ContextAug:model-domain failing test augmentation with contextual information  

作　　者：Zhuo ZHANG Jianxin XUE Deheng YANG Xiaoguang MAO 

机构地区：[1]School of Information Technology and Engineering,Guangzhou College of Commerce,Guangzhou 511363,China [2]School of Computer and Information Engineering,Institute for Artificial Intelligence,Shanghai Polytechnic University,Shanghai 201209,China [3]College of Computer,National University of Defense Technology,Changsha 410073,China

出　　处：《Frontiers of Computer Science》2024年第2期43-60,共18页中国计算机科学前沿（英文版）

摘　　要：In the process of software development,the ability to localize faults is crucial for improving the efficiency of debugging.Generally speaking,detecting and repairing errant behavior at an early stage of the development cycle considerably reduces costs and development time.Researchers have tried to utilize various methods to locate the faulty codes.However,failing test cases usually account for a small portion of the test suite,which inevitably leads to the class-imbalance phenomenon and hampers the effectiveness of fault localization.Accordingly,in this work,we propose a new fault localization approach named ContextAug.After obtaining dynamic execution through test cases,ContextAug traces these executions to build an information model;subsequently,it constructs a failure context with propagation dependencies to intersect with new model-domain failing test samples synthesized by the minimum variability of the minority feature space.In contrast to traditional test generation directly from the input domain,ContextAug seeks a new perspective to synthesize failing test samples from the model domain,which is much easier to augment test suites.Through conducting empirical research on real large-sized programs with 13 state-of-the-art fault localization approaches,ContextAug could significantly improve fault localization effectiveness with up to 54.53%.Thus,ContextAug is verified as able to improve fault localization effectiveness.

关 键 词：CONTEXT fault localization test cases 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]