A model driven approach to analysis and synthesis of sequence diagrams

Software design is a vital phase in a software development life cycle as it creates a blueprint for the implementation of the software. It is crucial that software designs are error-free since any unresolved design-errors could lead to costly implementation errors. To minimize these errors, the software community adopted the concept of modelling from various other engineering disciplines. Modelling provides a platform to create and share abstract or conceptual representations of the software system – leading to various modelling languages, among them Unified Modelling Language (UML) and Petri Nets. While Petri Nets strong mathematical capability allows various formal analyses to be performed on the models, UMLs user-friendly nature presented a more appealing platform for system designers. Using Multi Paradigm Modelling, this thesis presents an approach where system designers may have the best of both worlds; SD2PN, a model transformation that maps UML Sequence Diagrams into Petri Nets allows system designers to perform modelling in UML while still using Petri Nets to perform the analysis. Multi Paradigm Modelling also provided a platform for a well-established theory in Petri Nets – synthesis to be adopted into Sequence Diagram as a method of putting-together different Sequence Diagrams based on a set of techniques and algorithms

The ASSERT Virtual Machine Kernel: Support for preservation of temporal properties.

The ASSERT Project1 is aimed at defining new software engineering methods and tools for the development of critical embedded real-time systems in the aerospace domain. One of its main achievements is a new model-driven software process, which is based on the concept of property-preserving model transformations. Functional models developed with appropriate tools for the application domain are embedded in containers defining component interfaces and non-functional (e.g. timing) properties in a platform-independent set of notations. The resulting model is then automatically transformed to a platform-specific model using deployment information on target computer nodes, communication channels, and software platforms. Finally, source code for each computer node is automatically generated from the platform-specific model. The key element of the ASSERT process is that non-functional properties must be preserved during all phases of model transformations. In order to ensure that properties are preserved in model transformations and that the different views of each model are consistent with each other, a common meta-model has been defined which provides a formal basis to the whole process. This meta-model is called the Ravenscar Computational Model (RCM)

Model interoperability via model driven development

It is widely recognised that software development is a complex process. Among the factors that contribute to its inherent complexity is the gap between the design and the formal analysis domains. Software design is often considered a human oriented task while the analysis phase draws on formal representation and mathematical foundations. An example of this dichotomy is the use of UML for the software design phase and Petri Nets for the analysis; a separation of concerns that leads to the creation of heterogeneous models. Although UML is widely accepted as a language that can be used to model the structural and behavioural aspects of a system, its lack of mathematical foundations is seen as a serious impediment to rigorous analysis. Petri Nets on the other hand have a strong mathematical basis that is well suited for formal analysis; they lack however the appeal and the easeof-use of UML. A pressing concern for software developers is how to bridge the gap between these domains and allow for model interoperability and the integration of different toolsets across them, and thus reduce the complexity of the software development process. The aim of this paper is to present a Model Driven Development (MDD) model transformation which supports a seamless transition between UML and Petri Nets. This is achieved by model interoperability between UML Sequenc

A toolset for the development of mixed-criticality partitioned systems

The development of mixed-criticality virtualized multi-core systems poses new challenges that are being subject of active research work. There is an additional complexity: it is now required to identify a set of partitions, and allocate applications to partitions. In this job, a number of issues have to be considered, such as the criticality level of the application, security and dependability requirements, time requirements granularity, etc. MultiPARTES [11] toolset relies on Model Driven Engineering (MDE), which is a suitable approach in this setting, as it helps to bridge the gap between design issues and partitioning concerns. MDE is changing the way systems are developed nowadays, reducing development time. In general, modelling approaches have shown their benefits when applied to embedded systems. These benefits have been achieved by fostering reuse with an intensive use of abstractions, or automating the generation of boiler-plate code

SPaCIFY: a Formal Model-Driven Engineering for Spacecraft On-Board Software

International audienceThe aim of this article is to present a model- driven approach proposed by the SPaCIFY project for spacecraft on-board software development. This ap- proach is based on a formal globally asynchronous lo- cally synchronous language called Synoptic, and on a set of transformations allowing code generation and model verification

Automated Experiments for Deriving Performance-relevant Properties of Software Execution Environments

The execution environment can play a crucial role when analyzing the performance of a software system. However, detecting execution environment properties and integrating such properties into performance analyses is a manual, error-prone task. In this thesis, a novel approach for detecting performance-relevant properties of the software execution environment is presented. These properties are automatically detected using predefined experiments and integrated into performance prediction tools