Holger Rendel

Delta-oriented architectural variability using MontiCore

Modeling of software architectures is a fundamental part of software development processes. Reuse of software components and early analysis of software topologies allow the reduction of development costs and increases software quality. Integrating variability modeling concepts into architecture description languages (ADLs) is essential for the development of diverse software systems with high demands on software quality. In this paper, we present the integration of delta modeling into the existing ADL MontiArc. Delta modeling is a language-independent variability modeling approach supporting proactive, reactive and extractive product line development. We show how Δ-MontiArc, a language for explicit modeling of architectural variability based on delta modeling, is implemented as domain-specific language (DSL) using the DSL development framework MontiCore. We also demonstrate how MontiCores language reuse mechanisms provide efficient means to derive an implementation of Δ-MontiArc tool implementation. We evaluate Δ-MontiArc by comparing it with annotative variability modeling.

Evolving delta-oriented software product line architectures

Diversity is prevalent in modern software systems. Several system variants exist at the same time in order to adapt to changing user requirements. Additionally, software systems evolve over time in order to adjust to unanticipated changes in their application environment. In modern software development, software architecture modeling is an important means to deal with system complexity by architectural decomposition. This leads to the need of architectural description languages that can represent spatial and temporal variability. In this paper, we present delta modeling of software architectures as a uniform modeling formalism for architectural variability in space and in time. In order to avoid degeneration of the product line model under system evolution, we present refactoring techniques to maintain and improve the quality of the variability model. Using a running example from the automotive domain, we evaluate our approach by carrying out a case study that compares delta modeling with annotative variability modeling.

Evaluation of Variability Concepts for Simulink in the Automotive Domain

Modeling variability in Matlab/Simulink becomes more and more important. We took the two variability modeling concepts already included in Matlab/Simulink and our own one and evaluated them to find out which one is suited best for modeling variability in the automotive domain. We conducted a controlled experiment with developers at Volkswagen AG to decide which concept is preferred by developers and if their preference aligns with measurable performance factors. We found out that all existing concepts are viable approaches and that the delta approach is both the preferred concept as well as the objectively most efficient one, which makes Delta-Simulink a good solution to model variability in the automotive domain.