By the same authors

Selecting Highly Efficient Sets of Subdomains for Mutation Adequacy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Standard

Selecting Highly Efficient Sets of Subdomains for Mutation Adequacy. / Patrick, M.; Alexander, R.; Oriol, M.; Clark, J.A.

Software Engineering Conference (APSEC, 2013 20th Asia-Pacific). Vol. 1 2013. p. 91-98.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Harvard

Patrick, M, Alexander, R, Oriol, M & Clark, JA 2013, Selecting Highly Efficient Sets of Subdomains for Mutation Adequacy. in Software Engineering Conference (APSEC, 2013 20th Asia-Pacific). vol. 1, pp. 91-98. https://doi.org/10.1109/APSEC.2013.23

APA

Patrick, M., Alexander, R., Oriol, M., & Clark, J. A. (2013). Selecting Highly Efficient Sets of Subdomains for Mutation Adequacy. In Software Engineering Conference (APSEC, 2013 20th Asia-Pacific) (Vol. 1, pp. 91-98) https://doi.org/10.1109/APSEC.2013.23

Vancouver

Patrick M, Alexander R, Oriol M, Clark JA. Selecting Highly Efficient Sets of Subdomains for Mutation Adequacy. In Software Engineering Conference (APSEC, 2013 20th Asia-Pacific). Vol. 1. 2013. p. 91-98 https://doi.org/10.1109/APSEC.2013.23

Author

Patrick, M. ; Alexander, R. ; Oriol, M. ; Clark, J.A. / Selecting Highly Efficient Sets of Subdomains for Mutation Adequacy. Software Engineering Conference (APSEC, 2013 20th Asia-Pacific). Vol. 1 2013. pp. 91-98

Bibtex - Download

@inproceedings{ca2a924979304dc3ade33df3f9f2f3ad,
title = "Selecting Highly Efficient Sets of Subdomains for Mutation Adequacy",
abstract = "Test selection techniques are used to reduce the human effort involved in software testing. Most research focusses on selecting efficient sets of test cases according to various coverage criteria for directed testing. We introduce a new technique to select efficient sets of sub domains from which new test cases can be sampled at random to achieve a high mutation score. We first present a technique for evolving multiple sub domains, each of which target a different group of mutants. The evolved sub domains are shown to achieve an average 160% improvement in mutation score compared to random testing with six real world Java programs. We then present a technique for selecting sets of the evolved sub domains to reduce the human effort involved in evaluating sampled test cases without reducing their fault finding effectiveness. This technique significantly reduces the number of sub domains for four of the six programs with a negligible difference in mutation score.",
keywords = "Java, program testing, software fault tolerance, Java programs, fault finding effectiveness, highly efficient subdomain sets, mutation adequacy, mutation score, software testing, test cases, test selection techniques, Covariance matrices, Equations, Fault diagnosis, Optimization, Schedules, Software, Testing, input subdomains, mutation analysis, test case selection, test data generation",
author = "M. Patrick and R. Alexander and M. Oriol and J.A. Clark",
note = "{\textcopyright} 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Published version: 10.1109/APSEC.2013.23",
year = "2013",
month = dec,
day = "1",
doi = "10.1109/APSEC.2013.23",
language = "English",
volume = "1",
pages = "91--98",
booktitle = "Software Engineering Conference (APSEC, 2013 20th Asia-Pacific)",

}

RIS (suitable for import to EndNote) - Download

TY - GEN

T1 - Selecting Highly Efficient Sets of Subdomains for Mutation Adequacy

AU - Patrick, M.

AU - Alexander, R.

AU - Oriol, M.

AU - Clark, J.A.

N1 - © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Published version: 10.1109/APSEC.2013.23

PY - 2013/12/1

Y1 - 2013/12/1

N2 - Test selection techniques are used to reduce the human effort involved in software testing. Most research focusses on selecting efficient sets of test cases according to various coverage criteria for directed testing. We introduce a new technique to select efficient sets of sub domains from which new test cases can be sampled at random to achieve a high mutation score. We first present a technique for evolving multiple sub domains, each of which target a different group of mutants. The evolved sub domains are shown to achieve an average 160% improvement in mutation score compared to random testing with six real world Java programs. We then present a technique for selecting sets of the evolved sub domains to reduce the human effort involved in evaluating sampled test cases without reducing their fault finding effectiveness. This technique significantly reduces the number of sub domains for four of the six programs with a negligible difference in mutation score.

AB - Test selection techniques are used to reduce the human effort involved in software testing. Most research focusses on selecting efficient sets of test cases according to various coverage criteria for directed testing. We introduce a new technique to select efficient sets of sub domains from which new test cases can be sampled at random to achieve a high mutation score. We first present a technique for evolving multiple sub domains, each of which target a different group of mutants. The evolved sub domains are shown to achieve an average 160% improvement in mutation score compared to random testing with six real world Java programs. We then present a technique for selecting sets of the evolved sub domains to reduce the human effort involved in evaluating sampled test cases without reducing their fault finding effectiveness. This technique significantly reduces the number of sub domains for four of the six programs with a negligible difference in mutation score.

KW - Java

KW - program testing

KW - software fault tolerance

KW - Java programs

KW - fault finding effectiveness

KW - highly efficient subdomain sets

KW - mutation adequacy

KW - mutation score

KW - software testing

KW - test cases

KW - test selection techniques

KW - Covariance matrices

KW - Equations

KW - Fault diagnosis

KW - Optimization

KW - Schedules

KW - Software

KW - Testing

KW - input subdomains

KW - mutation analysis

KW - test case selection

KW - test data generation

U2 - 10.1109/APSEC.2013.23

DO - 10.1109/APSEC.2013.23

M3 - Conference contribution

VL - 1

SP - 91

EP - 98

BT - Software Engineering Conference (APSEC, 2013 20th Asia-Pacific)

ER -