New Random Testing-based Fault Localization Approach
一种随机TBFL方法

Fixing faults in software are an essential task in software development, and many approaches have been presented to automate fault localization. Among them, testing-based approaches are most promising. These approaches use the information of test cases to localize the faults, and they are called collectively as TBFL approach. But these TBFL approaches have ignored the similarity of the test cases, which may harm the effectiveness of these approaches. In fact it is impossible to completely avoid redundancy. Therefore this paper presented a new TBFL approach named random TBFL approach from a new view. The basic idea is that; the program is viewed as a random variable, and before testing, a prior distribution about the error probability of statements of the program is given, then some adjustments to the error probability of statements arc made based on the execution information of the test suite, and the readjusted probability is called posterior probabihty,finally this posterior probability is used to localize the faults. This paper integrated the traditional TI3FI_ approaches into the random framework, and compared and analyzed them on several instances. The analysis demonstrates that the random TI3FL approach can correctly locate the faults,and redundancy has little influence on the effectiveness of the random TBFL approach.