Validate implementation correctness using simulation: the TASTE approach

High-integrity systems operate in hostile environment and must guarantee a continuous operational state, even if unexpected events happen. In addition, these systems have stringent requirements that must be validated and correctly translated from high-level specifications down to code. All these constraints make the overall development process more time-consuming. This becomes especially complex because the number of system functions keeps increasing over the years. As a result, engineers must validate system implementation and check that its execution conforms to the specifications. To do so, a traditional approach consists in a manual instrumentation of the implementation code to trace system activity while operating. However, this might be error-prone because modifications are not automatic and still made manually. Furthermore, such modifications may have an impact on the actual behavior of the system. In this paper, we present an approach to validate a system implementation by comparing execution against simulation. In that purpose, we adapt TASTE, a set of tools that eases system development by automating each step as much as possible. In particular, TASTE automates system implementation from functional (system functions description with their properties – period, deadline, priority, etc.) and deployment(processors, buses, devices to be used) models. We tailored this tool-chain to create traces during system execution. Generated output shows activation time of each task, usage of communication ports (size of the queues, instant of events pushed/pulled, etc.) and other relevant execution metrics to be monitored. As a consequence, system engineers can check implementation correctness by comparing simulation and execution metrics

Scheduling policies and system software architectures for mixed-criticality computing

Mixed-criticality model of computation is being increasingly adopted in timing-sensitive systems. The model not only ensures that the most critical tasks in a system never fails, but also aims for better systems resource utilization in normal condition. In this report, we describe the widely used mixed-criticality task model and fixed-priority scheduling algorithms for the model in uniprocessors. Because of the necessity by the mixed-criticality task model and scheduling policies, isolation, both temporal and spatial, among tasks is one of the main requirements from the system design point of view. Different virtualization techniques have been used to design system software architecture with the goal of isolation. We discuss such a few system software architectures which are being and can be used for mixed-criticality model of computation

Towards Automatic Learning of Heuristics for Mechanical Transformations of Procedural Code

The current trend in next-generation exascale systems goes towards integrating a wide range of specialized (co-)processors into traditional supercomputers. However, the integration of different specialized devices increases the degree of heterogeneity and the complexity in programming such type of systems. Due to the efficiency of heterogeneous systems in terms of Watt and FLOPS per surface unit, opening the access of heterogeneous platforms to a wider range of users is an important problem to be tackled. In order to bridge the gap between heterogeneous systems and programmers, in this paper we propose a machine learning-based approach to learn heuristics for defining transformation strategies of a program transformation system. Our approach proposes a novel combination of reinforcement learning and classification methods to efficiently tackle the problems inherent to this type of systems. Preliminary results demonstrate the suitability of the approach for easing the programmability of heterogeneous systems.Comment: Part of the Program Transformation for Programmability in Heterogeneous Architectures (PROHA) workshop, Barcelona, Spain, 12th March 2016, 9 pages, LaTe

Category Theory and Model-Driven Engineering: From Formal Semantics to Design Patterns and Beyond

There is a hidden intrigue in the title. CT is one of the most abstract mathematical disciplines, sometimes nicknamed "abstract nonsense". MDE is a recent trend in software development, industrially supported by standards, tools, and the status of a new "silver bullet". Surprisingly, categorical patterns turn out to be directly applicable to mathematical modeling of structures appearing in everyday MDE practice. Model merging, transformation, synchronization, and other important model management scenarios can be seen as executions of categorical specifications. Moreover, the paper aims to elucidate a claim that relationships between CT and MDE are more complex and richer than is normally assumed for "applied mathematics". CT provides a toolbox of design patterns and structural principles of real practical value for MDE. We will present examples of how an elementary categorical arrangement of a model management scenario reveals deficiencies in the architecture of modern tools automating the scenario.Comment: In Proceedings ACCAT 2012, arXiv:1208.430

Early aspects: aspect-oriented requirements engineering and architecture design

This paper reports on the third Early Aspects: Aspect-Oriented Requirements Engineering and Architecture Design Workshop, which has been held in Lancaster, UK, on March 21, 2004. The workshop included a presentation session and working sessions in which the particular topics on early aspects were discussed. The primary goal of the workshop was to focus on challenges to defining methodical software development processes for aspects from early on in the software life cycle and explore the potential of proposed methods and techniques to scale up to industrial applications

Integrated research in constitutive modelling at elevated temperatures, part 1

Topics covered include: numerical integration techniques; thermodynamics and internal state variables; experimental lab development; comparison of models at room temperature; comparison of models at elevated temperature; and integrated software development