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ASE 2020
Mon 21 - Fri 25 September 2020 Melbourne, Australia
Thu 24 Sep 2020 03:00 - 03:10 at Wombat - AI for Software Engineering (4) Chair(s): Hoa Khanh Dam

Given a bug report of a project, the task of locating the faults of the bug report is called fault localization. To help programmers in the fault localization process, many approaches have been proposed, and have achieved promising results to locate faulty files. However, it is still challenging to locate faulty methods, because many methods are short and do not have sufficient details to determine whether they are faulty. In this paper, we present BugPecker, a novel approach to locate faulty methods based on its deep learning on revision graphs. Its key idea includes (1) building revision graphs and capturing the details of past fixes as much as possible, and (2) discovering relations inside our revision graphs to expand the details for methods and calculating various features to assist our ranking. We have implemented BugPecker, and evaluated it on three open source projects. The early results show that BugPecker achieves a mean average precision (MAP) of 0.263 and mean reciprocal rank (MRR) of 0.291, which improve the prior approaches significantly. For example, BugPecker improves the MAP values of all three projects by five times, compared with two recent approaches such as DNNLoc-m and BLIA 1.5.

Thu 24 Sep

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02:20 - 03:20
AI for Software Engineering (4)Research Papers / NIER track at Wombat
Chair(s): Hoa Khanh Dam University of Wollongong
Detecting and Explaining Self-Admitted Technical Debts with Attention-based Neural Networks
Research Papers
Xin Wang Wuhan University, Jin Liu Wuhan University, Li Li Monash University, Australia, Xiao Chen Monash University, Xiao Liu School of Information Technology, Deakin University, Hao Wu Yunnan University
OCoR: An Overlapping-Aware Code Retriever
Research Papers
Qihao Zhu Peking University, Zeyu Sun Peking University, Xiran Liang Peking University, Yingfei Xiong Peking University, China, Lu Zhang Peking University, China
BugPecker: Locating Faulty Methods with Deep Learning on Revision Graphs
NIER track
Junming Cao School of Software, Shanghai Jiao Tong University, Shouliang Yang School of Software, Shanghai Jiao Tong University, Wenhui Jiang School of Software, Shanghai Jiao Tong University, Hushuang Zeng School of Software, Shanghai Jiao Tong University, Beijun Shen School of Software, Shanghai Jiao Tong University, Hao Zhong Shanghai Jiao Tong University