An Empirical Study on the Effect of Dynamic Slicing on Automated Program Repair Efficiency

Research on the characteristics of error propagation can guide fault localization more efficiently. Spectrum-based fault localization (SFL) and slice-based fault localization are effective fault localization techniques. The former produces a list of statements in descending order of suspicious values, and the latter generates statements that affect failure statements. We propose a new dynamic slicing and spectrum-based fault localization (DSFL) method, which combines the list of suspicious statements generated by SFL with dynamic slicing, and take the characteristics of error propagation into account. To the best of our knowledge, DSFL has not yet been implemented in automated repair tools. In this study, we use the dynamic slicing tool Javaslicer to determine the error propagation chain of faulty programs and the statements related to failure execution. We implement the DSFL algorithm in the automated repair tool Nopol and conduct repair experiments on dataset Defects4j to compare the effects of SFL and DSFL on the efficiency of automated repair. Preliminary results indicate that the scope of error propagation for most programs is a single class, and the DSFL makes automated repair more efficient.