Claude-generated .NET tests can look complete and still miss the regression they are meant to catch. The author walks through tracing assertions back to their inputs, checking mock boundaries, and verifying that a test fails for the intended reason. It is a practical review checklist for anyone accepting agent-written tests into a C# codebase.
The author shows how to test the 404 branch of a minimal API endpoint by calling the handler directly instead of booting WebApplicationFactory. Typed result unions such as Results<Ok<T>, NotFound> make the return type a compiler-checked contract. The approach gives fast, readable unit tests, while the author keeps a thin layer of integration tests for routing, binding and middleware.
The Azure Cosmos DB blog shows how to test a database-backed feature against the Azure Cosmos DB Emulator running in Docker, then run the same tests in GitHub Actions. The example is a Python demo app, but the pattern applies to any .NET service that talks to Cosmos DB. Each pull request update runs against a fresh emulator, so you can check that a write reached storage and changed the answer, not just that the HTTP call returned 200.
The Critter Stack team has described the test automation strategy behind Bobcat, its new spec-driven integration testing framework for .NET. The post, written by Jeremy Miller, lays out practices for tests that ship confidence, are cheap to write, run fast, stay reliable and explain their failures. It is a useful reference for .NET teams who want their CI results to be trusted as a merge gate.
Mehdi Mohseni argues that coding agents now write much of the code, but developers still need the judgment to spot code that looks right and is wrong. Using ASP.NET Core examples, he shows how generated code can compile, pass tests and still hide a fail-open security check or a silent misconfiguration. A practical read for anyone reviewing agent output.