fast-check-testing

Overview

fast-check is "a property-based testing framework for JavaScript and TypeScript, inspired by QuickCheck" (fast-check-readme).

It's runner-agnostic (fast-check-overview): "Test Runner Agnostic: Works seamlessly with Jest, Mocha, Vitest, and other testing frameworks without special integration."

When to use

• A JS/TS codebase has functions with non-trivial input shapes (parsers, serializers, validators, data transforms).
• Async code where race conditions hide; fast-check supports race condition detection (fast-check-overview).
• Round-trip / metamorphic properties hold (encode(decode(x)) === x).
• Existing example-based tests pass but production bugs keep appearing in edge cases not covered.

Install

Per fast-check-readme:

npm install fast-check --save-dev
# or
yarn add fast-check --dev
# or
pnpm add -D fast-check

Basic property

Per fast-check-readme, the canonical Mocha-style example:

import fc from 'fast-check';

const contains = (text, pattern) => text.indexOf(pattern) >= 0;

describe('properties', () => {
  it('should always contain itself', () => {
    fc.assert(fc.property(fc.string(), (text) => contains(text, text)));
  });

  it('should always contain its substrings', () => {
    fc.assert(
      fc.property(fc.string(), fc.string(), fc.string(), (a, b, c) => {
        return contains(a + b + c, b);
      })
    );
  });
});

The shape: fc.assert(fc.property(<arbitraries...>, (...inputs) => <predicate>)).

The predicate returns:

• true → the property holds.
• false → the property fails.
• Throws an exception → the property fails (typical for expect(...) style assertions).

fc.assert runs the property with 100 generated cases by default; on failure, fast-check shrinks to the minimal counterexample.

Arbitraries and composite inputs

Pick arbitraries that match the input domain, build domain values with .map() / .chain(), and assemble objects with fc.record. Full catalog and combinator patterns: references/arbitraries.md. Prefer constrained arbitraries (fc.integer({ min: 1 }), fc.emailAddress()) over broad ones filtered down.

Integrate with the test runner

Per fast-check-overview: works "with major testing frameworks including Jest, Vitest, Mocha, Jasmine, AVA, and Tape" without special integration.

// Jest / Vitest example
import { test, expect } from 'vitest';
import fc from 'fast-check';

test('reverse is involutive', () => {
  fc.assert(
    fc.property(fc.array(fc.integer()), (arr) => {
      expect([...arr].reverse().reverse()).toEqual(arr);
    })
  );
});

The assertion library (expect, assert) is the runner's; fast-check hooks into thrown errors as failures. For async properties use await fc.assert(fc.asyncProperty(...)).

Shrinking and reproducibility

On failure fast-check prints the shrunk counterexample plus a seed; replaying that seed reproduces the failure deterministically, and a fixed CI seed keeps runs stable. Output format, replay, and CI seed: references/shrinking-and-reproducibility.md.

Stateful and async testing

For concurrent code use fc.scheduler race-condition detection; for stateful systems use command-sequence model-based testing with fc.commands / fc.modelRun. Both patterns: references/stateful-and-async.md.

How to use

1. Install fast-check as a dev dependency (npm install fast-check --save-dev).
2. Identify a property that holds for all inputs (round-trip, invariant, metamorphic) rather than a single example.
3. Pick arbitraries matching the input domain from references/arbitraries.md; prefer constrained arbitraries over .filter().
4. Wire fc.assert(fc.property(<arbitraries...>, (...inputs) => <predicate>)); the predicate returns false or throws on violation.
5. Run under the existing runner (Jest / Vitest / Mocha / ...); for async use await fc.assert(fc.asyncProperty(...)).
6. On failure, read the shrunk counterexample and replay its seed to reproduce - see references/shrinking-and-reproducibility.md.
7. Verify: after fixing the cause, re-run the property and confirm it passes all 100 generated cases, and replay the failing seed to confirm the counterexample is gone; if it still fails, the fix is incomplete or the property itself is wrong - correct and re-run.
8. For stateful or concurrent code, escalate to model-based testing or fc.scheduler - references/stateful-and-async.md.

Worked example

A codec exposes encode(obj) and decode(str) and claims decode(encode(x)) === x for every payload.

1. Model the input with a composite arbitrary (references/arbitraries.md):

import fc from 'fast-check';
import { encode, decode } from './codec';

const payload = fc.record({
  id: fc.uuid(),
  count: fc.integer({ min: 0 }),
  tags: fc.uniqueArray(fc.string()),
});

2. Assert the round-trip under Vitest:

test('decode reverses encode', () => {
  fc.assert(
    fc.property(payload, (x) => {
      expect(decode(encode(x))).toEqual(x);
    })
  );
});

3. encode silently drops empty-string tags, so the run fails and fast-check shrinks to the minimal offending input:

Property failed after 12 tests
{ seed: 42, path: "11:0", endOnFailure: true }
Counterexample: [{"id":"...","count":0,"tags":[""]}]

4. Replaying { seed: 42, path: "11:0" } reproduces it every time (references/shrinking-and-reproducibility.md). Fix encode to preserve empty tags; the property then passes all 100 cases.

Anti-patterns

Limitations

• Shrinking time. Complex arbitraries (deeply nested records) can take 30+ seconds to shrink. Use endOnFailure: true to short-circuit when the unshrunk case is sufficient.
• Type inference for composite records. TypeScript's inference on fc.record({ ... }) can produce unhelpful types; explicit type annotations help.
• Race-condition detection has cost. fc.scheduler explores interleavings exhaustively; for many-task tests, runtime grows fast.
• No formal proof. 100 cases is convention; non-trivial domains may need more.

References

• fast-check-readme - install, basic example with fc.assert / fc.property / fc.string, runner integration, trust list.
• fast-check-overview - arbitraries catalog, .map / .chain combinators, race-condition detection, model-based testing, framework-agnostic positioning.
• references/arbitraries.md - arbitraries catalog, combinators, composite fc.record inputs.
• references/stateful-and-async.md - race-condition detection and model-based testing.
• references/shrinking-and-reproducibility.md - failure output format, seed replay, CI seed.
• hypothesis-testing - Python sibling.
• schemathesis-fuzzing - applies fast-check-shaped PBT to API schemas.