Resumen:
Uniform and Scalable SAT-Sampling for Configurable Systems

Fecha

2021-09-22

Editor

Sistedes

Publicado en

Actas de las XXV Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2021)

Licencia

CC BY-NC-ND 4.0

Resumen

Several relevant analyses on configurable software systems remain intractable because they require examining vast and highly-constrained configuration spaces. Those analyses could be addressed through statistical inference, i.e., working with a much more tractable sample that later supports generalizing the results obtained to the entire configuration space. To make this possible, the laws of statistical inference impose an indispensable requirement: each member of the population must be equally likely to be included in the sample, i.e., the sampling process needs to be +AGAAYA-uniform''. Various SAT-samplers have been developed for generating uniform random samples at a reasonable computational cost. Unfortunately, there is a lack of experimental validation over large configuration models to show whether the samplers indeed produce genuine uniform samples or not. This paper (i) presents a new statistical test to verify to what extent samplers accomplish uniformity and (ii) reports the evaluation of four state-of-the-art samplers: Spur, QuickSampler, Unigen2, and Smarch. According to our experimental results, only Spur satisfies both scalability and uniformity.

Descripción

Acerca de Heradio, Ruben

Palabras clave

Configurable Systems, SAT, Software Product Line, Uniform Sampling, Variability Modeling
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