Experience report: How do techniques, programs, and tests impact automated program repair?

Created by W.Langdon from gp-bibliography.bib Revision:1.8120

@InProceedings{Kong:2015:ieeeISSRE,

• author = "Xianglong Kong and Lingming Zhang and W. Eric Wong and Bixin Li",
• booktitle = "26th IEEE International Symposium on Software Reliability Engineering (ISSRE)",
• title = "Experience report: How do techniques, programs, and tests impact automated program repair?",
• year = "2015",
• pages = "194--204",
• address = "Gaithersbury, MD, USA",
• keywords = "genetic algorithms, genetic programming, genetic improvement, APR, SBSE",
• DOI = "doi:10.1109/ISSRE.2015.7381813",
• month = "2-5 " # nov,
• abstract = "Automated program repair can save tremendous manual efforts in software debugging. Therefore, a huge body of research efforts have been dedicated to design and implement automated program repair techniques. Among the existing program repair techniques, genetic-programming-based techniques have shown promising results. Recently, researchers found that random-search-based and adaptive program repair techniques can also produce effective results. In this work, we performed an extensive study for four program repair techniques, including genetic-programming-based, random-search-based, brute-force-based and adaptive program repair techniques. Due to the extremely large time cost of the studied techniques, the study was performed on 153 bugs from 9 small to medium sized programs. In the study, we further investigated the impacts of different programs and test suites on effectiveness and efficiency of program repair techniques. We found that techniques that work well with small programs become too costly or ineffective when applied to medium sized programs. We also computed the false positive rates and discussed the ratio of the explored search space to the whole search space for each studied technique. Surprisingly, all the studied techniques except the random-search-based technique are consistent with the 80/20 rule, i.e., about 80percent of successful patches are found within the first 20percent of search space.",
• notes = "Sch. of Comput. Sci. & Eng., Southeast Univ., Nanjing, China

  Also known as \cite{7381813}",

}

Genetic Programming entries for Xianglong Kong Lingming Zhang W Eric Wong Bixin Li

Citations