Automated test generation

Problem

Developers skip writing tests under deadline pressure, leading to low coverage and fragile releases. Retroactively adding tests is tedious and often deprioritized sprint after sprint.

Solution

The AI agent reads function signatures, docstrings, and usage patterns to generate meaningful test cases—including edge cases, error paths, and integration scenarios. Tests follow the project's existing framework and naming conventions so they integrate seamlessly into CI.

Benefits

• 40–60% coverage increase with minimal effort
• Edge cases and error paths covered automatically
• Tests follow existing framework conventions
• Faster PR cycles with pre-written test suites

How to get started

1. 1

   Connect to repository

   Link your GitHub or GitLab repo. The agent indexes the codebase, identifies the test framework in use (Jest, pytest, JUnit, etc.), and maps untested functions.

2. 2

   Generate test suites

   Select files, modules, or let the agent prioritize by coverage gaps. It generates tests with descriptive names, assertions, and mocks—ready to run locally or in CI.

3. 3

   Review and merge

   Tests appear as a PR or local branch. Review generated tests, adjust assertions if needed, and merge. The agent learns from your feedback to improve future suggestions.

Recommended tools

Cursor, Codium, GitHub Copilot. See the full list on the AI Coding Agent pillar page.