Digital Ecosystems: Ecosystem-Oriented Architectures

We view Digital Ecosystems to be the digital counterparts of biological ecosystems. Here, we are concerned with the creation of these Digital Ecosystems, exploiting the self-organising properties of biological ecosystems to evolve high-level software applications. Therefore, we created the Digital Ecosystem, a novel optimisation technique inspired by biological ecosystems, where the optimisation works at two levels: a first optimisation, migration of agents which are distributed in a decentralised peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. The Digital Ecosystem was then measured experimentally through simulations, with measures originating from theoretical ecology, evaluating its likeness to biological ecosystems. This included its responsiveness to requests for applications from the user base, as a measure of the ecological succession (ecosystem maturity). Overall, we have advanced the understanding of Digital Ecosystems, creating Ecosystem-Oriented Architectures where the word ecosystem is more than just a metaphor.Comment: 39 pages, 26 figures, journa

Managing evolution and change in web-based teaching and learning environments

The state of the art in information technology and educational technologies is evolving constantly. Courses taught are subject to constant change from organisational and subject-specific reasons. Evolution and change affect educators and developers of computer-based teaching and learning environments alike – both often being unprepared to respond effectively. A large number of educational systems are designed and developed without change and evolution in mind. We will present our approach to the design and maintenance of these systems in rapidly evolving environments and illustrate the consequences of evolution and change for these systems and for the educators and developers responsible for their implementation and deployment. We discuss various factors of change, illustrated by a Web-based virtual course, with the objective of raising an awareness of this issue of evolution and change in computer-supported teaching and learning environments. This discussion leads towards the establishment of a development and management framework for teaching and learning systems

Incremental Consistency Checking in Delta-oriented UML-Models for Automation Systems

Automation systems exist in many variants and may evolve over time in order to deal with different environment contexts or to fulfill changing customer requirements. This induces an increased complexity during design-time as well as tedious maintenance efforts. We already proposed a multi-perspective modeling approach to improve the development of such systems. It operates on different levels of abstraction by using well-known UML-models with activity, composite structure and state chart models. Each perspective was enriched with delta modeling to manage variability and evolution. As an extension, we now focus on the development of an efficient consistency checking method at several levels to ensure valid variants of the automation system. Consistency checking must be provided for each perspective in isolation, in-between the perspectives as well as after the application of a delta.Comment: In Proceedings FMSPLE 2016, arXiv:1603.0857