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ICPC 2020
Mon 13 - Wed 15 July 2020
co-located with ICSE 2020
Tue 14 Jul 2020 00:12 - 00:24 at ICPC - Session 3: Faults Chair(s): Mohamed Wiem Mkaouer

Information Retrieval (IR) methods have been recently employed to provide automatic support for bug localization tasks. However, for an IR-based bug localization tool to be useful, it has to achieve adequate retrieval accuracy. Lower precision and recall can leave developers with large amounts of incorrect information to wade through. To address this issue, in this paper, we systematically investigate the impact of combining various IR methods on the retrieval accuracy of bug localization engines. The main assumption is that different IR methods, targeting different dimensions of similarity between artifacts, can be used to enhance the confidence in each others’ results. Five benchmark systems from different application domains are used to conduct our analysis. The results show that a) near-optimal global configurations can be determined for different combinations of IR methods, b) optimized IR-hybrids can significantly outperform individual methods as well as other unoptimized methods, and c) hybrid methods achieve their best performance when utilizing information-theoretic IR methods. Our findings can be used to enhance the practicality of IR-based bug localization tools and minimize the cognitive overload developers often face when locating bugs.

Tue 14 Jul
Times are displayed in time zone: (UTC) Coordinated Universal Time change

00:00 - 01:00
Session 3: FaultsResearch / ERA at ICPC
Chair(s): Mohamed Wiem MkaouerRochester Institute of Technology
00:00
12m
Paper
Exploiting Code Knowledge Graph for Bug Localization via Bi-directional Attention
Research
Jinglei ZhangPeking University, Rui XiePeking University, Wei YePeking University, Yuhan ZhangPeking University, Shikun ZhangPeking University
Media Attached
00:12
12m
Paper
On Combining IR Methods to Improve Bug Localization
Research
Saket KhatiwadaLouisiana State University, Miroslav TushevLouisiana State University, Nash MahmoudLouisiana State University
Media Attached
00:24
12m
Paper
An Empirical Study on Critical Blocking Bugs
Research
Hao RenDepartment of Computer Science and Technology, Nanjing University, Yanhui LiDepartment of Computer Science and Technology, Nanjing University, Lin ChenNanjing University
Media Attached
00:36
12m
Paper
Improving the Accuracy of Spectrum-based Fault Localization for Automated Program Repair
ERA
Tetsushi Kuma Osaka University, Yoshiki HigoOsaka University, Shinsuke MatsumotoOsaka University, Shinji KusumotoOsaka University
Media Attached
00:48
12m
Paper
Automatic Android Deprecated-API Usage Update by Learning from Single Updated Example
ERA
Stefanus Agus HaryonoSingapore Management University, Ferdian ThungSingapore Management University, Hong Jin KangSchool of Information Systems, Singapore Management University, Lucas SerranoSorbonne University/Inria/LIP6, Gilles MullerInria, Julia Lawall INRIA, David LoSingapore Management University, Lingxiao JiangSingapore Management University
Media Attached