2024/01/26 by Haibo Wang, Wang, Haibo, Zezhong Xing +7
Computer Science · #Biology #Computer science #FOS: Computer and information sciences #Genetics #Program synthesis #Program transformation #Programming language #Software Engineering (cs.SE) #Software Engineering Research #Software Reliability and Analysis Research #Software Testing and Debugging Techniques #Transformation (genetics)
paper · pdf · doi:10.48550/arxiv.2401.15234
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2024/01/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
To reduce the complexity of software, Developers manually simplify program (known as developer-induced program simplification in this paper) to reduce its code size yet preserving its functionality but manual simplification is time-consuming and error-prone. To reduce manual effort, rule-based approaches (e.g., refactoring) and deletion-based approaches (e.g., delta debugging) can be potentially applied to automate developer-induced program simplification. However, as there is little study on how developers simplify programs in Open-source Software (OSS) projects, it is unclear whether these approaches can be effectively used for developer-induced program simplification. Hence, we present the first study of developer-induced program simplification in OSS projects, focusing on the types of program transformations used, the motivations behind simplifications, and the set of program transformations covered by existing refactoring types. Our study of 382 pull requests from 296 projects reveals that there exist gaps in applying existing approaches for automating developer-induced program simplification. and outlines the criteria for designing automatic program simplification techniques. Inspired by our study and to reduce the manual effort in developer-induced program simplification, we propose SimpT5, a tool that can automatically produce simplified programs (semantically-equivalent programs with reduced source lines of code). SimpT5 is trained based on our collected dataset of 92,485 simplified programs with two heuristics: (1) simplified line localization that encodes lines changed in simplified programs, and (2)checkers that measure the quality of generated programs. Our evaluation shows that SimpT5 are more effective than prior approaches in automating developer-induced program simplification.