Does Genetic Programming Work Well on Automated Program Repair?

Author

Yuhua Qi ; Xiaoguang Mao ; Yan Lei ; Ziying Dai ; Chengsong Wang

Author_Institution

Sch. of Comput., Nat. Univ. of Defense Technol., Changsha, China

fYear

2013

fDate

21-23 June 2013

Firstpage

1875

Lastpage

1878

Abstract

Automated program repair has made some important progress in the recent decade. One well-known repair tool is GneProg, which automates the patch generation process according to the guidance of genetic programming. Although GenProg has successfully fixed many legacy faulty programs, the guidance effectiveness of genetic programming used by GenProg has not been even justified through the comparison with random search algorithm. In this paper we try to make the guidance effectiveness comparison between genetic programming and random search algorithm on program repair. The experimental results show that genetic programming does not perform better than random search algorithm on guiding the patch generation process.

Keywords

genetic algorithms; program debugging; search problems; software maintenance; GneProg; automated program repair; automated software repair; genetic programming; guidance effectiveness comparison; legacy faulty programs; patch generation process; random search algorithm; Genetic algorithms; Genetic programming; Maintenance engineering; Sociology; Software; Software engineering; Statistics; automated debugging; automated program repair; genetic programming; random search;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational and Information Sciences (ICCIS), 2013 Fifth International Conference on

Conference_Location

Shiyang

Type

conf

DOI

10.1109/ICCIS.2013.490

Filename

6643409