Software fault localization research based on graph mining and decision tree

Abstract

Abstract: Testers often spend a lot of time to find the non-crash software fault. In order to locate the kind of fault fast and accurately, reduce the cost of software development and improve the quality of software, a kind of auxiliary method to locate the non-crash fault is proposed. The approach collects the information of the program execution path and constructs program call graph. The technique extracting frequent edge and utilizing J48 algorithm builds a fault decision tree based on granularity level in method. Experimental results show that this method is effective.

Key words: software fault localization, execution path, graph mining, decision tree

摘要： 对于非崩溃的错误，测试人员往往花费大量的时间才能发现。为了快速准确地定位这类错误，降低软件开发成本，提高软件质量，提出一种辅助定位非崩溃错误的方法。该方法通过收集程序的执行轨迹信息，构造出程序调用图。提取频繁边，运用J48决策树算法，得到基于方法粒度的故障决策树，可辅助人员判定软件缺陷。通过实验与分析，进一步验证了该方法的有效性。

关键词: 软件故障定位, 执行轨迹, 图挖掘, 决策树

YANG Shuxin, XU Liping, WANG Peng. Software fault localization research based on graph mining and decision tree[J]. Computer Engineering and Applications, 2015, 51(20): 67-71.

杨书新，徐丽萍，王鹏. 基于图挖掘和决策树的软件故障定位研究[J]. 计算机工程与应用, 2015, 51(20): 67-71.

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Software fault localization research based on graph mining and decision tree

基于图挖掘和决策树的软件故障定位研究

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