DIRECTDEBUG: Automated Testing and Debugging of Feature Models

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.

Knowledge-based recommender systems: overview and research directions

“…Related research efforts focus on the topics of automated testing and debugging, human-centered knowledge acquisition , and deep models of knowledge understanding . Automated testing and debugging focuses on the application of model-based diagnosis where pre-defined test cases are used to induce conflicts in the knowledge base which are then resolved on the basis of diagnosis algorithms—see, for example, Le et al ( 2021 ). Understanding the complexity individual knowledge structures can also help to increase the maintainability of knowledge bases—this topic includes the aspects of cognitive complexities of knowledge structures (Felfernig et al, 2015 ) and related knowledge structuring, for example, in terms of the ordering of constraints in a recommendation knowledge base (Felfernig et al, 2013a ).…”

DirectDebug: A software package for the automated testing and debugging of feature models

“…These test cases are integrated in negated form into the background knowledge. For details of the test case generation, we refer to [13].…”

“…A diagnosis (𝛥) includes constraints responsible for the faulty behavior of a feature model (see [13]). Such constraints have to be deleted or adapted to make the feature model consistent with 𝑇 𝜋 .…”

“…DirectDebug [13] is a practical approach to assist software engineers in pro-actively identifying minimal sets of faulty constraints responsible for unintended behaviors of a feature model. This way, this approach helps to accelerate feature model development and evolution processes.…”

“…The algorithm returns an 𝑀𝑆𝑆 -𝛤 (Maximum Satisfiable Subsetsee Definition 3 in[13]), a corresponding diagnosis is 𝐶 ⧵ 𝛤 . If 𝐶𝐹 is diagnosed as a whole, then 𝐶 = 𝐶𝐹 ⧵ {𝑐 0 } and 𝐵 = {𝑐 0 } ∪ 𝑇 − .…”