An implementation of the behavior annex in the AADL-toolset Osate2

AADL is a modeling language to design and analyze High-Integrity Distributed and Real-time systems. Embedded sub-languages published as AADL annexes extend an AADL model to enhance analysis. The behavior annex specifies the behavior of an AADL application model. An implantation of this annex allows to perform behavior analysis. In addition, as there are several AADL annexes, the implementation of generic mechanisms to support each one of them is challenging. The behavior annex is a valid candidate to illustrate these challenges by combining several sub-languages. In this paper we expose our experiment to support the behavior annex in the reference AADL toolset OSATE2. This one, supports the AADL version 2 by providing a front-end and a set of analysis plug-ins to analyze an AADL model

Data in Business Process Models. A Preliminary Empirical Study

Traditional activity-centric process modeling languages treat data as simple black boxes acting as input or output for activities. Many alternate and emerging process modeling paradigms, such as case handling and artifact-centric process modeling, give data a more central role. This is achieved by introducing lifecycles and states for data objects, which is beneficial when modeling data-or knowledge-intensive processes. We assume that traditional activity-centric process modeling languages lack the capabilities to adequately capture the complexity of such processes. To verify this assumption we conducted an online interview among BPM experts. The results not only allow us to identify various profiles of persons modeling business processes, but also the problems that exist in contemporary modeling languages w.r.t. The modeling of business data. Overall, this preliminary empirical study confirms the necessity of data-awareness in process modeling notations in general

Model-driven engineering approach to design and implementation of robot control system

In this paper we apply a model-driven engineering approach to designing domain-specific solutions for robot control system development. We present a case study of the complete process, including identification of the domain meta-model, graphical notation definition and source code generation for subsumption architecture -- a well-known example of robot control architecture. Our goal is to show that both the definition of the robot-control architecture and its supporting tools fits well into the typical workflow of model-driven engineering development.Comment: Presented at DSLRob 2011 (arXiv:cs/1212.3308