Recent empirical studies show that the performance of GenProg is not satisfactory, particularly for Java. In this paper, we propose ARJA, a new GP based repair approach for automated repair of Java programs. To be specific, we present a novel lower-granularity patch representation that properly decouples the search subspaces of likely-buggy locations, operation types and potential fix ingredients, enabling GP to explore the search space more effectively. Based on this new representation, we formulate automated program repair as a multi-objective search problem and use NSGA-II to look for simpler repairs. To reduce the computational effort and search space, we introduce a test filtering procedure that can speed up the fitness evaluation of GP and three types of rules that can be applied to avoid unnecessary manipulations of the code. Moreover, we also propose a type matching strategy that can create new potential fix ingredients by exploiting the syntactic patterns of the existing statements. We conduct a large-scale empirical evaluation of ARJA along with its variants on both seeded bugs and real-world bugs in comparison with several state-of-the-art repair approaches. Our results verify the effectiveness and efficiency of the search mechanisms employed in ARJA and also show its superiority over the other approaches. In particular, compared to jGenProg (an implementation of GenProg for Java), an ARJA version fully following the redundancy assumption can generate a test-suite adequate patch for more than twice the number of bugs (from 27 to 59), and a correct patch for nearly four times of the number (from 5 to 18), on 224 real-world bugs considered in Defects4J. Furthermore, ARJA is able to correctly fix several real multi-location bugs that are hard to be repaired by most of the existing repair approaches.
Long and Rinard @cite_60 reported SPR, which adopts a staged program repair strategy to navigate a rich search space of candidate patches efficiently. SPR defines a set of transformation schemas beforehand and uses the target value search or condition synthesis algorithm to determine the parameter values of the selected transformation schema. Experimental results on 69 bugs from 8 open source applications indicate that SPR can generate more correct patches than previous repair systems.
@cite_60
2060333670
We present SPR, a new program repair system that combines staged program repair and condition synthesis. These techniques enable SPR to work productively with a set of parameterized transformation schemas to generate and efficiently search a rich space of program repairs. Together these techniques enable SPR to generate correct repairs for over five times as many defects as previous systems evaluated on the same benchmark set.