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Software Product Line Analysis Using Variability-aware Datalog

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posted on 07.07.2021, 08:05 by Ramy Shahin, Murad Akhundov, marsha chechik
Applying program analyses to Software Product Lines (SPLs) has been a fundamental research problem at the intersection
of Product Line Engineering and software analysis. Different attempts have been made to "lift" particular product-level analyses to run on the entire product line. In this paper, we tackle the class of Datalog-based analyses (e.g., pointer and taint analyses), study the theoretical aspects of lifting Datalog inference, and implement a lifted inference algorithm inside the Souffl  Datalog engine. We evaluate our implementation on a set of Java and C-language benchmark product lines. We show significant savings in processing time and fact database size (billions of times faster on one of the benchmarks) compared to brute-force analysis of each product individually.

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Email Address of Submitting Author

rshahin@cs.toronto.edu

Submitting Author's Institution

University of Toronto

Submitting Author's Country

Canada

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