Catalog
concept#Software Engineering#Quality Assurance#DevOps#Observability

.NET Testing Framework

A conceptual framework for tools, libraries and practices for automated testing of .NET applications.

The .
Established
Medium

Classification

  • Medium
  • Technical
  • Architectural
  • Intermediate

Technical context

CI systems (Azure DevOps, GitHub Actions)Test runners (dotnet test, vstest, xUnit)Coverage tools (coverlet, ReportGenerator)

Principles & goals

Tests should run fast, deterministically, and in isolation.Clear separation between unit, integration and E2E tests.Automation and CI integration as a norm.
Build
Team, Domain

Use cases & scenarios

Compromises

  • Overreliance on test suites can replace monitoring.
  • Insufficient tests create false confidence.
  • Slow tests slow down development cycles.
  • Prioritize small, deterministic unit tests.
  • Complement unit tests with targeted integration tests.
  • Use test parallelism and caching in CI.

I/O & resources

  • Source code and build artifacts
  • Test data and migration scripts
  • CI/CD infrastructure and runners
  • Test reports and coverage metrics
  • Automated gate results for deployments
  • Failure reports and reproducible scenarios

Description

The .NET Testing Framework concept describes the ecosystem of tools, libraries, and patterns used to create automated tests for .NET applications. It covers unit, integration, and end-to-end testing and promotes testability, isolation, and maintainable test suites. It supports CI execution and local developer workflows.

✔

  • Early defect detection and fewer regressions.
  • Improved design through testable components.
  • Safer, automated releases with gate criteria.

✖

  • High initial effort for test infrastructure.
  • Flaky tests possible due to external dependencies.
  • Maintenance effort for test data and mocks.

  • Test runtime

    Total duration of the test suite; affects feedback cycle.

  • Failure rate per test run

    Frequency of failing tests, including flaky rate.

  • Coverage of critical paths

    Percentage of covered business- or security-critical paths.

Library with extensive unit tests

An internal utility package uses xUnit and mocking to achieve 95% coverage on critical paths.

Microservice integration test with container setup

Integration tests spin up dependent services in Docker Compose and validate API flows.

End-to-end test as pipeline gate

E2E tests in staging block deployments on critical regression failures.

1

Evaluate existing tests and choose a standard framework.

2

Define test categories, runtimes and CI gates.

3

Set up infrastructure (runners, caching, containers).

4

Train the team and introduce migration rules.

⚠️ Technical debt & bottlenecks

  • Outdated test APIs without refactoring.
  • Unstructured test data and missing seeds.
  • Slow, non-parallel test suites.
slow testsmissing test dataexternal dependencies
  • High coverage target without focus on critical paths.
  • Running integration tests directly against production data.
  • Test-only libraries that are not maintained.
  • Ignoring root causes of flaky tests and only rerunning.
  • Insufficient isolation leads to non-deterministic results.
  • Too broad integration tests instead of focused endpoint validation.
C#/.NET development experienceKnowledge of mocking and test doublesCI/CD and container fundamentals
Fast feedback cyclesDeterministic test executionSeamless CI integration
  • • Limited CI resources (agents/timeouts).
  • • Legacy code without clear interfaces.
  • • Regulatory requirements for test data.