Multi-objective Coevolutionary Automated Software Correction

Abstract

For a given program, testing, locating the errors identified, and correcting those errors is a critical, yet expensive process. The field of Search Based Software Engineering (SBSE) addresses these phases by formulating them as search problems. The Coevolutionary Automated Software Correction (CASC) system targets the correction phase by coevolving test cases and programs at the source code level. This paper presents the latest version of the CASC system featuring multi-objective optimization and an enhanced representation language. Results are presented demonstrating CASC's ability to successfully correct five seeded bugs in two non-trivial programs from the Siemens test suite. Additionally, evidence is provided substantiating the hypothesis that multi-objective optimization is beneficial to SBSE.

Meeting Name

14th International Conference on Genetic and Evolutionary Computation, GECCO'12 (2012: Jul. 7-11, Philadelphia, PA)

Department(s)

Computer Science

Keywords and Phrases

Automated Program Correction; Coevolution; Fitness Sharing; Genetic Programming; Multi-Objective Optimization; NSGA-II; SBSE

International Standard Book Number (ISBN)

978-1450311779

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2012 Association for Computing Machinery (ACM), All rights reserved.

Publication Date

01 Jan 2012

Link to Full Text

Share

 
COinS