Quantitative analysis of probabilistic models of software product lines with statistical model checking (Contributo in atti di convegno)

Type
Label
  • Quantitative analysis of probabilistic models of software product lines with statistical model checking (Contributo in atti di convegno) (literal)
Anno
  • 2015-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.4204/EPTCS.182.5 (literal)
Alternative label
  • Ter Beek M. H., Legay A., Lluch Lafuente A., Vandin A. (2015)
    Quantitative analysis of probabilistic models of software product lines with statistical model checking
    in FMSPLE'15 - 6th International Workshop on Formal Methods for Software Product Line Engineering, London, UK, 11 April 2015
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Ter Beek M. H., Legay A., Lluch Lafuente A., Vandin A. (literal)
Pagina inizio
  • 56 (literal)
Pagina fine
  • 70 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#altreInformazioni
  • Progetto A Quantitative Approach to Management and Design of Collective and Adaptive Behaviours Acronimo QUANTICOL Grant agreement 600708 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://eptcs.web.cse.unsw.edu.au/paper.cgi?FMSPLE15.5 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana
  • 182 (literal)
Note
  • PuMa (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • CNR-ISTI, Pisa, Italy; Inria Rennes, France; DTU, Lyngby, Denmark; University of Southampton, UK (literal)
Titolo
  • Quantitative analysis of probabilistic models of software product lines with statistical model checking (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#curatoriVolume
  • J.M. Atlee, S. Gnesi (literal)
Abstract
  • We investigate the suitability of statistical model checking techniques for analysing quantitative properties of software product line models with probabilistic aspects. For this purpose, we enrich the feature-oriented language FLan with action rates, which specify the likelihood of exhibiting particular behaviour or of installing features at a specific moment or in a specific order. The enriched language (called PFLan) allows us to specify models of software product lines with probabilistic configurations and behaviour, e.g. by considering a PFLan semantics based on discrete-time Markov chains. The Maude implementation of PFLan is combined with the distributed statistical model checker MultiVeStA to perform quantitative analyses of a simple product line case study. The presented analyses include the likelihood of certain behaviour of interest (e.g. product malfunctioning) and the expected average cost of products. (literal)
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