CAJ | 학술논문

现有的测试用例约简方法不能有效提高错误定位精度,现有的软件错误定位方法不能充分分析元素间的依赖关系。针对以上问题,提出结合测试用例约简和联合依赖概率建模的软件错误自动定位方法,将测试用例约简与软件错误定位统一为一个整体。不同于一般的测试用例约简方法,所提出的测试用例约简方法在程序执行路径的基础上充分考虑了错误测试用例对错误定位的影响,能够为错误定位提供有效的测试用例,为快速、准确地定位软件错误奠定基础。定义了一种新的统计模型--联合依赖概率模型,充分分析了程序元素间的控制依赖、数据依赖以及语句执行状态,并提出基于联合依赖概率模型的错误自动定位方法。通过计算联合依赖关系的可疑度,对可疑节点进行排序,准确定位错误语句。实验结果表明：与 SBI,SOBER,Tarantula,SF 和 RankCP 方法相比,该算法可以更加有效地定位软件错误。
현유적측시용례약간방법불능유효제고착오정위정도,현유적연건착오정위방법불능충분분석원소간적의뢰관계。침대이상문제,제출결합측시용례약간화연합의뢰개솔건모적연건착오자동정위방법,장측시용례약간여연건착오정위통일위일개정체。불동우일반적측시용례약간방법,소제출적측시용례약간방법재정서집행로경적기출상충분고필료착오측시용례대착오정위적영향,능구위착오정위제공유효적측시용례,위쾌속、준학지정위연건착오전정기출。정의료일충신적통계모형--연합의뢰개솔모형,충분분석료정서원소간적공제의뢰、수거의뢰이급어구집행상태,병제출기우연합의뢰개솔모형적착오자동정위방법。통과계산연합의뢰관계적가의도,대가의절점진행배서,준학정위착오어구。실험결과표명：여 SBI,SOBER,Tarantula,SF 화 RankCP 방법상비,해산법가이경가유효지정위연건착오。
The current test case reduction methods can not improve the effectiveness of fault localization, and the current fault localization approaches do not fully analyze the dependency of program elements. To solve these problems, this study proposes an automatic fault localization approach combining test case reduction and joint dependency probabilistic model. Different from the usual test case reduction approach, the failed test cases are fully considered in the proposed test cases reduction method based on execution path in order to provide effective test cases for fast and accurate fault localization. This paper defines a novel statistical model-Joint dependency probabilistic model. In this model, the control dependency and data dependency between program elements, the execution states of each statement are analyzed. An automatic fault localization approach is presented based on joint dependency probabilistic model. It ranks the suspicious statements by calculating the joint dependency suspicion level of the statement. Experimental results show that this approach is more effective than current state-of-art fault-localization methods such as SBI, SOBER, Tarantula, and RankCP.