A Comprehensive Study of Automatic Program Repair on the QuixBugs Benchmark

Automatic program repair papers tend to repeatedly use the same benchmarks. This poses a threat to the external validity of the findings of the program repair research community. In this paper, we perform an automatic repair experiment on a benchmark called QuixBugs that has been recently published. This benchmark has never been studied in the context of program repair. In this study, we report on the characteristics of QuixBugs, and we design and perform an experiment about the effectiveness of test-suite based program repair on QuixBugs. We study two repair systems, Astor and Nopol, which are representatives of generate-and-validate repair technique and synthesis repair technique respectively. We propose three patch correctness assessment techniques to comprehensively study overfitting and incorrect patches. Our key results are: 1) 13 / 40 buggy programs in the QuixBugs can be repaired with a test-suite adequate patch; 2) a total of 22 different plausible patches for those 13 buggy programs in the QuixBugs are present in the search space of the considered tools; 3) the three patch assessment techniques discard in total 12 / 22 patches that are overfitting. This sets a baseline for future research of automatic repair on QuixBugs. Our experiment also highlights the major properties and challenges of how to perform automated correctness assessment of program repair patches. All experimental results are publicly available on Github in order to facilitate future research on automatic program repair.