一种基于层次切片谱的软件错误定位技术

传统的软件错误定位技术通常利用测试覆盖信息计算程序语句发生错误的可疑度进行软件错误定位,但是这种定位技术没有充分考虑程序本身固有的依赖信息,缺乏语句筛选,从而使错误定位的精度受限.提出了一种基于层次切片谱的错误定位技术,以提高面向对象程序中的错误定位效率.这种技术首先分析程序不同粒度层次元素(包、类、方法以及语句)之间的依赖信息,对可能发生错误的元素进行筛选,缩小错误查找范围;在此基础上,建立了层次切片谱模型,并定义了一种可疑度度量方法;最后根据该可疑度结果从大到小的顺序进行错误定位.通过实验验证了基于层次切片谱的错误定位技术的有效性,且比基于程序谱的Tarantula 技术、Union 技术、Intersection 技术效率更高.

Technique of Software Fault Localization Based on Hierarchical Slicing Spectrum

A commonly-used software fault localization technique mainly utilizes testing coverage information to calculate the suspiciousness of each program statement to find the faulty statement. However, this technique does not fully take dependences of the program into account; thus, its capacity for precisely locating faults is limited. This paper proposes a more effective hierarchical slicing spectrum-based software fault localization (HSS-SFL) technique for object-oriented programs. HSS-SFL first analyzes the dependence among the elements at different granularity levels including package level, class level, method level and statement level, and deletes some elements which are unrelated to the failed testing outputs. Next, the technique builds the hierarchical slicing spectrum model for these hierarchical slices obtained from the previous step, and further defines a suspiciousness method for each slice element. Finally, the faulty statement is located according to the suspiciousness results. Experimental results on real application programs show that HSS-SFL is more effective to locate the fault than program spectrum-based Tarantula technique, Union technique and Intersection technique.