Supporting the statistical analysis of variability models
Sprache des Vortragstitels:
Englisch
Original Tagungtitel:
ICSE 2019
Sprache des Tagungstitel:
Englisch
Original Kurzfassung:
Variability models are broadly used to specify the
configurable features of highly customizable software. In practice,
they can be large, defining thousands of features with their
dependencies and conflicts. In such cases, visualization techniques
and automated analysis support are crucial for understanding the
models. This paper contributes to this line of research by presenting
a novel, probabilistic foundation for statistical reasoning
about variability models. Our approach not only provides a new
way to visualize, describe and interpret variability models, but
it also supports the improvement of additional state-of-the-art
methods for software product lines; for instance, providing exact
computations where only approximations were available before,
and increasing the sensitivity of existing analysis operations for
variability models. We demonstrate the benefits of our approach
using real case studies with up to 17,365 features, and written
in two different languages (KConfig and feature models).
Index Terms?Variability modeling, feature modeling, software
product lines, software visualization, binary decision diagrams.
Forschungs-