ISML: an interface specification meta-language

In this paper we present an abstract metaphor model situated within a model-based user interface framework. The inclusion of metaphors in graphical user interfaces is a well established, but mostly craft-based strategy to design. A substantial body of notations and tools can be found within the model-based user interface design literature, however an explicit treatment of metaphor and its mappings to other design views has yet to be addressed. We introduce the Interface Specification Meta-Language (ISML) framework and demonstrate its use in comparing the semantic and syntactic features of an interactive system. Challenges facing this research are outlined and further work proposed

Business-oriented development of telecommunication services

The development of software for distributed systems, e.g. telecommunication services, is a complex activity. Numerous issues have to be resolved when developing such systems, examples of which are language/system heterogeneity and remoteness of components. Interface definition languages (IDLs) are used as the basis for addressing some of these issues. IDLs allow for the specification of the syntactic aspects of the interfaces of the components in the system to be made. Whilst lending itself to issues of heterogeneity and location transparency, dealing with IDL as the basis for system development is not without its problems. Two of the main problems with IDL are its lack of behaviour and its lack of abstraction. Thus designers should not be constrained to work within the syntactic notations used to implement their systems, nor should they be unaided in how they might better design their systems. In this paper we show how these issues are being addressed in the TOSCA project in its development of a service creation and validation environment

System-of-Systems Complexity

The global availability of communication services makes it possible to interconnect independently developed systems, called constituent systems, to provide new synergistic services and more efficient economic processes. The characteristics of these new Systems-of-Systems are qualitatively different from the classic monolithic systems. In the first part of this presentation we elaborate on these differences, particularly with respect to the autonomy of the constituent systems, to dependability, continuous evolution, and emergence. In the second part we look at a SoS from the point of view of cognitive complexity. Cognitive complexity is seen as a relation between a model of an SoS and the observer. In order to understand the behavior of a large SoS we have to generate models of adequate simplicity, i.e, of a cognitive complexity that can be handled by the limited capabilities of the human mind. We will discuss the importance of properly specifying and placing the relied-upon message interfaces between the constituent systems that form an open SoS and discuss simplification strategies that help to reduce the cognitive complexity.Comment: In Proceedings AiSoS 2013, arXiv:1311.319

Abstraction and Learning for Infinite-State Compositional Verification

Despite many advances that enable the application of model checking techniques to the verification of large systems, the state-explosion problem remains the main challenge for scalability. Compositional verification addresses this challenge by decomposing the verification of a large system into the verification of its components. Recent techniques use learning-based approaches to automate compositional verification based on the assume-guarantee style reasoning. However, these techniques are only applicable to finite-state systems. In this work, we propose a new framework that interleaves abstraction and learning to perform automated compositional verification of infinite-state systems. We also discuss the role of learning and abstraction in the related context of interface generation for infinite-state components.Comment: In Proceedings Festschrift for Dave Schmidt, arXiv:1309.455

Reusing Test-Cases on Different Levels of Abstraction in a Model Based Development Tool

Seamless model based development aims to use models during all phases of the development process of a system. During the development process in a component-based approach, components of a system are described at qualitatively differing abstraction levels: during requirements engineering component models are rather abstract high-level and underspecified, while during implementation the component models are rather concrete and fully specified in order to enable code generation. An important issue that arises is assuring that the concrete models correspond to abstract models. In this paper, we propose a method to assure that concrete models for system components refine more abstract models for the same components. In particular we advocate a framework for reusing testcases at different abstraction levels. Our approach, even if it cannot completely prove the refinement, can be used to ensure confidence in the development process. In particular we are targeting the refinement of requirements which are represented as very abstract models. Besides a formal model of our approach, we discuss our experiences with the development of an Adaptive Cruise Control (ACC) system in a model driven development process. This uses extensions which we implemented for our model-based development tool and which are briefly presented in this paper.Comment: In Proceedings MBT 2012, arXiv:1202.582

An integrated architecture for shallow and deep processing

We present an architecture for the integration of shallow and deep NLP components which is aimed at flexible combination of different language technologies for a range of practical current and future applications. In particular, we describe the integration of a high-level HPSG parsing system with different high-performance shallow components, ranging from named entity recognition to chunk parsing and shallow clause recognition. The NLP components enrich a representation of natural language text with layers of new XML meta-information using a single shared data structure, called the text chart. We describe details of the integration methods, and show how information extraction and language checking applications for realworld German text benefit from a deep grammatical analysis

Mastering Heterogeneous Behavioural Models

Heterogeneity is one important feature of complex systems, leading to the complexity of their construction and analysis. Moving the heterogeneity at model level helps in mastering the difficulty of composing heterogeneous models which constitute a large system. We propose a method made of an algebra and structure morphisms to deal with the interaction of behavioural models, provided that they are compatible. We prove that heterogeneous models can interact in a safe way, and therefore complex heterogeneous systems can be built and analysed incrementally. The Uppaal tool is targeted for experimentations.Comment: 16 pages, a short version to appear in MEDI'201