A parallel evolutionary algorithm for prioritized pairwise testing of software product lines
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86093025" target="_blank" >RIV/61989100:27240/14:86093025 - isvavai.cz</a>
Výsledek na webu
<a href="http://dx.doi.org/10.1145/2576768.2598305" target="_blank" >http://dx.doi.org/10.1145/2576768.2598305</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/2576768.2598305" target="_blank" >10.1145/2576768.2598305</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
A parallel evolutionary algorithm for prioritized pairwise testing of software product lines
Popis výsledku v původním jazyce
Software Product Lines (SPLs) are families of related software systems, which provide different feature combinations. Different SPL testing approaches have been proposed. However, despite the extensive and successful use of evolutionary computation techniques for software testing, their application to SPL testing remains largely unexplored. In this paper we present the Parallel Prioritized product line Genetic Solver (PPGS), a parallel genetic algorithm for the generation of prioritized pairwise testing suites for SPLs. We perform an extensive and comprehensive analysis of PPGS with 235 feature models from a wide range of number of features and products, using 3 different priority assignment schemes and 5 product prioritization selection strategies. We also compare PPGS with the greedy algorithm prioritized-ICPL. Our study reveals that overall PPGS obtains smaller covering arrays with an acceptable performance difference with prioritized-ICPL. 2014 ACM.
Název v anglickém jazyce
A parallel evolutionary algorithm for prioritized pairwise testing of software product lines
Popis výsledku anglicky
Software Product Lines (SPLs) are families of related software systems, which provide different feature combinations. Different SPL testing approaches have been proposed. However, despite the extensive and successful use of evolutionary computation techniques for software testing, their application to SPL testing remains largely unexplored. In this paper we present the Parallel Prioritized product line Genetic Solver (PPGS), a parallel genetic algorithm for the generation of prioritized pairwise testing suites for SPLs. We perform an extensive and comprehensive analysis of PPGS with 235 feature models from a wide range of number of features and products, using 3 different priority assignment schemes and 5 product prioritization selection strategies. We also compare PPGS with the greedy algorithm prioritized-ICPL. Our study reveals that overall PPGS obtains smaller covering arrays with an acceptable performance difference with prioritized-ICPL. 2014 ACM.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
IN - Informatika
OECD FORD obor
—
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2014
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
GECCO 2014 - Proceedings of the 2014 Genetic and Evolutionary Computation Conference
ISBN
978-1-4503-2662-9
ISSN
—
e-ISSN
—
Počet stran výsledku
8
Strana od-do
1255-1262
Název nakladatele
ACM
Místo vydání
New York
Místo konání akce
Vancouver
Datum konání akce
12. 7. 2014
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
000364333000157