Title
Search-based Diverse Sampling from Real-world Software Product Lines
Abstract
Real-world software product lines (SPLs) often encompass enormous valid configurations that are impossible to enumerate. To understand properties of the space formed by all valid configurations, a feasible way is to select a small and valid sample set. Even though a number of sampling strategies have been proposed, they either fail to produce diverse samples with respect to the number of selected features (an important property to characterize behaviors of configurations), or achieve diverse sampling but with limited scalability (the handleable configuration space size is limited to 1013). To resolve this dilemma, we propose a scalable diverse sampling strategy, which uses a distance metric in combination with the novelty search algorithm to produce diverse samples in an incremental way. The distance metric is carefully designed to measure similarities between configurations, and further diversity of a sample set. The novelty search incrementally improves diversity of samples through the search for novel configurations. We evaluate our sampling algorithm on 39 real-world SPLs. It is able to generate the required number of samples for all the SPLs, including those which cannot be counted by sharpSAT, a state-of-the-art model counting solver. Moreover, it performs better than or at least competitively to state-of-the-art samplers regarding diversity of the sample set. Experimental results suggest that only the proposed sampler (among all the tested ones) achieves scalable diverse sampling.
Year
DOI
Venue
2022
10.1145/3510003.3510053
2022 ACM/IEEE 44TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING (ICSE 2022)
Keywords
DocType
ISSN
Software product lines, diverse sampling, novelty search, distance metric
Conference
0270-5257
Citations 
PageRank 
References 
0
0.34
0
Authors
8
Name
Order
Citations
PageRank
Yi Xiang100.34
Han Huang215930.23
Yuren Zhou372149.79
Sizhe Li400.34
Chuan Luo549641.38
Qingwei Lin628527.76
Miqing Li700.34
xiaowei yang81950111.09