Variability encoding: From compile-time to load-time variability

Many software systems today are configurable. Analyzing configurable systems is challenging, especially as (1) the number of system variants may grow exponentially with the number of configuration options, and (2) often existing analysis tools cannot be used for configurable systems. Recent work proposes to automatically transform compile-time variability into load-time variability—called variability encoding—with the goal of reusing existing analysis tools for analyzing configurable systems and improving analysis performance compared to analyzing all system variants in a bruteforce manner. However, it is not clear whether one can automatically find an efficiently analyzable load-time configurable system for any given compile-time configurable system. Also, for many analyses, we need guarantees that the load-time configurable system precisely encodes the behavior of all system variants that can be statically derived. We address both issues (1) by developing a formal model of variability encoding based on FEATHERWEIGHT JAVA, (2) by proving that variability encoding preserves variant behavior with respect to a core set of language mechanisms, (3) by discussing how our work extends to more complex language mechanisms that elude our formal model, and (4) by sharing our experience with implementing and using variability encoding in real-world applications.