SFLVis: visual analysis of software fault localization

IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Visualization Pub Date : 2024-04-02 DOI:10.1007/s12650-024-00979-x
Desheng Sun, Xiaoqi Yue, Chao Liu, Hongxing Qin, Haibo Hu
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Abstract

Since the birth of software, fault localization has been a time-consuming and laborious task. Programmers need to constantly find faults in software through program logging, assertions, breakpoints, and profiling. In order to improve the debugging efficiency, many fault localization methods based on test cases have been proposed, such as program spectrum-based methods, and slice-based methods. However, these methods are far from the logic of actual debugging and still require programmers to use traditional methods. However, programmers cannot access the execution process of the program, they need to constantly modify breakpoints and repeatedly check variable values, which makes fault localization very time-consuming. After interviewing five experts in the field of visualization and software testing, we designed SFLVis to provide users with a new method to improve the efficiency of fault localization. We designed an algorithm to obtain the process of program execution and combined it with existing fault localization methods. The goal is to show users the execution results of test cases, source code logic, and the level of suspicion of statements, and reproduce the execution process of test cases. We designed rich interactive features to help users explore SFLVis and correlate information from various views to improve the efficiency of fault localization. To verify the effectiveness of SFLVis, we conducted a case study using the program in the Siemens Suite dataset and conducted group experiments and related interviews with 20 volunteers. The results show that SFLVis can effectively improve programmers’ efficiency compared with existing fault localization methods.

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SFLVis:软件故障定位的可视化分析
自软件诞生以来,故障定位一直是一项费时费力的工作。程序员需要通过程序日志、断言、断点和剖析不断查找软件中的故障。为了提高调试效率,人们提出了许多基于测试用例的故障定位方法,如基于程序谱的方法和基于切片的方法。然而,这些方法与实际调试的逻辑相去甚远,仍然需要程序员使用传统方法。然而,程序员无法进入程序的执行过程,他们需要不断修改断点,反复检查变量值,这使得故障定位非常耗时。在采访了五位可视化和软件测试领域的专家后,我们设计了 SFLVis,为用户提供了一种提高故障定位效率的新方法。我们设计了一种获取程序执行过程的算法,并将其与现有的故障定位方法相结合。其目标是向用户展示测试用例的执行结果、源代码逻辑和语句的可疑程度,重现测试用例的执行过程。我们设计了丰富的交互功能,帮助用户探索 SFLVis,并将不同视图的信息关联起来,以提高故障定位的效率。为了验证 SFLVis 的有效性,我们在西门子套件数据集中使用该程序进行了案例研究,并对 20 名志愿者进行了分组实验和相关访谈。结果表明,与现有的故障定位方法相比,SFLVis 可有效提高程序员的工作效率。
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来源期刊
Journal of Visualization
Journal of Visualization COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY
CiteScore
3.40
自引率
5.90%
发文量
79
审稿时长
>12 weeks
期刊介绍: Visualization is an interdisciplinary imaging science devoted to making the invisible visible through the techniques of experimental visualization and computer-aided visualization. The scope of the Journal is to provide a place to exchange information on the latest visualization technology and its application by the presentation of latest papers of both researchers and technicians.
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