Enhanced Evolutionary Automated Program Repair by Finer-Granularity Ingredients and Better Search Algorithms
Bo Wang, Guizhuang Liu, Youfang Lin, Shuang Ren, Honghui Li, Dalin Zhang · 2022
Bug repair is time-consuming and tedious, which hampers software maintenance. To alleviate the burden, automated program repair (APR) is proposed and has been fruitful in the last decade. Evolutionary repair is the seminal work of this field and proliferated a family of approaches. The performance of evolutionary repair approaches is affected by two main factors: (1) search space, which defines all possible patches, and (2) search algorithms, which navigates the space. Although recent approaches have achieved remarkable progress, the main challenges of the two factors still remain. On one hand, the different kinds of search space are very coarse for containing correct patches. On the other hand, the search process guided by genetic algorithms is inefficient to find the correct patches in an appropriate time budget.