Using Mutation Analysis to Evolve Subdomains for Random Testing

Author

Patrick, Matthew ; Alexander, Rob ; Oriol, Manuel ; Clark, John A.

Author_Institution

Univ. of York, York, UK

fYear

2013

fDate

18-22 March 2013

Firstpage

53

Lastpage

62

Abstract

Random testing is inexpensive, but it can also be inefficient. We apply mutation analysis to evolve efficient subdomains for the input parameters of eight benchmark programs that are frequently used in testing research. The evolved subdomains can be used for program analysis and regression testing. Test suites generated from the optimised subdomains outperform those generated from random subdomains with 10, 100 and 1000 test cases for uniform, Gaussian and exponential sampling. Our subdomains kill a large proportion of mutants for most of the programs we tested with just 10 test cases.

Keywords

program diagnostics; program testing; regression analysis; sampling methods; Gaussian sampling; exponential sampling; mutation analysis; optimised subdomain; program analysis; random subdomain; random testing; regression testing; subdomain evolution; test suite; testing research; uniform sampling; Benchmark testing; Convergence; Gaussian distribution; Optimization; Schedules; Shape; mutation testing input distribution test case generation search based evolution strategy;

fLanguage

English

Publisher

ieee

Conference_Titel

Software Testing, Verification and Validation Workshops (ICSTW), 2013 IEEE Sixth International Conference on

Conference_Location

Luxembourg

Print_ISBN

978-1-4799-1324-4

Type

conf

DOI

10.1109/ICSTW.2013.14

Filename

6571608