Industry widely uses unstructured merge tools that rely on textual analysis to detect and resolve conflicts between code contributions. Semistructured merge tools go further by partially exploring the syntactic structure of code artifacts, and, as a consequence, obtaining significant merge accuracy gains for Java-like languages. To understand whether semistructured merge and the observed gains generalize to other kinds of languages, we implement two semistructured merge tools for JavaScript, and compare them to an unstructured tool. We find that current semistructured merge algorithms and frameworks are not directly applicable for scripting languages like JavaScript. By adapting the algorithms, and studying 10,345 merge scenarios from 50 JavaScript projects on GitHub, we find evidence that our JavaScript tools report fewer spurious conflicts than unstructured merge, without compromising the correctness of the merging process. The gains, however, are much smaller than the ones observed for Java-like languages, suggesting that semistructured merge advantages might be limited for languages that allow both commutative and non-commutative declarations at the same syntactic level.
Thu 14 NovDisplayed time zone: Tijuana, Baja California change
16:00 - 17:40 | Untangling and MergingResearch Papers at Cortez 2&3 Chair(s): Iftekhar Ahmed University of California at Irvine, USA | ||
16:00 20mTalk | The Impact of Structure on Software Merging: Semistructured versus Structured Merge Research Papers Guilherme Cavalcanti Federal University of Pernambuco, Brazil, Paulo Borba Federal University of Pernambuco, Brazil, Georg Seibt University of Passau, Sven Apel Saarland University Pre-print | ||
16:20 20mTalk | Semistructured Merge in JavaScript Systems Research Papers Alberto Trindade Tavares Federal University of Pernambuco, Paulo Borba Federal University of Pernambuco, Brazil, Guilherme Cavalcanti Federal University of Pernambuco, Brazil, Sergio Soares Federal University of Pernambuco Pre-print | ||
16:40 20mTalk | CLCDSA: Cross Language Code Clone Detection using Syntactical Features and API Documentation Research Papers Kawser Nafi University of Saskatchewan, Tonny Shekha Kar University of Saskatchewan, Canada, Banani Roy University of Saskatchewan, Chanchal K. Roy University of Saskatchewan, Kevin Schneider University of Saskatchewan | ||
17:00 20mTalk | B2SFinder: Detecting Open-Source Software Reuse in COTS Software Research Papers Muyue Feng Institute of Information Engineering, Chinese Academy of Sciences, Zimu Yuan Institute of Information Engineering, Chinese Academy of Sciences, Feng Li Institute of Computing Technology at Chinese Academy of Sciences, China, Gu Ban Institute of Information Engineering, Chinese Academy of Sciences, Yang Xiao Institute of Information Engineering, Chinese Academy of Sciences & School of Cyber Security, University of Chinese Academy of Sciences, Shiyang Wang Institute of Information Engineering, Chinese Academy of Sciences, Qian Tang Institute of Information Engineering, Chinese Academy of Sciences, He Su Institute of Information Engineering, Chinese Academy of Sciences, Chendong Yu University of Chinese Academy of Sciences, Jiahuan Xu Institute of Information Engineering, Chinese Academy of Sciences, Aihua Piao Institute of Information Engineering, Chinese Academy of Sciences, Jingling Xue UNSW Sydney, Wei Huo Institute of Information Engineering, Chinese Academy of Sciences | ||
17:20 20mTalk | CoRA: Decomposing and Describing Tangled Code Changes for Reviewer Research Papers Min Wang Peking University, Zeqi Lin Microsoft Research, China, Yanzhen Zou Peking University, Bing Xie Peking University | ||