Tasks, Challenges, and Paths Towards AI for Software Engineering

Alex Gu, Naman Jain, Wen-Ding Li, Manish Shetty, Kevin Ellis, Koushik Sen, Armando Solar-Lezama

Track: long paper (up to 9 pages)

Keywords: ai for code

Abstract: AI for software engineering has made remarkable progress, becoming a notable success within generative AI. Despite this, achieving fully automated software engineering is still a significant challenge, requiring research efforts across both academia and industry. In this position paper, our goal is threefold. First, we provide a taxonomy of measures and tasks to categorize work towards AI software engineering. Second, we outline the key bottlenecks permeating today's approaches. Finally, we highlight promising paths towards making progress on these bottlenecks to guide future research in this rapidly maturing field.

Anonymization: This submission has been anonymized for double-blind review via the removal of identifying information such as names, affiliations, and identifying URLs.

Submission Number: 7