A parallel evolutionary algorithm for prioritized pairwise testing of software product lines.

Lopez-Herrejon, Roberto Erick; Ferrer, Javier; Chicano, Francisco; Haslinger, Evelyn Nicole; Egyed, Alexander; Alba, Enrique

doi:10.1145/2576768.2598305

A parallel evolutionary algorithm for prioritized pairwise testing of software product lines.

by Roberto Erick Lopez-Herrejon, Javier Ferrer, Francisco Chicano, Evelyn Nicole Haslinger, Alexander Egyed, Enrique Alba

Abstract:

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 dierent 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.

Reference:

Roberto Erick Lopez-Herrejon, Javier Ferrer, Francisco Chicano, Evelyn Nicole Haslinger, Alexander Egyed, Enrique Alba, "A parallel evolutionary algorithm for prioritized pairwise testing of software product lines.", pp. 1255-1262, 2014.

Bibtex Entry:

@Conference{DBLP:conf/gecco/Lopez-HerrejonFCHEA14,
  Title                    = {A parallel evolutionary algorithm for prioritized pairwise testing of software product lines.},
  Author                   = {Roberto Erick Lopez-Herrejon and Javier Ferrer and Francisco Chicano and Evelyn Nicole Haslinger and Alexander Egyed and Enrique Alba},
  Booktitle                = {Genetic and Evolutionary Computation Conference (GECCO), Vancover, Canada},
  Year                     = {2014},
  Pages                    = {1255-1262},

  Abstract                 = {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 dierent 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.},
  Doi                      = {10.1145/2576768.2598305},
  File                     = {A parallel evolutionary algorithm for prioritized pairwise testing of software product lines:Conferences\\GECCO 2014 - A parallel evolutionary algorithm for prioritized pairwise testing of software product lines\\A parallel evolutionary algorithm for prioritized pairwise testing of software product lines.pdf:PDF},
  Keywords                 = {testing, variability, FWF P25289-N15, FWF M1421-N15}
}