PFI–TT: Intelligent Software Refactoring Bot for Continuous Integration

Award ID: 2216768

The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project focuses on issues of economic impact: improvement of the software and systems that underpin our national infrastructure. By adopting the proposed technology, software development teams may avoid critical quality and security issues. This intelligent refactoring technology enables organizations to better maintain their software as it ages and better align their maintenance efforts with their priorities. This innovation seeks to deliver continuous will also provide training opportunities for students in technological innovation and entrepreneurship. This project focuses on developing scalable methods to determine when and how to integrate developer feedback to semi-automate code refactoring for continuous integration environments while adhering to industry standards to align the effort with their commercialization objectives. Software refactoring is recognized as the key component for maintaining high quality software by restructuring existing code and reducing technical debt. Refactoring requires programmers to review, detect, and fix quality issues to improve software performance. However, refactoring is difficult to achieve and often neglected not only due to a pressure to meet release deadlines, but also due to the constraints imposed by manual refactoring as well as lack of technical skill in restructuring complex systems. The traditional root-canal refactoring process is not practical since it is time consuming and hard to integrate in the development pipelines. Hence, new refactoring tool must deliver timely support for code repair. The goal of this technology is to clearly exhibit the feasibility of combining interactive, semi-automated, refactoring technology with continuous integration via an artificial intelligence-based bot and demonstrate the implemented concept at large-scale. The effort will also support multiple programming languages including quantitative (such as accuracy, relevance, and performance) and qualitative (such as programmers' comments) aspects. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Samir Iqbal