Interactive Fault Localization Using Test Information

Debugging is a time-consuming task in software development. Although various automated approaches have been proposed, they are not effective enough. On the other hand, in manual debugging, developers have difficulty in choosing breakpoints. To address these problems and help developers locate faults effectively, we propose an interactive fault-localization framework, combining the benefits of automated approaches and manual debugging. Before the fault is found, this framework continuously recommends checking points based on statements＇ suspicions, which are calculated according to the execution information of test cases and the feedback information from the developer at earlier checking points. Then we propose a naive approach, which is an initial implementation of this framework. However, with this naive approach or manual debugging, developers＇ wrong estimation of whether the faulty statement is executed before the checking point （breakpoint） may make the debugging process fail. So we propose another robust approach based on this framework, handling cases where developers make mistakes during the fault-localization process. We performed two experimental studies and the results show that the two interactive approaches are quite effective compared with existing fault-localization approaches. Moreover, the robust approach can help developers find faults when they make wrong estimation at some checking points.

一种基于反馈优化的启发式软件调试框架

基于频谱的缺陷定位方法通过生成缺陷定位报告来引导程序员识别软件缺陷。由于缺少足够的上下文信息,基于该报告识别缺陷的过程非常耗时费力。此外,在连续搜索软件缺陷的过程中,程序员先前的判断对提高缺陷定位报告的效率没有任何帮助。针对上述问题,提出一种基于反馈优化的启发式软件调试框架。程序员可以在该框架上使用可视化的启发式图迭代地识别缺陷。首先,基于静态程序切片技术分析缺陷相关信息,并通过执行跟踪技术记录实时运行信息,以DOT格式组织并可视化这些信息,构造出有助于程序员识别缺陷的启发信息;然后,提出一种优化缺陷报告的算法,该算法可以根据程序员的反馈使用正向和反向切片技术来动态调整缺陷定位报告;最后,还提出了一种增强的算法,该算法可以基于程序员的多个反馈更高效地调整缺陷定位报告。实验结果表明,提出的启发式软件调试框架可以有效提高程序调试的效率。