Variability-Aware Differencing with DiffDetectiveBest Demo Paper
Diff tools are essential in developers’ daily workflows and software engineering research. Motivated by limitations of traditional line-based differencing, countless specialized diff tools have been proposed, aware of the underlying artifacts’ type, such as a program’s syntax or semantics. However, no diff tool is aware of systematic variability embodied in highly configurable systems such as the Linux kernel. Our software library called DiffDetective can turn any generic diff tool into a variability-aware differencer such that a changes’ impact on the actual source code and its superimposed variability can be distinguished and analyzed. Next to graphical diff inspectors, DiffDetective provides an analysis framework for large-scale empirical analyses of version histories on a substantial body of variability-intensive software including the Linux kernel. DiffDetective has been successfully employed to, for example, explain edits, generate benchmark data, or evaluate differencing algorithms and patch mutations.
Wed 17 JulDisplayed time zone: Brasilia, Distrito Federal, Brazil change
11:00 - 12:30 | Software Maintenance and Comprehension 1Research Papers / Ideas, Visions and Reflections / Demonstrations at Acerola Chair(s): Wesley Assunção North Carolina State University | ||
11:00 18mTalk | Enhancing Function Name Prediction using Votes-Based Name Tokenization and Multi-Task Learning Research Papers Xiaoling Zhang Institute of Information Engineering, Chinese Academy of Sciences, School of Cyber Security, University of Chinese Academy of Sciences,, Zhengzi Xu Nanyang Technological University, shouguo yang Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China, Zhi Li Institute of Information Engineering, Chinese Academy of Sciences, China, Zhiqiang Shi Institute of Information Engineering, Chinese Academy of Sciences, School of Cyber Security, University of Chinese Academy of Sciences,, Limin Sun Institute of Information Engineering, Chinese Academy of Sciences, School of Cyber Security, University of Chinese Academy of Sciences, DOI Pre-print | ||
11:18 18mTalk | Only diff is Not Enough: Generating Commit Messages Leveraging Reasoning and Action of Large Language Model Research Papers Jiawei Li University of California, Irvine, David Faragó Innoopract GmbH & QPR Technologies, Christian Petrov Innoopract GmbH, Iftekhar Ahmed University of California, Irvine | ||
11:36 18mTalk | Towards Efficient Build Ordering for Incremental Builds with Multiple Configurations Research Papers Jun Lyu Nanjing University, Shanshan Li Software Institute, Nanjing University, He Zhang Nanjing University, Lanxin Yang Nanjing University, Bohan Liu Nanjing University, Manuel Rigger National University of Singapore | ||
11:54 18mTalk | Unprecedented Code Change Automation: The Fusion of LLMs and Transformation by Example Research Papers Malinda Dilhara University of Colorado Boulder, Abhiram Bellur University of Colorado Boulder, Timofey Bryksin JetBrains Research, Danny Dig University of Colorado Boulder, JetBrains Research Pre-print | ||
12:12 9mTalk | Variability-Aware Differencing with DiffDetectiveBest Demo Paper Demonstrations Paul Maximilian Bittner Paderborn University, Alexander Schultheiß Paderborn University, Benjamin Moosherr University of Ulm, Timo Kehrer University of Bern, Thomas Thüm Paderborn University Pre-print Media Attached | ||
12:21 9mTalk | From Models to Practice: Enhancing OSS Project Sustainability with Evidence-Based Advice Ideas, Visions and Reflections Nafiz Imtiaz Khan Department of Computer Science, University of California, Davis, Vladimir Filkov University of California at Davis, USA Link to publication DOI | ||