Clafer: Lightweight Modeling of Structure, Behaviour, and Variability

Embedded software is growing fast in size and complexity, leading to intimate mixture of complex architectures and complex control. Consequently, software specification requires modeling both structures and behaviour of systems. Unfortunately, existing languages do not integrate these aspects well, usually prioritizing one of them. It is common to develop a separate language for each of these facets. In this paper, we contribute Clafer: a small language that attempts to tackle this challenge. It combines rich structural modeling with state of the art behavioural formalisms. We are not aware of any other modeling language that seamlessly combines these facets common to system and software modeling. We show how Clafer, in a single unified syntax and semantics, allows capturing feature models (variability), component models, discrete control models (automata) and variability encompassing all these aspects. The language is built on top of first order logic with quantifiers over basic entities (for modeling structures) combined with linear temporal logic (for modeling behaviour). On top of this semantic foundation we build a simple but expressive syntax, enriched with carefully selected syntactic expansions that cover hierarchical modeling, associations, automata, scenarios, and Dwyer's property patterns. We evaluate Clafer using a power window case study, and comparing it against other notations that substantially overlap with its scope (SysML, AADL, Temporal OCL and Live Sequence Charts), discussing benefits and perils of using a single notation for the purpose

Multibody modeling and verification

A summary of a ten week project on flexible multibody modeling, verification and control is presented. Emphasis was on the need for experimental verification. A literature survey was conducted for gathering information on the existence of experimental work related to flexible multibody systems. The first portion of the assigned task encompassed the modeling aspects of flexible multibodies that can undergo large angular displacements. Research in the area of modeling aspects were also surveyed, with special attention given to the component mode approach. Resulting from this is a research plan on various modeling aspects to be investigated over the next year. The relationship between the large angular displacements, boundary conditions, mode selection, and system modes is of particular interest. The other portion of the assigned task was the generation of a test plan for experimental verification of analytical and/or computer analysis techniques used for flexible multibody systems. Based on current and expected frequency ranges of flexible multibody systems to be used in space applications, an initial test article was selected and designed. A preliminary TREETOPS computer analysis was run to ensure frequency content in the low frequency range, 0.1 to 50 Hz. The initial specifications of experimental measurement and instrumentation components were also generated. Resulting from this effort is the initial multi-phase plan for a Ground Test Facility of Flexible Multibody Systems for Modeling Verification and Control. The plan focusses on the Multibody Modeling and Verification (MMV) Laboratory. General requirements of the Unobtrusive Sensor and Effector (USE) and the Robot Enhancement (RE) laboratories were considered during the laboratory development

The Performability Manager

The authors describe the performability manager, a distributed system component that contributes to a more effective and efficient use of system components and prevents quality of service (QoS) degradation. The performability manager dynamically reconfigures distributed systems whenever needed, to recover from failures and to permit the system to evolve over time and include new functionality. Large systems require dynamic reconfiguration to support dynamic change without shutting down the complete system. A distributed system monitor is needed to verify QoS. Monitoring a distributed system is difficult because of synchronization problems and minor differences in clock speeds. The authors describe the functionality and the operation of the performability manager (both informally and formally). Throughout the paper they illustrate the approach by an example distributed application: an ANSAware-based number translation service (NTS), from the intelligent networks (IN) area