Details

Autor(en) / Beteiligte

• Petriu, Dorina C.

Titel

Integrating the analysis of multiple non-functional properties in model-driven engineering

Ist Teil von

• Software and systems modeling, 2021-12, Vol.20 (6), p.1777-1791

Ort / Verlag

Berlin/Heidelberg: Springer Berlin Heidelberg

Erscheinungsjahr

2021

Link zum Volltext

Quelle

SpringerLink (Online service)

Beschreibungen/Notizen

• This paper discusses the progress made so far and future challenges in integrating the analysis of multiple Non-Functional Properties (NFP) (such as performance, schedulability, reliability, availability, scalability, security, safety, and maintainability) into the Model-Driven Engineering (MDE) process. The goal is to guide the design choices from an early stage and to ensure that the system under construction will meet its non-functional requirements. The evaluation of the NFPs considered in this paper uses various kinds of NFP analysis models (also known as quality models) based on existent formalisms and tools developed over the years. Examples are queueing networks, stochastic Petri nets, stochastic process algebras, Markov chains, fault trees, probabilistic time automata, etc. In the MDE context, these models are automatically derived by model transformations from the software models built for development. Developing software systems that exhibit a good trade-off between multiple NFPs is difficult because the design of the software under construction and its underlying platforms have a large number of degrees of freedom spanning a very large discontinuous design space, which cannot be exhaustively explored. Another challenge in balancing the NFPs of a system under construction is due to the fact that some NFPs are conflicting—when one gets better the other gets worse—so an appropriate software process is needed to evaluate and balance all the non-functional requirements. The integration approach discussed in this paper is based on an ecosystem of inter-related heterogeneous modeling artifacts intended to support the following features: feedback of analysis results, consistent co-evolution of the software and analysis models, cross-model traceability, incremental propagation of changes across models, (semi)automated software process steps, and metaheuristics for reducing the design space size to be explored.