Add Fuzz Target

Add a fuzz target

remindb fuzzes parser, query, transformer, compiler, and temperature code. The fuzz harness is whatever Go's testing.F gives you — there's no project-specific framework — but the seed-corpus discipline is project convention worth getting right. scripts/fuzz.sh auto-discovers any Fuzz* function via go test -list='^Fuzz', so naming your function FuzzXxx is the only registration needed.

Where it lands

Two files at most.

If pkg/<package>/fuzz_test.go already exists (it does for parser, query, transformer, compiler, temperature), append; don't make a second file.

The function shape

Mirror pkg/parser/fuzz_test.go and pkg/temperature/fuzz_test.go. The shape is uniform:

func FuzzExample(f *testing.F) {
    // Seed corpus — see "Seed selection" below.
    f.Add(input1, input2)
    // ... more f.Add lines, each one shape ...

    f.Fuzz(func(t *testing.T, input1 T1, input2 T2) {
        result, err := YourFunc(input1, input2)

        // Invariants — see "Invariant assertions" below.
        if err != nil {
            return        // errors are fine; panics are not
        }
        if !invariantHolds(result) {
            t.Errorf("invariant violated: ...")
        }
    })
}

Two rules:

• Function name FuzzXxx. scripts/fuzz.sh greps for ^Fuzz in go test -list output. Anything else is invisible.
• One target per logical surface. Don't multiplex two unrelated functions into one fuzz target — Go's fuzzer mutates the input tuple as a unit, so combined targets dilute coverage.

Seed selection — the discipline

A fuzz seed says "this is a shape worth starting from." The fuzzer mutates from there. The point isn't to enumerate all valid inputs; it's to give the mutator a head start on every category of structural variation. Aim for one seed per shape:

pkg/temperature/fuzz_test.go is the cleanest template for numeric fuzz; pkg/parser/fuzz_test.go is the template for byte-sequence fuzz. Both spend ~10 seed lines each — that's the right density.

Invariant assertions

The default invariant is must not panic. The runtime catches panics and reports them as crashes, so you don't write that one — it's free.

Beyond no-panic, write property assertions, not example-based ones. The mutator generates novel inputs you can't predict:

• Type-level invariants: len(out) <= len(in), result >= 0, tokensUsed <= budget.
• Round-trip invariants: Decode(Encode(x)) == x.
• Conditional invariants: "if input is valid UTF-8, error must be nil". pkg/parser/fuzz_test.go does this for ErrInvalidUTF8.
• Domain invariants: "result is non-NaN when both inputs are non-NaN" (see FuzzDecayFactor and FuzzScore in pkg/temperature/fuzz_test.go).

A common pattern: when an input could be invalid, gate the assertion on input validity:

if budget >= 0 && tok1 >= 0 && tok2 >= 0 {
    if result.TokensUsed > budget {
        t.Errorf("TokensUsed = %d exceeds budget %d", result.TokensUsed, budget)
    }
}

This avoids spurious failures from negative-int inputs you've already documented as out-of-domain.

Running it locally

# Run all fuzz targets for 30 seconds each
scripts/fuzz.sh 30s

# Or one target for longer
go test -run='^$' -fuzz='^FuzzExample$' -fuzztime=2m ./pkg/<package>/

A new target should run for at least 30s without crashing before you commit. If a crash surfaces, the crashing seed is saved under pkg/<package>/testdata/fuzz/FuzzExample/<hash> — commit that file along with the fix so future runs replay the regression.

Quick reference

1. pkg/<package>/fuzz_test.go    (FuzzXxx with seed corpus + Fuzz callback)
2. scripts/fuzz.sh 30s            (must finish without crashes)
3. If a crash file appears in testdata/fuzz/: fix root cause, commit the seed

Common mistakes

• Asserting on a specific output value. The fuzzer's input is unpredictable; specific outputs can't hold. Use property assertions: bounds, types, conditional invariants.
• Returning early on err != nil without checking what kind of error. If the function should return a specific sentinel for a given input class (like ErrInvalidUTF8 for invalid UTF-8 in parser), assert that. Otherwise generic return on error is correct.
• Missing the f.Add(...) seed for the empty/zero case. The Go fuzzer mutates from seeds — without an empty seed, it may take a long time to discover the empty input naturally.
• Long-running invariant checks inside the fuzz body. Each iteration runs thousands of times per second; an O(n²) assertion will throttle the fuzzer and reduce coverage. Keep invariant checks O(n) or O(1).
• Not committing crash seeds from testdata/fuzz/. The seed file is the regression test for the bug you just fixed. Without it, the same bug can re-emerge silently.
• Naming the function FuzzTestXxx or FuzzCheck. scripts/fuzz.sh greps ^Fuzz so any prefix-only-Fuzz name works, but stylistic convention here is FuzzXxx matching the function-under-test.

Cross-references

• .claude/rules/go-concise.md — error sentinel patterns, naming
• .claude/skills/add-parser/SKILL.md — for the special case of seeding FuzzParseBytes with a new format (you don't add a new fuzz target, you extend an existing one)
• scripts/fuzz.sh — the auto-discovery loop; read it once if you're curious how go test -list='^Fuzz' finds your target