PP 1593: ENsurance of Software evolUtion by Run-time cErtification II

Facts

Run time
01/2016  – 08/2019
DFG subject areas

Software Engineering and Programming Languages

Sponsors

DFG Individual Research Grant DFG Individual Research Grant

Description

Quality attributes play an important role in different classes of software systems, e.g. safety in embedded systems and performance in business information systems. Currently, quality requirements are typically checked at design time. For evolving systems with changing environmental conditions this leads to the problem that the system may behave differently with respect to quality attributes than analysed at design time. ENSURE proposes to address this problem by developing a holistic model-driven approach, which treats quality evaluation models as first class entities. This approach used dedicated model transformations to evolve quality evaluation models with structural and behavioural models. In the first phase, we developed a co-evolution approach for architectural as well as quality evaluation models which supports incremental change propagation between the models. This is complemented by an approach to efficiently learn the attributes of the quality evaluation models from the actual running system and an approach to specify the quality properties to analyse using controlled natural language. Complementary to these activities, we empirically studied model-driven engineering and its challenges related to our topics as well as how meta models of modelling languages evolve. We participated in both demonstrators, focusing on the Pick and Place Unit (PPU), and evaluated our approach on the PPU case study. In the second phase, we will extend our co-evolution approach by providing recommendation support for cases where the co-evolution specifications do not provide deterministic co-evolution using machines learning techniques on model histories. The second major extension is exploiting the information from the model changes, from the co-evolution for performance improvement of the quality analysis by an incremental approach. Finally, we will empirically study and evaluate the results from both phases with experts from industry as well as both demonstrators of the SPP. We will continue to be well integrated in the activities of the SPP.