CAREER: Democratizing Algorithmic Program Synthesis

Program synthesis is the process of automatically generating programs that meet the user's intent. As one of the most central research problems in computer science and AI, program synthesis is extremely challenging. Recent years have seen success stories of algorithmic program synthesis in real-life code generation.

Despite the promising progress, modern-day synthesizers can still only be mastered by experts. One vital problem is that program synthesis has not been integrated to the traditional software development process that most regular programmers are familiar with. This project takes a major step toward lowering the barrier of algorithmic program synthesis for regular programmers.

The key insight is that the challenging steps in the current synthesis process can be perceived as part of the synthesis task and incorporated into the synthesis algorithms. More specifically, this project develops new synthesis frameworks and algorithms that enable scalable, quantitative, library-based program synthesis without hand-crafted objective functions, library models or decomposition strategies.

This project aims to make software development easier for regular programmers by transforming program synthesizers into more natural and accessible tools. The project also has the potential to significantly broaden the base of people who can overcome the programming-related challenges in their own fields. The project will provide valuable training for graduate students, enable novel pedagogical approaches and material suitable for compiler-related, synthesis-related and networking-related courses, and provide new computational thinking assessments and tutorials for broadening participation of K-12 and undergraduate students for broader community.

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.