Catalog
method#Quality Assurance#Integration#Observability#Security

API Testing

Method for systematic verification of APIs using automated and manual tests to validate contracts, error handling, performance and security.

API testing is a structured method for verifying interfaces using automated and manual tests.
Established
Medium

Classification

  • Medium
  • Technical
  • Design
  • Intermediate

Technical context

CI systems (e.g. GitHub Actions, Jenkins)Test frameworks (e.g. Rest Assured, pytest)Mocking and service virtualization (e.g. WireMock)

Principles & goals

Specify and version contracts explicitly.Prioritize automation: run early and continuously.Combine isolated tests (mocks) and validated integration.
Build
Team, Domain

Use cases & scenarios

Compromises

  • False security assumptions from incomplete tests.
  • High maintenance effort with rapid API changes.
  • False sense of security after green tests without production monitoring.
  • Use contract-first development and automatic validation.
  • Separate isolated unit/mock tests from end-to-end checks.
  • Integrate test results into monitoring and postmortems.

I/O & resources

  • API specification (e.g. OpenAPI)
  • Test data and test accounts
  • Access to test and staging environments
  • Automated test reports (pass/fail)
  • Defect tickets with reproduction steps
  • Regression suite for CI/CD

Description

API testing is a structured method for verifying interfaces using automated and manual tests. It validates contracts, error handling, performance, and security of APIs during development and CI/CD. The practice aims at early defect detection, reliable integrations and reproducible regression suites including test data, mocks, load scenarios and pipeline integration.

✔

  • Early defect detection along the development pipeline.
  • More stable integrations and clearer API contracts.
  • Automated regressions reduce manual verification effort.

✖

  • Mock-based tests may underestimate real production conditions.
  • Effort required for test data management and environment provisioning.
  • Complex end-to-end scenarios require additional infrastructure.

  • Test coverage (API endpoints)

    Proportion of endpoints covered by automated tests.

  • Average test suite execution time

    Average duration of a full test run in CI.

  • Defect detection rate per release

    Number of defects found by API tests per release.

Microservice architecture with OpenAPI contracts

Teams use automated API tests against OpenAPI specifications to ensure compatible integrations.

Regression tests in CI for payment API

Automated regressions prevent regressions in critical payment flows after changes.

Security checks for authentication endpoints

Special tests validate token handling, scope checks and rate limits.

1

Capture and version the specification (OpenAPI).

2

Write automated tests for contract, error and performance cases.

3

Integrate tests into CI/CD and define gate criteria.

4

Provide mocks, test data and synthetic load scenarios.

⚠️ Technical debt & bottlenecks

  • Unstructured test code without maintenance guidelines.
  • Outdated mocks that don't reflect production behavior.
  • Lack of test data strategy for reproducible runs.
test-data-setupthird-party-dependenciesrate-limits
  • Running API tests only sporadically before release.
  • Using mocks as the only verification for critical flows.
  • Writing tests without clearly defined acceptance criteria.
  • Test data not isolated; tests influence each other.
  • Missing authentication data blocks automated runs.
  • Excessive dependence on unstable third-party services.
Understanding of HTTP, REST and API conceptsKnowledge of test automation and CIScripting and working with test frameworks
Explicit API contracts (contract-first)Automatable test pipelines and CI integrationObservability and monitoring for validation
  • • Limited availability of real test environments
  • • Requirement for valid authentication credentials
  • • Costs for load and integration environments