Although there is much research advancing state-of-art of program transformation tools, their application in industry source code change problems has not yet been gauged. In this context, the purpose of this paper is to better understand developer familiarity and comfort with these languages by conducting a survey. It poses, and answers, four research questions to understand how frequently source code transformation languages are applied to refactoring tasks, how well-known these languages are in industry, what developers think are obstacles to adoption, and what developer refactoring habits tell us about their current use, or underuse, of transformation languages. The results show that while source code transformation languages can fill a needed niche in refactoring, research must motivate their application. We provide explanations and insights based on data, aimed at the program transformation and refactoring communities, with a goal to motivate future research and ultimately improve industry adoption of transformation languages for refactoring tasks.
Date of creation, presentation, or exhibit
Department, Program, or Center
Software Engineering (GCCIS)
Christian D. Newman, Mohamed Wiem Mkaouer, Michael L. Collard, and Jonathan I. Maletic. 2018. A study on developer perception of transformation languages for refactoring. In Proceedings of the 2nd International Workshop on Refactoring (IWoR 2018). Association for Computing Machinery, New York, NY, USA, 34–41. DOI:https://doi.org/10.1145/3242163.3242170
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