DirectDebug: Automated Testing and Debugging of Feature Models

TL;DR

DirectDebug is an automated diagnosis tool that identifies faulty constraints in large-scale feature models, improving quality assurance and reducing maintenance efforts.

Contribution

It introduces a direct diagnosis algorithm for automated testing and debugging of variability models, streamlining fault detection.

Findings

Reduces debugging time for feature models

Automates identification of faulty constraints

Enhances quality assurance processes

Abstract

Variability models (e.g., feature models) are a common way for the representation of variabilities and commonalities of software artifacts. Such models can be translated to a logical representation and thus allow different operations for quality assurance and other types of model property analysis. Specifically, complex and often large-scale feature models can become faulty, i.e., do not represent the expected variability properties of the underlying software artifact. In this paper, we introduce DirectDebug which is a direct diagnosis approach to the automated testing and debugging of variability models. The algorithm helps software engineers by supporting an automated identification of faulty constraints responsible for an unintended behavior of a variability model. This approach can significantly decrease development and maintenance efforts for such models.