Variability-aware Neo4j for Analyzing a Graphical Model of a Software Product Line
Xiang Chen, Joanne M. Atlee · 2023
Comprehensive analysis of a software product line (SPL) is expensive because the number of products to be analyzed is exponential in the number of the SPL’s features. To compensate, we analyze a model of the SPL rather than the source code, thereby reducing the size of the artifact under analysis. In this paper, we facilitate SPL analysis by lifting the Neo4j query engine to apply to an SPL model, so that a Neo4j query returns variability-aware results that cover all the SPL’s products. We used the lifted Neo4j to analyze five nontrivial SPLs (with respect to dataflows, control-flows, component interactions, etc.) and found that the overhead for returning variability-aware results for the full SPL, versus the results for just one product, ranges from 1.88% to 456%. In comparison to related work V-Soufflé (a lifted Datalog engine), lifted Neo4j is able to report complete path results whereas V-Soufflé reports only endpoints of paths. When both analyzers report the same results (e.g., endpoints of paths), lifted Neo4j is usually more efficient.