In this article, we will analyze the causes of flaky assertions in Chai, explore debugging techniques, and provide best practices to ensure stable and reliable test assertions.

Understanding Flaky Assertions in Chai

Flaky assertions occur when a test sometimes passes and sometimes fails without any code changes. Common causes include:

  • Incorrect usage of deep equality checks.
  • Assertions executing before asynchronous operations complete.
  • State mutation within test assertions.
  • Floating point precision issues in numerical comparisons.

Common Symptoms

  • Tests failing intermittently without changes to the test or code.
  • Assertions evaluating undefined or null unexpectedly.
  • Async tests passing before expected behavior completes.
  • Comparisons of objects failing despite appearing identical.

Diagnosing Flaky Chai Assertions

1. Checking Deep Equality Issues

Ensure objects being compared are structurally identical:

expect({ a: 1 }).to.deep.equal({ a: 1 });

2. Debugging Asynchronous Assertions

Ensure async assertions properly await promises:

await expect(fetchData()).to.eventually.have.property("status", "success");

3. Detecting Mutated State

Ensure objects are not modified between assertions:

const data = { a: 1 };
data.a = 2;
expect(data).to.deep.equal({ a: 1 }); // Fails

4. Handling Floating Point Precision

Use approximate assertions for numerical comparisons:

expect(0.1 + 0.2).to.be.closeTo(0.3, 0.0001);

5. Ensuring Proper Promise Handling

Check that rejected promises are correctly handled:

await expect(Promise.reject(new Error("Fail"))).to.be.rejectedWith("Fail");

Fixing Flaky Assertions in Chai

Solution 1: Using deep.equal for Object Comparisons

Ensure deep object comparisons are used correctly:

expect({ a: 1, b: 2 }).to.deep.equal({ a: 1, b: 2 });

Solution 2: Waiting for Asynchronous Operations

Use chai-as-promised for async assertions:

const chaiAsPromised = require("chai-as-promised");
chai.use(chaiAsPromised);
await expect(fetchData()).to.eventually.have.property("id");

Solution 3: Avoiding State Mutations

Use immutable structures to prevent test interference:

const data = Object.freeze({ a: 1 });
data.a = 2; // TypeError in strict mode

Solution 4: Handling Floating Point Precision Issues

Use closeTo instead of direct equality:

expect(1.005).to.be.closeTo(1.01, 0.01);

Solution 5: Ensuring Proper Cleanup in Tests

Reset state between test runs:

beforeEach(() => resetDatabase());

Best Practices for Reliable Chai Assertions

  • Always use deep.equal for object comparisons.
  • Use chai-as-promised for asynchronous assertions.
  • Ensure test data is immutable to prevent unintended state mutations.
  • Use closeTo for floating point number comparisons.
  • Reset test state before each test execution.

Conclusion

Flaky assertions in Chai can lead to unreliable test results and debugging difficulties. By using correct equality checks, handling async operations properly, and ensuring state isolation, developers can improve test reliability and confidence in their code.

FAQ

1. Why do my Chai object comparisons fail?

Ensure you use deep.equal instead of equal when comparing objects.

2. How do I handle async assertions in Chai?

Use chai-as-promised to properly await asynchronous assertions.

3. What causes state mutations in tests?

Reusing test objects between assertions without resetting them can lead to state mutations.

4. How do I fix floating point assertion failures?

Use closeTo to allow for small rounding errors in floating point calculations.

5. Why does my test pass inconsistently?

Check for async race conditions, object mutations, or unhandled promise rejections.