DocumentCode
185636
Title
An Empirical Study on the Scalability of Selective Mutation Testing
Author
Jie Zhang ; Muyao Zhu ; Dan Hao ; Lu Zhang
Author_Institution
MoE, China Inst. of Software, Peking Univ., Beijing, China
fYear
2014
fDate
3-6 Nov. 2014
Firstpage
277
Lastpage
287
Abstract
Software testing plays an important role in ensuring software quality by running a program with test suites. Mutation testing is designed to evaluate whether a test suite is adequate in detecting faults. Due to the expensive cost of mutation testing, selective mutation testing was proposed to select a subset of mutants whose effectiveness is similar to the whole set of generated mutants. Although selective mutation testing has been widely investigated in recent years, many people still doubt whether it can suit well for large programs. To study the scalability of selective mutation testing, we systematically explore how the program size impacts selective mutation testing through four projects (including 12 versions all together). Based on the empirical study, for programs smaller than 16 KLOC, selective mutation testing has surprisingly good scalability. In particular, for a program whose number of lines of executable code is E, the number of mutants used in selective mutation testing is proportional to Ec, where c is a constant whose value is between 0.05 and 0.25.
Keywords
program testing; software quality; executable code; fault detection; selective mutation testing; software quality; software testing; Atmospheric measurements; Educational institutions; Particle measurements; Scalability; Software; Testing; XML; empirical study; mutation testing; scalability; software testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Reliability Engineering (ISSRE), 2014 IEEE 25th International Symposium on
Conference_Location
Naples
ISSN
1071-9458
Print_ISBN
978-1-4799-6032-3
Type
conf
DOI
10.1109/ISSRE.2014.27
Filename
6982634
Link To Document