Automatic instantiation of abstract tests on specific configurations for large critical control systems

Computer-based control systems have grown in size, complexity, distribution and criticality. In this paper a methodology is presented to perform an abstract testing of such large control systems in an efficient way: an abstract test is specified directly from system functional requirements and has to be instantiated in more test runs to cover a specific configuration, comprising any number of control entities (sensors, actuators and logic processes). Such a process is usually performed by hand for each installation of the control system, requiring a considerable time effort and being an error prone verification activity. To automate a safe passage from abstract tests, related to the so called generic software application, to any specific installation, an algorithm is provided, starting from a reference architecture and a state-based behavioural model of the control software. The presented approach has been applied to a railway interlocking system, demonstrating its feasibility and effectiveness in several years of testing experience

Refinement for user interface designs

Formal approaches to software development require that we correctly describe (or specify) systems in order to prove properties about our proposed solution prior to building it. We must then follow a rigorous process to transform our specification into an implementation to ensure that the properties we have proved are retained. Different transformation, or refinement, methods exist for different formal methods, but they all seek to ensure that we can guide the transformation in a way which preserves the desired properties of the system. Refinement methods also allow us to subsequently compare two systems to see if a refinement relation exists between the two. When we design and build the user interfaces of our systems we are similarly keen to ensure that they have certain properties before we build them. For example, do they satisfy the requirements of the user? Are they designed with known good design principles and usability considerations in mind? Are they correct in terms of the overall system specification? However, when we come to implement our interface designs we do not have a defined process to follow which ensures that we maintain these properties as we transform the design into code. Instead, we rely on our judgement and belief that we are doing the right thing and subsequent user testing to ensure that our final solution remains useable and satisfactory. We suggest an alternative approach, which is to define a refinement process for user interfaces which will allow us to maintain the same rigorous standards we apply to the rest of the system when we implement our user interface designs

Modeling, Simulation and Emulation of Intelligent Domotic Environments

Intelligent Domotic Environments are a promising approach, based on semantic models and commercially off-the-shelf domotic technologies, to realize new intelligent buildings, but such complexity requires innovative design methodologies and tools for ensuring correctness. Suitable simulation and emulation approaches and tools must be adopted to allow designers to experiment with their ideas and to incrementally verify designed policies in a scenario where the environment is partly emulated and partly composed of real devices. This paper describes a framework, which exploits UML2.0 state diagrams for automatic generation of device simulators from ontology-based descriptions of domotic environments. The DogSim simulator may simulate a complete building automation system in software, or may be integrated in the Dog Gateway, allowing partial simulation of virtual devices alongside with real devices. Experiments on a real home show that the approach is feasible and can easily address both simulation and emulation requirement

A Holistic Approach in Embedded System Development

We present pState, a tool for developing "complex" embedded systems by integrating validation into the design process. The goal is to reduce validation time. To this end, qualitative and quantitative properties are specified in system models expressed as pCharts, an extended version of hierarchical state machines. These properties are specified in an intuitive way such that they can be written by engineers who are domain experts, without needing to be familiar with temporal logic. From the system model, executable code that preserves the verified properties is generated. The design is documented on the model and the documentation is passed as comments into the generated code. On the series of examples we illustrate how models and properties are specified using pState.Comment: In Proceedings F-IDE 2015, arXiv:1508.0338