OpenSZZ: A Free, Open-Source, Web-Accessible Implementation of the SZZ Algorithm
The accurate identification of defect-inducing commits represents a key problem for researchers interested in studying the naturalness of defects and defining defect prediction models. To tackle this problem, software engineering researchers have relied on and proposed several implementations of the well-known SliwerskiZimmermann-Zeller (SZZ) algorithm. Despite its popularity and wide usage, no open-source, publicly available, and web-accessible implementation of the algorithm has been proposed so far. In this paper, we prototype and make available one such implementation for further use by practitioners and researchers alike. The evaluation of the proposed prototype showed competitive results and lays the foundation for future work. This paper outlines our prototype, illustrating its usage and reporting on its evaluation in action.
Tue 14 JulDisplayed time zone: (UTC) Coordinated Universal Time change
07:00 - 08:00 | Session 5: For ResearchersResearch / ERA / Tool Demonstration at ICPC Chair(s): Bin Lin Università della Svizzera italiana (USI) | ||
07:00 15mPaper | A Literature Review of Automatic Traceability Links Recovery for Software Change Impact Analysis Research Thazin Win Win Aung University of Technology Sydney, Yulei Sui University of Technology Sydney, Australia, Huan Huo University of Technology Sydney Media Attached | ||
07:15 15mPaper | Improving Code Search with Co-Attentive Representation Learning Research Jianhang Shuai School of Big Data & Software Engineering, Chongqing University, Ling Xu School of Big Data & Software Engineering, Chongqing University, Chao Liu Zhejiang University, Meng Yan School of Big Data & Software Engineering, Chongqing University, Xin Xia Monash University, Yan Lei School of Big Data & Software Engineering, Chongqing University Media Attached | ||
07:30 15mPaper | OpenSZZ: A Free, Open-Source, Web-Accessible Implementation of the SZZ Algorithm Tool Demonstration Valentina Lenarduzzi LUT University , Fabio Palomba University of Salerno, Davide Taibi Tampere University , Damian Andrew Tamburri Jheronimus Academy of Data Science Media Attached | ||
07:45 15mPaper | Staged Tree Matching for Detecting Code Move across Files ERA Akira Fujimoto Osaka University, Yoshiki Higo Osaka University, Junnosuke Matsumoto , Shinji Kusumoto Osaka University Media Attached |