Exploring the Computational Complexity of SAT Counting and Uniform Sampling with Phase Transitions

Uniform Random Sampling (URS) is the problem of selecting solutions (models) from a Boolean formula such that each solution gets the same probability of being selected. URS has many applications. In large configurable software systems, one wants an unbiased sample of configurations to look for bugs...

Full description

Saved in:
Bibliographic Details
Published in2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) pp. 322 - 323
Main Authors Zeyen, Olivier, Cordy, Maxime, Perrouin, Gilles, Acher, Mathieu
Format Conference Proceeding
LanguageEnglish
Published ACM 14.04.2024
Subjects
Computer bugs
Costs
Deep learning
Evolutionary computation
knowledge compilation
Model counting
SAT
Sociology
Software systems
Statistics
uniform random sampling
Online AccessGet full text

Cover

More Information
Summary:Uniform Random Sampling (URS) is the problem of selecting solutions (models) from a Boolean formula such that each solution gets the same probability of being selected. URS has many applications. In large configurable software systems, one wants an unbiased sample of configurations to look for bugs at an affordable cost [12], [13]. Other applications of URS include deep learning verification (to sample inputs from unknown distributions) [2] and evolutionary algorithms (to initialize the input population) [4].
ISSN:2574-1934
DOI:10.1145/3639478.3643097