2012
Ferrer, Javier; Kruse, Peter M; Chicano, Francisco; Alba, Enrique
Evolutionary algorithm for prioritized pairwise test data generation Inproceedings
In: Soule, Terence; Moore, Jason H (Ed.): łdots on Genetic and evolutionary łdots, pp. 1213–1220, ACM, New York, New York, USA, 2012, ISBN: 978-1-4503-1177-9.
Abstract | Links | BibTeX | Tags: combinatorial testing, evolutionary algorithm, pair-, pairwise coverage, prioritization, search based soft-, search based software engineering, software testing, Testing Funcional, ware engineering
@inproceedings{DBLP:conf/gecco/FerrerKCA12,
title = {Evolutionary algorithm for prioritized pairwise test data generation},
author = {Javier Ferrer and Peter M Kruse and Francisco Chicano and Enrique Alba},
editor = {Terence Soule and Jason H Moore},
url = {http://dl.acm.org/citation.cfm?id=2330163.2330331 http://dl.acm.org/citation.cfm?doid=2330163.2330331 http://dl.acm.org/citation.cfm?id=2330331},
doi = {10.1145/2330163.2330331},
isbn = {978-1-4503-1177-9},
year = {2012},
date = {2012-07-01},
booktitle = {łdots on Genetic and evolutionary łdots},
pages = {1213--1220},
publisher = {ACM},
address = {New York, New York, USA},
abstract = {Combinatorial Interaction Testing (CIT) is a technique used to discover faults caused by parameter interactions in highly configurable systems. These systems tend to be large and exhaustive testing is generally impractical. Indeed, when the resources are limited, prioritization of test cases is a must. Important test cases are assigned a high priority and should be executed earlier. On the one hand, the prioritization of test cases may reveal faults in early stages of the testing phase. But, on the other hand the generation of minimal test suites that fulfill the demanded coverage criteria is an NP-hard problem. Therefore, search based approaches are required to find the (near) optimal test suites. In this work we present a novel evolutionary algorithm to deal with this problem. The experimental analysis compares five techniques on a set of benchmarks. It reveals that the evolutionary approach is clearly the best in our comparison. The presented algorithm can be integrated into CTE XL professional tool.},
keywords = {combinatorial testing, evolutionary algorithm, pair-, pairwise coverage, prioritization, search based soft-, search based software engineering, software testing, Testing Funcional, ware engineering},
pubstate = {published},
tppubtype = {inproceedings}
}
2009
Ferrer, Javier; Chicano, Francisco; Alba, Enrique
Dealing with inheritance in OO evolutionary testing Inproceedings
In: Genetic and evolutionary computation - GECCO '09, pp. 1665, ACM Press, New York, USA, 2009, ISBN: 9781605583259.
Links | BibTeX | Tags: evolutionary algorithm, instanceof, object-oriented, oo evolutionary testing, search based software engineering, software testing
@inproceedings{Ferrer2009a,
title = {Dealing with inheritance in OO evolutionary testing},
author = {Javier Ferrer and Francisco Chicano and Enrique Alba},
url = {http://dl.acm.org/citation.cfm?id=1569901.1570124},
doi = {10.1145/1569901.1570124},
isbn = {9781605583259},
year = {2009},
date = {2009-07-01},
booktitle = {Genetic and evolutionary computation - GECCO '09},
pages = {1665},
publisher = {ACM Press},
address = {New York, USA},
keywords = {evolutionary algorithm, instanceof, object-oriented, oo evolutionary testing, search based software engineering, software testing},
pubstate = {published},
tppubtype = {inproceedings}
}