Title :
MUGAMMA: Mutation Analysis of Deployed Software to Increase Confidence and Assist Evolution
Author :
Kim, Sang-Woon ; Harrold, Mary Jean ; Kwon, Yong-Rae
Author_Institution :
Dept. of EECS, KAIST, Daejeon
Abstract :
This paper presents a novel approach to unit testing that lets users of deployed software assist in performing mutation testing of the software. Our technique, MUGAMMA, provisions a software system so that when it executes in the field, it will determine whether users´ executions would have killed mutants (without actually executing the mutants), and if so, captures the state information about those executions. In the absence of bug reports, knowledge of executions that would have killed mutants provides additional confidence in the system over that gained by the testing performed before deployment. Captured information about the state before and after execution of units (e.g., methods) can be used to construct test cases for use in unit testing when changes are made to the software. The paper also describes our prototype MuGamma implementation along with a case study that demonstrates its potential efficacy.
Keywords :
program debugging; program testing; MUGAMMA; bugs; deployed software; mutation analysis; unit testing; Automatic testing; Environmental economics; Genetic mutations; Monitoring; Performance analysis; Performance evaluation; Software performance; Software quality; Software testing; System testing;
Conference_Titel :
Mutation Analysis, 2006. Second Workshop on
Conference_Location :
Raleigh, NC
Print_ISBN :
0-7695-2897-X
DOI :
10.1109/MUTATION.2006.8