Lifting Datalog-Based Analyses to Software Product Lines
Abstract
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\'e Datalog engine. We evaluate our implementation on a set of 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.
Cite
@article{arxiv.1907.02192,
title = {Lifting Datalog-Based Analyses to Software Product Lines},
author = {Ramy Shahin and Marsha Chechik and Rick Salay},
journal= {arXiv preprint arXiv:1907.02192},
year = {2019}
}
Comments
FSE'19 paper