BURST: Benchmarking Uniform Random Sampling Techniques - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Article Dans Une Revue Science of Computer Programming Année : 2023

BURST: Benchmarking Uniform Random Sampling Techniques

Résumé

BURST is a benchmarking platform for uniform random sampling (URS) techniques. Given: i) the description of a sampling space provided as a Boolean formula (DIMACS), and ii) a sampling budget (time and strength of uniformity), BURST evaluates ten samplers for scalability and uniformity. BURST measures scalability based on the time required to produce a sample, and uniformity based on the state-of-the-art and proven statistical test Barbarik. BURST is easily extendable to new samplers and offers: i) 128 feature models (for highly-configurable systems), ii) many other models mined from the artificial intelligence/satisfiability solving benchmarks. BURST envisions supporting URS assessment and design across multiple research communities.
Fichier principal
Vignette du fichier
BURST_SCPJournalOSP-CR.pdf (195.91 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03897639 , version 1 (14-12-2022)

Licence

Paternité

Identifiants

Citer

Mathieu Acher, Gilles Perrouin, Maxime Cordy. BURST: Benchmarking Uniform Random Sampling Techniques. Science of Computer Programming, 2023, 226, pp.1-10. ⟨10.1016/j.scico.2022.102914⟩. ⟨hal-03897639⟩
164 Consultations
161 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More