Logic Mutations: The Bugs Your Tests Are Secretly Ignoring

<p>An AI coding agent implements a feature, generates tests, runs them, and opens a pull request with a green build.</p> <p>That looks like independent verification. It often is

<h2> The Asymmetry of Change: Why Your Tests Are Looking the Wrong Way </h2> <p>A passing build is often treated as a certificate of correctness. In reality, it's a narrow

<p>An agent patch that passes its own tests is a baseline, not a verdict. The same model wrote the code and the tests, so both share the same blind spots. Mutation testing scores

<h3> Intro </h3> <p>There's a pitch behind every "AI writes your tests too" workflow: more coverage, less manual toil, a safety net that used to take a sprint now takes

<h1> AI Writes Your Tests. Here's What It Systematically Misses. </h1> <p>We ran a tool called Optinum against 16 real bugs from SWE-bench Verified — a dataset of production OSS

<p>Last month I asked a senior candidate the same question I ask everyone. "Tell me about a flaky test you fixed and how you fixed it."</p> <p>She paused and said, "I just added a

<p>Built a .NET invoicing library with Claude Code over about a week. Zero dependencies, VAT and GST arithmetic, JSON and CSV export, the usual. By the third phase I had 202 tests