Investigate Code Explanation Techniques and Share Your Insights

This blog post is about the 24th day of the 30-day AI Testing Challenge, exploring code interpretation techniques and sharing insights. The article may introduce different code interpretation techniques, such as explainable AI, model interpretation, and interpretable machine learning, and discuss their applications in the testing domain. The author may share their understanding and experience in using these techniques, as well as insights into their advantages, challenges, and potential application areas. By sharing insights into code interpretation techniques, readers will gain an understanding of the author’s exploration and thoughts on new technologies and methods in AI testing, as well as expectations and prospects for future developments. This series aims to provide a platform for testing professionals to understand and explore new technologies and methods in AI testing and to promote further research and application of AI in the testing domain.