After generating fuzz tests with LLMs, the next important step is verifying that these tests are of high quality and ensuring they run and work as intended. CI Fuzz can now automatically build the generated fuzz test, run it, and perform a health check to assess its quality and refine it further if it doesn't pass the health check. Watch the video to see it in action.

Creating high-quality fuzz tests is essential for efficient fuzz testing. However, crafting these tests is a time-consuming, manual process, which has become a major barrier to the widespread adoption of fuzz testing. Watch the video to see how CI Fuzz can automatically generate high-quality fuzz tests by leveraging LLMs and static analysis.

The first step to start fuzzing is to identify what part of the software you want to fuzz. You definitely want to fuzz the most critical functions/APIs—those that exercise a significant amount of code and trigger key functionalities. However, manually identifying these targets can be time-consuming and challenging. Watch the video to see how CI Fuzz can automatically prioritize functions for fuzzing.

If you want to automate your code analysis to identify the best fuzzing targets, you can do so with CI Fuzz. In the previous video, Khaled demonstrated how CI Fuzz automatically prioritized functions to test. But what if you already have unit or fuzz tests? CI Fuzz can analyze an LCOV coverage report and identify less-covered functions. These functions will now receive higher scores, highlighting them as top targets for new tests.