Statistical Fault Localization via Semi-dynamic Program Slicing

Abstract

Fault localization is a critical step of software debugging. We present a statistical fault localization approach via semi-dynamic slicing in this paper. In our technique, we first conduct the execution flow graph based on both the coverage information and static control-flow-graph to model the executions approximately. Second, we use the backward slicing to analyze the dependence relationships between execution statements and execution results, obtain sliced statements and calculate the coverage statistics. At last, we calculate the fault suspiciousness according to Tarantula, a classic approach of statistical fault localization. Controlled experiments are setup on the Siemens subjects, and the results are promising.