KernelHaven -- An Experimentation Workbench for Analyzing Software Product Lines
This work addresses the need for streamlined empirical research in software engineering, specifically for static product line analysis and verification, though it is incremental as it builds on existing tools.
The authors tackled the problem of fragmented experimentation in software product line analysis by presenting KernelHaven, an experimentation workbench that enables efficient combination of existing tools through an open plug-in infrastructure, resulting in support for a significant number of experiments with features like configuration-based definitions, parallelization, and caching.
Systematic exploration of hypotheses is a major part of any empirical research. In software engineering, we often produce unique tools for experiments and evaluate them independently on different data sets. In this paper, we present KernelHaven as an experimentation workbench supporting a significant number of experiments in the domain of static product line analysis and verification. It addresses the need for extracting information from a variety of artifacts in this domain by means of an open plug-in infrastructure. Available plug-ins encapsulate existing tools, which can now be combined efficiently to yield new analyses. As an experimentation workbench, it provides configuration-based definitions of experiments, their documentation, and technical services, like parallelization and caching. Hence, researchers can abstract from technical details and focus on the algorithmic core of their research problem. KernelHaven supports different types of analyses, like correctness checks, metrics, etc., in its specific domain. The concepts presented in this paper can also be transferred to support researchers of other software engineering domains. The infrastructure is available under Apache 2.0: https://github.com/KernelHaven. The plug-ins are available under their individual licenses.