does it return a literal type?
          │     ├─ YES → Write BOTH runtime AND type tests
          │     └─ NO → Write RUNTIME tests (minimum); possibly write type tests
          │
          ├─ Class
          │  └─ Does it use generics or have methods which return literal types?
          │     ├─ YES → Write BOTH runtime AND type tests
          │     └─ NO → Write RUNTIME tests primarily
          │
          └─ Interface / Type Definition (e.g., a type without a generic input)
             └─ Usually NO test needed; if there is no generic then there is no variance to test
             └─ Only exception might be when the type being defined uses a lot of type utilities in it's definition. In these cases, you _might_ test that the type is not an `any` or `never` type because the underlying utilities 

Rule of thumb: When in doubt, write tests. It's better to have coverage than to skip it.

Test Organization and Structure

File Structure

Tests are organized by feature/command area:

tests/
├── unit/
│   ├── test-command/       # Tests for the 'test' CLI command
│   ├── symbol-command/     # Tests for the 'symbols' CLI command
│   ├── source-command/     # Tests for the 'source' CLI command
│   ├── utils/              # Tests for utility functions
│   └── WIP/                # Temporary location for in-progress phase tests
├── integration/
│   ├── fast/               # Fast integration tests (<2s each)
│   └── *.test.ts           # Full integration tests
└── fixtures/               # Test fixtures and sample projects

Naming Conventions

• Test files: *.test.ts
• Fast integration tests: *.fast.test.ts
• Test descriptions:
  • Use "should" statements: it("should return true when...)
  • Be specific about the scenario: it("should handle empty arrays")
  • Describe the behavior, not the implementation

Test Structure Principles

DO:

• Keep tests focused on a single behavior
• Use descriptive test names that explain the scenario
• Group related tests in describe blocks
• Test edge cases (empty, null, undefined, boundary values)
• Test error conditions and failure modes
• Make tests independent (no shared state between tests)

DON'T:

• Test implementation details (test behavior, not internals)
• Add logic to tests (no conditionals, loops, or complex computations)
• Share mutable state between tests
• Make tests depend on execution order
• Skip asserting the results (every test needs expectations)

TDD Workflow for Phase-Based Development

When implementing a new feature or phase of work, follow this comprehensive TDD workflow:

Phase Structure Overview

1. SNAPSHOT - Capture current test state
2. CREATE LOG - Document starting position
3. WRITE TESTS - Create tests first (TDD)
4. IMPLEMENTATION - Build to pass tests
5. CLOSE OUT - Verify, migrate tests, document completion

Step 1: SNAPSHOT

Capture the current state of all tests before making any changes.

Actions:

1. Run all runtime tests:

   pnpm test
   

2. Run all type tests:

   pnpm test:types
   

3. Create a simple XML representation of test results distinguishing between runtime and type test runs

4. Document any existing failures (these are your baseline - don't fix yet)

Purpose: Establish a clear baseline so you can detect regressions and measure progress.

Step 2: CREATE LOG

Create a log file to track this phase of work.

Actions:

1. Create log file with naming convention:

   mkdir -p .ai/logs
   touch .ai/logs/YYYY-MM-planName-phaseN-log.md
   

   Example: .ai/logs/2025-10-symbol-filtering-phase1-log.md

2. Add ## Starting Test Position section with XML code block containing test results from SNAPSHOT

3. Add ## Repo Starting Position section

4. Run the start-position script to capture git state:

   bun run .claude/skills/scripts/start-position.ts planName phaseNumber
   

   This returns markdown content showing:

   • Last local commit hash
   • Last remote commit hash
   • Dirty files (uncommitted changes)
   • File snapshot (if not using --dry-run flag)

5. Append the start-position output to the log file

Purpose: Create a detailed record of the starting point for debugging and tracking progress.

Step 3: WRITE TESTS

Write tests FIRST before any implementation. This is true Test-Driven Development.

Actions:

1. Understand existing test structure:

   • Review similar tests in the codebase
   • Identify patterns and conventions
   • Determine where your tests should eventually live

2. Create tests in WIP directory:

   • All new test files for this phase go in tests/unit/WIP/
   • This isolation allows:
     • Easy GLOB pattern targeting: pnpm test WIP
     • Regression testing by exclusion: pnpm test --exclude WIP
     • Clear separation of work-in-progress from stable tests

3. Write comprehensive test coverage:

   • Start with happy path (expected successful behavior)
   • Add edge cases (empty, null, undefined, boundaries)
   • Add error conditions
   • Include both runtime and type tests if applicable

4. Verify tests FAIL initially:

   • Run your new tests: pnpm test WIP
   • Confirm they fail (you haven't implemented yet)
   • Failing tests prove they're valid and will detect when implementation is complete

Example WIP structure:

tests/unit/WIP/
├── phase1-cli-options.test.ts
├── phase1-filter-logic.test.ts
└── phase1-integration.test.ts

Purpose: Tests define the contract and expected behavior before any code is written.

Step 4: IMPLEMENTATION

Use the tests to guide your implementation.

Actions:

1. Implement minimal code to pass each test:

   • Work on one test at a time (or small group)
   • Write the simplest code that makes the test pass
   • Don't over-engineer or add features not covered by tests

2. Iterate rapidly:

   • Run tests frequently: pnpm test WIP
   • For type tests: pnpm test:types WIP
   • Fix failures immediately
   • Keep the feedback loop tight

3. Continue until all phase tests pass:

   • All tests in tests/unit/WIP/ should be green
   • No shortcuts - every test must pass

4. Refactor with confidence:

   • Once tests pass, improve code quality
   • Tests act as a safety net
   • Re-run tests after each refactor

Purpose: Let tests drive the implementation, ensuring you build exactly what's needed.

Step 5: CLOSE OUT

Verify completeness, check for regressions, and finalize the phase.

Actions:

1. Run full test suite:

   pnpm test        # All runtime tests
   pnpm test:types  # All type tests
   

2. Handle any regressions:

   If existing tests now fail:

   • STOP and think deeply - understand WHY the test is failing, not just the error message
   • Document the regression in the log file under ## Regressions Found
   • Determine root cause:
     • Is your implementation incorrect?
     • Does the existing test need updating (only if requirements changed)?
     • Is there a side effect you didn't anticipate?
   • Fix the root cause, not just the symptom
   • Re-run all tests to confirm fix

3. If no regressions, migrate tests to permanent locations:

   • Think carefully about the right permanent location for each test
   • Consider if a new subdirectory is needed in the test structure
   • Move tests from tests/unit/WIP/ to their permanent homes
   • Delete the tests/unit/WIP/ directory
   • Rerun tests to ensure nothing broke during migration

4. Update the log file:

   Add a ## Phase Completion section with:

   • Date and time completed
   • Final test count (passing/total)
   • Any notable issues or decisions made
   • Location where tests were migrated to

5. Report completion:

   Inform the user that the phase is complete with a summary of:

   • What was implemented
   • Test coverage added
   • Any important notes or caveats

Purpose: Ensure quality, prevent regressions, and properly integrate work into the codebase.

Testing Best Practices

General Principles

• Prefer real implementations over mocks: Only mock external dependencies (APIs, file system, databases). Keep internal code integration real.

• Use realistic test data: Mirror actual usage patterns. If your function processes user objects, use realistic user data in tests.

• One behavior per test: Each it() block should test a single specific behavior. This makes failures easier to diagnose.

• Tests should be deterministic: Same input = same output, every time. Avoid depending on current time, random values, or external state unless that's what you're testing.

• Keep tests independent: Each test should be able to run in isolation. Use beforeEach() for setup, not shared variables.

• Test the contract, not the implementation: If you change HOW something works but it still behaves the same, tests shouldn't break.

Error Handling

• Prioritize fixing source code over changing tests: When tests fail, your first instinct should be to fix the implementation to meet the test's expectation, not to change the test to match the implementation.

• Understand failures deeply: Don't just read the error message - understand WHY the test is failing. Use debugging, logging, or step through the code if needed.

• Document complex test scenarios: If a test needs explanation, add a comment describing what scenario it's covering and why it matters.

THE CARDINAL SIN: Never Change Tests to Match Buggy Code

⚠️ CRITICAL RULE: TESTS DOCUMENT CORRECT BEHAVIOR, NOT CURRENT BEHAVIOR

This is the most important testing principle and MUST be followed at all times:

NEVER change test expectations to make failing tests pass.

When tests fail, there are ONLY THREE valid responses:

1. Fix the implementation - The implementation has a bug. Fix it.
2. Validate with the user - Ask the user if your test expectation is wrong. They must explicitly approve any changes to test assertions. Say: "I expected X to be true, but it's returning false. Should the test expect false instead, or is this a bug?"
3. Mark as TODO (with user permission) - If there's a known dependency that must be implemented first, ask the user for permission to use it.todo() or describe.todo(). Explain what needs to be done first and when this test can be enabled.

INVALID responses:

• ❌ Change AssertTrue to AssertFalse because the test is failing
• ❌ Change expected values to match buggy output
• ❌ Comment out failing tests "temporarily"
• ❌ Add comments like "known limitation" to justify wrong assertions
• ❌ Use it.skip() or it.todo() without user permission
• ❌ Assume your test expectation is wrong without asking

Example of the WRONG Approach

// User says: "Arrays SHOULD match but there's a bug in Contains"
type ArrayUnion = string[] | number[] | [1, 2, 3];
type Test1 = UnionIncludes<ArrayUnion, [1, 2, 3]>;

// ❌ WRONG: Changing test to make it pass
type cases = [
    Expect<AssertFalse<Test1>>  // Changed to False to make test pass!
];

Example of the CORRECT Approach

// User says: "Arrays SHOULD match but there's a bug in Contains"
type ArrayUnion = string[] | number[] | [1, 2, 3];
type Test1 = UnionIncludes<ArrayUnion, [1, 2, 3]>;

// ✅ CORRECT: Test asserts what SHOULD happen, even if it currently fails
type cases = [
    Expect<AssertTrue<Test1>>  // This SHOULD be true, so assert true
];
// This test will FAIL. That's GOOD. It documents the bug that needs fixing.

Why This Matters

1. Tests are documentation - They tell future developers what the code SHOULD do
2. Failing tests are bug reports - They point out what needs to be fixed
3. Passing tests mean nothing if they're wrong - Green tests that assert buggy behavior are worse than no tests
4. You defeat the purpose of testing - Tests exist to catch bugs, not hide them

When to Change Test Assertions

ONLY change test assertions when:

1. User explicitly approves - You asked the user "Should this be X or Y?" and they said "Y"
2. Requirements changed - The spec now says something different (with user confirmation)
3. Test was factually wrong - You misunderstood the API, made a typo, etc. (validate with user first)

NEVER change test assertions when:

1. Implementation is buggy - Fix the code, not the test
2. To make CI pass - This is hiding problems
3. Because the test is failing - That's the test doing its job!
4. Linter/formatter changed it back - The linter was CORRECTING your mistake
5. Without user permission - ALWAYS ask before changing assertions

When to Use it.todo() or describe.todo()

These modifiers mark tests that are written but cannot pass yet due to missing dependencies.

✅ Valid use (with user permission):

// User approved: "Mark this as TODO until we fix the Contains bug"
it.todo("should match array types in unions", () => {
    type ArrayUnion = string[] | number[] | [1, 2, 3];
    type Test1 = UnionIncludes<ArrayUnion, [1, 2, 3]>;

    type cases = [
        Expect<AssertTrue<Test1>>  // Correct expectation, blocked by Contains bug
    ];
});

❌ Invalid use (without permission):

// NO user permission - just trying to make tests pass
it.todo("should match array types in unions", () => {
    // ... hiding a failing test
});

Process for using TODO:

1. Write the test with correct expectations
2. Confirm it fails
3. Ask user: "This test documents correct behavior but fails due to [dependency]. May I mark it as it.todo() until [dependency] is fixed?"
4. Only use TODO if user approves
5. Document in test comment what needs to be done first

Red Flags That You're Making This Mistake

• You find yourself changing true to false or vice versa in assertions
• You're adding comments like "known limitation", "currently broken", "will fix later"
• The linter keeps changing your tests back
• You're adjusting expected values to match what the code actually does (rather than what it should do)
• You're thinking "I'll just make this pass for now"

IF YOU FIND YOURSELF DOING ANY OF THESE: STOP IMMEDIATELY.

The correct action is:

1. Keep the test asserting the correct behavior
2. Let it fail
3. Either fix the implementation or report that you cannot fix it yet and the test will fail until the bug is fixed

Performance

• Keep unit tests fast: Unit tests should run in milliseconds. If a test is slow, it's likely testing too much or hitting external resources.

• Separate fast and slow tests: Integration tests can be slower. Keep them in separate files (e.g., *.fast.test.ts vs *.test.ts).

• Use focused test runs during development: Don't run the entire suite on every change. Use glob patterns to run just what you're working on.

Type Testing Specifics

• Always test the positive case: Verify that valid types are accepted and produce the expected result type.

• Test the negative case when relevant: Use @ts-expect-error to verify that invalid types are properly rejected.

• Test edge cases in type logic: Empty objects, never, unknown, union types, etc.

• Keep type tests close to runtime tests: When testing a function with both runtime and type tests, keep them in the same file within the same describe block for cohesion.

Common Patterns and Examples

Testing Error Cases

it("should throw error for invalid input", () => {
    expect(() => parseConfig("invalid")).toThrow("Invalid config format");
});

it("should return error result for invalid type", () => {
    const result = safeParseConfig("invalid");
    expect(result.success).toBe(false);
    if (!result.success) {
        expect(result.error).toContain("Invalid config");
    }
});

Testing Async Functions

it("should resolve with data on success", async () => {
    const result = await fetchUser(123);
    expect(result.id).toBe(123);
    expect(result.name).toBeDefined();
});

it("should reject with error on failure", async () => {
    await expect(fetchUser(-1)).rejects.toThrow("User not found");
});

Testing Type Narrowing

it("should narrow type based on discriminant", () => {
    type Result = { success: true; data: string } | { success: false; error: string };

    const handleResult = (result: Result) => {
        if (result.success) {
            type Test = Expect<Equal<typeof result, { success: true; data: string }>>;
            return result.data;
        } else {
            type Test = Expect<Equal<typeof result, { success: false; error: string }>>;
            return result.error;
        }
    };
});

Quick Reference

Commands

# Runtime tests
pnpm test                    # Run all runtime tests
pnpm test path/to/test       # Run specific test file
pnpm test WIP                # Run only WIP tests
pnpm test --exclude WIP      # Run all except WIP (regression check)
pnpm test:watch              # Run in watch mode
pnpm test:ui                 # Run with UI

# Type tests
pnpm test:types              # Run all type tests
pnpm test:types GLOB         # Run type tests matching pattern
pnpm test:types WIP          # Run only WIP type tests

# Common patterns during development
pnpm test utils              # Test all utils
pnpm test:types utils        # Type test all utils

Test Quality Checklist

Before considering tests complete, verify:

• All exported functions have runtime tests
• Functions with complex types have type tests
• Happy path is tested
• Edge cases are covered (empty, null, undefined, boundaries)
• Error conditions are tested
• Tests are independent (can run in any order)
• Tests are deterministic (consistent results)
• Test names clearly describe what's being tested
• No regressions in existing tests
• Tests run quickly (unit tests < 100ms per test)

Phase Completion Checklist

Before closing out a phase:

• SNAPSHOT captured
• Log file created with starting position
• Tests written in tests/unit/WIP/
• Tests initially failed (proving validity)
• Implementation completed
• All WIP tests passing
• Full test suite run (no regressions)
• Tests migrated from WIP to permanent locations
• tests/unit/WIP/ directory removed
• Log file updated with completion notes
• User notified of phase completion

Summary

Effective testing requires understanding what to test, how to test it, and when to use different testing approaches:

• Type utilities → Type tests only
• Simple functions → Runtime tests (minimum)
• Complex functions → Both runtime and type tests
• Classes → Primarily runtime tests, add type tests for complex generics

Follow TDD principles: write tests first, implement to pass them, then refactor with confidence. Keep tests fast, focused, and independent.

For phase-based development, use the five-step workflow: SNAPSHOT → CREATE LOG → WRITE TESTS → IMPLEMENTATION → CLOSE OUT. This ensures comprehensive test coverage, prevents regressions, and maintains clear documentation of your progress.

When tests fail, understand why before fixing. Prioritize fixing implementation over changing tests, unless the test itself was wrong.

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