Towards Automatic Updates of Software Dependencies based on Artificial Intelligence

Abstract

Software reusability encourages developers to heavily rely on a variety of third-party libraries and packages, resulting in dependent software products. Often ignored by developers due to the risk of breakage but dependent software have to adopt security and performance updates in their external dependencies. Existing work advocates a shift towards Automatic updation of dependent software code to implement update dependencies. Emerging automatic dependency management tools notify the availability of new updates, detect their impacts on dependent software and identify potential breakages or other vulnerabilities. However, support for automatic source code refactoring to fix potential breaking changes (to the best of my current knowledge) is missing from these tools. This paper presents a prototyping tool, DepRefactor, that assist in the programmed refactoring of software code caused by automatic updating of their dependencies. To measure the accuracy and effectiveness of DepRefactor, we test it on various students project developed in C#.