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Software debugging analysis based on developer behavior data

机译:基于开发人士行为数据的软件调试分析

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摘要

Software debugging is one of the most costly activities in software development process. It mainly consists of four core tasks, namely fault detection, fault localization, fault understanding and fault fixing. Among them, fault localization normally requires the longest time and the largest efforts [1]. However, the existing fault localization methods are based on the assumption of "perfect fault understanding", which refers to that the developers fully understand the fault when they are only given the list of suspicious statements. In addition, some researchers [2, 3] doubted the effectiveness of fault localization methods, and they performed experimental studies that showed the unsatisfactory performance of some spectrum-based localization techniques.In this paper, we propose a software debugging analysis method based on developer behavior data. We particularly attempt to analyze the data collected during the debugging process and thus investigate the impact of spectrum-based fault localization on the efficiency of debugging. This study addresses two major technical challenges: (1) what information about developer's behavior is critical for improving automated software debugging; and (2) how to collect developer's debugging behavior data without any interruption and conduct a comparative analysis between different developers. After practicing and analyzing a variety of manual debugging methods, it is shown that the behavior information generated by different developers during the debugging process show a certain degree of similarity. Such similarity can in turn help speed up the debugging process.This paper makes the following three contributions:1. We define a hierarchical information structure for the collection of developer behavior data, based on which a software debugging analysis method is developed and implemented in an Eclipse plug-in DebugInfo (Section 2).2. Experimental studies are conducted, with the purpose of explaining the reasons behind the unsatisfactory performance of spectrum-based fault localization in software debugging (Section 3). 3.We carry out a qualitative comparative study of the proposed method and related research, and give a vision for improving the performance of software debugging (Section 4).
机译:软件调试是软件开发过程中最昂贵的活动之一。它主要包括四个核心任务,即故障检测,故障定位,故障理解和故障修复。其中,故障本地化通常需要最长的时间和最大的努力[1]。但是,现有的故障定位方法基于“完美故障理解”的假设,这指的是,当开发人员仅在给定可疑语句列表时完全了解故障。此外,一些研究人员[2,3]怀疑故障定位方法的有效性,并且它们进行了实验研究,该研究表明了一些基于频谱的本地化技术的表现不令人满意。在本文中,我们提出了一种基于开发人员的软件调试分析方法行为数据。我们特别尝试分析调试过程中收集的数据,从而调查基于频谱的故障定位对调试效率的影响。本研究解决了两个主要的技术挑战:(1)开发人员行为的信息对于改善自动化软件调试至关重要; (2)如何在没有任何中断的情况下收集开发人员的调试行为数据,并在不同开发人员之间进行比较分析。在练习和分析各种手动调试方法之后,显示在调试过程中由不同开发人员产生的行为信息显示了一定程度的相似性。这种相似性反过来可以帮助加快调试过程。本文提出以下三个贡献:1。我们根据其中在Eclipse Plug-in DebugInfo(第2节)中,为开发人员行为数据进行了用于集合的分层信息结构。进行实验研究,目的是解释软件调试中基于频谱的故障定位的不令人满意的原因(第3节)。 3.我们对提出的方法和相关研究进行了一个定性的比较研究,并对改善软件调试的性能进行了愿景(第4节)。

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  • 来源
    《Frontiers of computer science》 |2021年第1期|151203.1-151203.3|共3页
  • 作者单位

    School of Information Science and Technology North China University of Technology Beijing 100144 China;

    School of Information Science and Technology North China University of Technology Beijing 100144 China;

    Department of Computer Science and Software Engineering Swinburne University of Technology Hawthorn VIC 3122 Australia;

    School of Information Science and Technology North China University of Technology Beijing 100144 China;

    School of Computer Science and Engineering Beihang University Beijing 100191 China;

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