Using Mutation Analysis to Evolve Subdomains for Random Testing

TY - CONF

T1 - Using Mutation Analysis to Evolve Subdomains for Random Testing

AU - Patrick, Matthew Timothy

AU - Alexander, Rob

AU - Oriol, Manuel Yves Antoine

AU - Clark, John Andrew

PY - 2013/3

Y1 - 2013/3

N2 - 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.

AB - 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.

U2 - 10.1109/ICSTW.2013.14

DO - 10.1109/ICSTW.2013.14

M3 - Paper

SP - 53

EP - 62

T2 - Mutation 2013: 8th International Workshop on Mutation Analysis

Y2 - 18 March 2013

ER -