AI coding assistants like GitHub Copilot and ChatGPT are revolutionizing test generation, but they often create redundant tests. A developer discovered that AI-generated tests for a simple calculator had a 72% redundancy rate. Out of 54 tests, 39 were exact duplicates, 168 were subset duplicates, and 45 were similar test pairs. This issue arises because these tools don't check for coverage duplication.

The developer built TestIQ to address this problem. TestIQ analyzes test execution patterns rather than just comparing code text. It collects coverage data, compares execution patterns, and provides interactive HTML reports to identify and visualize duplicate tests. This tool can detect exact duplicates, subset duplicates, and similar tests based on configurable thresholds.

TestIQ has shown promising results in real-world applications. In a production Django application, it reduced the test suite from 847 to 612 tests, leading to a 28% faster CI run without any loss in coverage. The tool integrates seamlessly with CI/CD pipelines, automatically blocking PRs with duplicate tests.

Developers can try TestIQ with a demo that analyzes an AI-generated calculator test suite. The tool is open-source and actively developed, with contributions welcome. This solution addresses a growing challenge in software development as AI tools become more prevalent in generating test cases.