FSE 2024 Best Demonstration Award

Our collaboration paper titled “Variability-Aware Differencing with DiffDetective” by Paul Maximilian Bittner, Alexander Schultheiß, Benjamin Moosherr, Timo Kehrer and Thomas Thüm, presented at the ACM International Conference on the Foundations of Software Engineering (FSE 2024), has received a Best Demonstration award.

Abstract

Diff tools are essential in developers’ daily workflows and software engineering research. Motivated by limitations of traditional line-based differencing, countless specialized diff tools have been proposed, aware of the underlying artifacts’ type, such as a program’s syntax or semantics. However, no diff tool is aware of systematic variability embodied in highly configurable systems such as the Linux kernel. Our software library called DiffDetective can turn any generic diff tool into a variability-aware differencer such that a changes’ impact on the source code and its superimposed variability can be distinguished and analyzed. Besides graphical diff inspectors, DiffDetective provides a framework for large-scale empirical analyses of version histories, tested on a substantial body of configurable software including the Linux kernel. DiffDetective has been successfully employed to explain edits, generate clone-and-own scenarios, or evaluate diff algorithms and patch mutation.