Bug fixing is expensive and the study of it is a hot research topic in software engineering. During the bug fixing process, developers leverage various software artifacts (e.g., bug reports, commits, log files, source files, etc.) and explore multi-source heterogeneous information (Q&A websites, web resources, software communities, etc.) to reproduce the bugs, locate the bugs, identify candidate fixing solutions, apply the fixes and validate the fixes. The rich data can indicate the important information of bug fixing, which can guide developers to resolve bugs. For example, a bug report not only shows the details of the reported bug, but also shows the potential method of bug fixing. Therefore, how to analyze and utilize these data is an important step of bug fixing.
The workshop will focus on intelligent bug fixing. Generally, bug fixing process includes bug understanding (i.e., bug reproduction, severity/priority verification, bug summarization, bug classification, bug knowledge extraction), bug localization, bug fixing, and bug validation. By using data mining, information retrieval, machine learning, natural language processing, artificial intelligence technologies, visualization technologies, human-computer interaction technologies and code analysis technologies, a series of new automated algorithms will be proposed to improve the performance of developers’bug fixing process. In this workshop, we solicit high-quality contributions with consolidated and thoroughly evaluated application-oriented research results in the area of intelligent bug fixing that are worthy of archival publication in SANER 2019 workshop proceeding. It is intended to (i) provide a summary of research that advances intelligent bug fixing using multiple data analysis and processing techniques, and (ii) serve as a comprehensive collection of some of the current state-of-the-art technologies within this content. The workshop will collaborate with the International Conference on Software Analysis, Evolution, and Reengineering (SANER 2019).
Submissions from academia and industry reporting original research results or practical experience are welcome. All submissions should consider the practical application of the idea through case studies, experiments, empirical validation, or systematic comparisons with other approaches already in practice. We strongly encourage authors to make available all data and software they use in their work, in order to allow for replication of their results.
The topics relevant to the Special Issue include (but are not limited to) the following.
The submissions must comply with the format of IEEE Proceedings. We invite the authors of selected papers to submit their extended versions to a special issue of IEEE Transactions on Reliability or IEEE Access.
Submission Page:click here
The Hong Kong University of Science and Technology, Hong Kong, China (scc@cse.ust.hk)
Yangzhou University, China (xbsun@yzu.edu.cn)
Harbin Engineering University, China (cstzhang@hrbeu.edu.cn)
Yan Cai | Chinese Academy of Sciences |
Lin Chen | Nanjing University |
Yucong Duan | Hainan University |
He Jiang | Dalian University of Technology |
Jing Jiang | Beihang University |
Sunghun Kim | Hong Kong University of Science and Technology |
Xianglong Kong | Southeast University |
Xuan-Bach D. Le | Carnegie Mellon University |
Bin Li | Yangzhou University |
Bixin Li | Southeast University |
Li Li | Monash University |
Yun Lin | National University of Singapore |
Hui Liu | Beijing Institute of Technology |
Yepang Liu | Southern University of Science and Technology |
Xiapu Luo | Hong Kong Polytechnic University |
Lei Ma | Harbin Institute of Technology |
Martin Monperrus | KTH Royal Institute of Technology |
Xin Peng | Fudan University |
Weiyi Shang | Concordia University |
Shin Yoo | KAIST |
Shin Hwei Tan | Southern University of Science and Technology |
Chuanqi Tao | Nanjing University of Aeronautics and Astronautics |
Shaowei Wang | Queen's University |
Zan Wang | Tianjin University |
Rongxin Wu | Hong Kong University of Science and Technology |
Xin Xia | Monash University |
Yingfei Xiong | Peking University |
Chang Xu | Nanjing University |
Jifeng Xuan | Wuhan University |
Hao Zhong | Shanghai Jiao Tong University |
Submitted papers must have been neither previously accepted for publication nor concurrently submitted for review in another journal, book, conference, or workshop.
All submissions must come in PDF format and conform, at time of submission, to the IEEE Conference Proceedings Formatting Guidelines (title in 24pt font and full text in 10pt font, LaTEX users must use \documentclass[10pt,conference]{IEEEtran} without including the compsoc or compsocconf option. Also, papers must comply with the IEEE Policy on Authorship.
All submissions must be in English. Full paper submissions should not exceed 10 pages (the last 2 pages can be used for references). Short paper submissions should not exceed 6 pages and poster paper submission should not exceed 2 pages. We invite the authors of selected papers to submit their extended versions to a special issue of IEEE Transactions on Reliability or IEEE Access.
Note that we conduct double-blind review process, please check the deals at here.
Submission Page:click here
Abstract:
The core of bug fixing is to synthesize a correct program to replace the buggy program. Due to the well-known problem of weak specification, the synthesized program should not only pass the tests but should have a high probability of being correct. In this talk, I will introduce our recent work on the learning to synthesize framework to address this problem. Based on a training set of programs and their contexts, this framework combines four tools including rewriting rules, machine learning, constraint solving, and search algorithms to find the most likely programs under a context. We have instantiated the framework for program repair and code generation, both showing significant improvements over the state-of-the-art.
About the Speaker:
Yingfei Xiong is an associate professor at Peking University. He got his Ph.D. degree from the University of Tokyo in 2009 and worked as a postdoctoral fellow at University of Waterloobetween 2009 and 2011. His research interests lie in software engineering and programming language in general, and bug fixing in particular. He has proposed a set of theories, methodologies, and techniques for bug fixing. For example, the repair approach, ACS, is the first one that achieved >70% precision on a general benchmark; in terms of evolutionary bugs, the delta-based bidirectional transformation framework is now considered as one of the standard types of bidirectional transformation frameworks. His work has been adopted by the industry, such as a Linux kernel configuration project, the Huawei company, and the YanCloud DaaS system.
Time Schedule | 24 Feb. 2019, Sunday |
08:00 – 09:00 | Registration |
09:00 - 09:05 | Opening |
09:05 - 09:50 | Keynote Talk: Learning to Synthesize Yingfei Xiong, Peking University |
09:50 - 10:30 | Technical Session 1: Analysis and Prediction 1.An empirical study on combining source selection and transfer learning for cross-project defect prediction(Wanzhi Wen, Bin Zhang, Xiang Gu and Xiaolin Ju) 2.Automatically Identifying Bug Entities and Relations for Bug Analysis(Dingshan Chen, Bin Li, Cheng Zhou and Xuanrui Zhu) |
10:30 - 11:00 | Coffee/Tea Break |
11:00 - 12:30 | Technical Session 2: Localization and Repair 3. A Comprehensive Study of Automatic Program Repair on the QuixBugs Benchmark(He Ye, Matias Martinez, Thomas Durieux and Martin Monperrus) 4. Automatic Software Merging Using Automated Program Repair(Xing Xiaoqian and Katsuhisa Maruyama) 5. NFL: Neighbor-based Fault Localization Technique (Béla Vancsics) 6. A New Interactive Fault Localization Method with Context Aware User Feedback(Ferenc Horváth, Victor Schnepper Lacerda, Árpád Beszédes, László Vidács and Tibor Gyimóthy) |
12:30h - 14:00 | Lunch |
Conference Room 5 天风厅