Extending feature models with relative cardinalities

Abstract

Feature modeling is widely used to capture and manage commonalities and variabilities in software product lines. Cardinality-based feature models are used when variability applies not only to the selection or exclusion of features but also to the number of times a feature can be included in a product. Feature cardinalities are usually considered to apply in either a local or global scope. However, we have identified that these interpretations are insufficient to capture the variability of cloud environments. In this paper, we redefine cardinality-based feature models to allow multiple relative cardinalities between features and we discuss the effects of relative cardinalities on feature modeling semantics, consistency and cross-tree constraints. To evaluate our approach we conducted an analysis of relative cardinalities in four cloud computing providers. In addition, we developed tools for reasoning on feature models with relative cardinalities and performed experiments to verify the performance and scalability of the approach. The results from our study indicate that extending feature models with relative cardinalities is feasible and improves variability modeling, particularly in the case of cloud environments.

Software Product Line Engineering

“…Nevertheless, modeling the FQAs variability is more complex that only considering their high degree of variability. Since each FQA (e.g., encryption) can be applied in several points of the application with different configurations (e.g., RSA or AES algorithms), each FQA needs to be modeled as a clonable feature [24,60] (see Encryption [1.. *] in Figure 2).…”

“…We answer to this question by empirically analyzing the most usable tools. We use a running case study based on an SPL process with demanding characteristics such as clonable features [24,60], variable features [21,22], attributes [10], huge feature models, and so on (Section 5). RQ3: Is it possible to carry out a complete SPL process with the existing tool support?…”

Automated Setup of Multi-cloud Environments for Microservices Applications

“…Therefore, we rely on previous developments done on cardinality-based feature models [15] and on modeling cloud providers with feature models [16]. For expressing relative cardinalities and the complex constraints found in cloud providers, we also rely on the results of our previous work on extending feature models with relative cardinalities [17].…”

“…This is a complex and time consuming task that involves translating the feature model to a constraint satisfaction problem and solving it to find a valid configuration that matches the requirements. This translation is based on existing work [24] and our previous developments [17] in cardinality-based feature models. If a solution to the corresponding constraint problem is found it means that the assignment is valid.…”