Debugging Python code, or any code, is often a challenging and time consuming task, especially when dealing with large and complex code bases. Traditional Python debugging and Python code review tools that are able to detect simple problems, usually related to style, syntax, as well as commonly listed security vulnerabilities. These tools can often be integrated into an IDE and certainly provide value in the development process. At the same time they lack the ability to detect complex problems that require contextual understanding of the code base.
AI has the potential to revolutionize the way runtime errors are detected and prevented in software development through the use of static code analysis. While the field is still in its early stages, research and development in this area are advancing rapidly, and companies such as Metabob have already presented AI-based capabilities for detecting runtime errors. As AI algorithms continue to improve, it is likely that AI will become the standard tool for software engineers to prevent coding errors.
Debugging is a means to tackle problems, but what if it is possible to solve debugging itself? In this post, we are looking at the open-source community and how it inspired a new way to review and ultimately debug codebases. Follow Massi Genta and his team on their quest to craft the ultimate debugging tool.
Within the past few years, the tech industry has consistently and reliably added jobs. The demand for skilled tech labor such as software developers, testers, and quality assurance analysts has developed an extremely competitive market...