120,662 research outputs found

    A Graph Rewriting Approach for Transformational Design of Digital Systems

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    Transformational design integrates design and verification. It combines “correctness by construction” and design creativity by the use of pre-proven behaviour preserving transformations as design steps. The formal aspects of this methodology are hidden in the transformations. A constraint is the availability of a design representation with a compositional formal semantics. Graph representations are useful design representations because of their visualisation of design information. In this paper graph rewriting theory, as developed in the last twenty years in mathematics, is shown to be a useful basis for a formal framework for transformational design. The semantic aspects of graphs which are no part of graph rewriting theory are included by the use of attributed graphs. The used attribute algebra, table algebra, is a relation algebra derived from database theory. The combination of graph rewriting, table algebra and transformational design is new

    BeSpaceD: Towards a Tool Framework and Methodology for the Specification and Verification of Spatial Behavior of Distributed Software Component Systems

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    In this report, we present work towards a framework for modeling and checking behavior of spatially distributed component systems. Design goals of our framework are the ability to model spatial behavior in a component oriented, simple and intuitive way, the possibility to automatically analyse and verify systems and integration possibilities with other modeling and verification tools. We present examples and the verification steps necessary to prove properties such as range coverage or the absence of collisions between components and technical details

    Leveraging language models semantic similarity capabilities to facilitate information reuse in system engineering

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    Model-Based Systems Engineering (MBSE) is a powerful approach for designing complex engineering systems, which also generates valuable data after each conducted study. However, currently there are few to no approaches for reusing this information in a systematic way. In this paper, we propose using state-of-the-art Natural Language Processing (NLP) methods and a graph database to analyze data from past missions and facilitate the design process of new missions. In particular, we firstly develop techniques for analysing a database of past-mission requirements. This includes the ability to identify semantic similar requirements from past missions for a given new requirement. We also fine-tune a language model in order to analyse the logical traceability between two requirements. These methods are meant to enable engineers to more efficiently define the requirement space for a new spacecraft.Secondly, we develop methods to analyse the physical and functional architectures of past missions. Based on an input for a new design, a graph database of past-mission design can be queried for similar design choices and functionalities by again leveraging the abilities of semantic similarity and a specialised breadth-first-search algorithm. Finally, we show how both the requirement and design analyses could be combined in order to automatically verify if the provisions of a requirements are reflected in the physical architecture. For this analysis, a language model is used to extract core concepts from a requirement. Then, in a second step, the concepts from the requirement are mapped to nodes in the graph database. For the actual verification, a relevant extract of the graph together with the requirement are then used as input for a large language model, which is prompted to reason if the requirement is fulfilled or not. By leveraging NLP and graph search techniques, we believe that these approaches can lead to more efficient and effective design processes for complex engineering systems by reusing information from past designs. The proposed techniques have been developed and tested on real past-mission requirements and design architectures in collaboration with Thales Alenia Space, RHEA group, and the European Space Agency

    Formal and efficient verification techniques for Real-Time UML models

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    The real-time UML profile TURTLE has a formal semantics expressed by translation into a timed process algebra: RT-LOTOS. RTL, the formal verification tool developed for RT-LOTOS, was first used to check TURTLE models against design errors. This paper opens new avenues for TURTLE model verification. It shows how recent work on translating RT-LOTOS specifications into Time Petri net model may be applied to TURTLE. RT-LOTOS to TPN translation patterns are presented. Their formal proof is the subject of another paper. These patterns have been implemented in a RT-LOTOS to TPN translator which has been interfaced with TINA, a Time Petri Net Analyzer which implements several reachability analysis procedures depending on the class of property to be verified. The paper illustrates the benefits of the TURTLE->RT-LOTOS->TPN transformation chain on an avionic case study

    Sciduction: Combining Induction, Deduction, and Structure for Verification and Synthesis

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    Even with impressive advances in automated formal methods, certain problems in system verification and synthesis remain challenging. Examples include the verification of quantitative properties of software involving constraints on timing and energy consumption, and the automatic synthesis of systems from specifications. The major challenges include environment modeling, incompleteness in specifications, and the complexity of underlying decision problems. This position paper proposes sciduction, an approach to tackle these challenges by integrating inductive inference, deductive reasoning, and structure hypotheses. Deductive reasoning, which leads from general rules or concepts to conclusions about specific problem instances, includes techniques such as logical inference and constraint solving. Inductive inference, which generalizes from specific instances to yield a concept, includes algorithmic learning from examples. Structure hypotheses are used to define the class of artifacts, such as invariants or program fragments, generated during verification or synthesis. Sciduction constrains inductive and deductive reasoning using structure hypotheses, and actively combines inductive and deductive reasoning: for instance, deductive techniques generate examples for learning, and inductive reasoning is used to guide the deductive engines. We illustrate this approach with three applications: (i) timing analysis of software; (ii) synthesis of loop-free programs, and (iii) controller synthesis for hybrid systems. Some future applications are also discussed

    Controlling Concurrent Change - A Multiview Approach Toward Updatable Vehicle Automation Systems

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    The development of SAE Level 3+ vehicles [{SAE}, 2014] poses new challenges not only for the functional development, but also for design and development processes. Such systems consist of a growing number of interconnected functional, as well as hardware and software components, making safety design increasingly difficult. In order to cope with emergent behavior at the vehicle level, thorough systems engineering becomes a key requirement, which enables traceability between different design viewpoints. Ensuring traceability is a key factor towards an efficient validation and verification of such systems. Formal models can in turn assist in keeping track of how the different viewpoints relate to each other and how the interplay of components affects the overall system behavior. Based on experience from the project Controlling Concurrent Change, this paper presents an approach towards model-based integration and verification of a cause effect chain for a component-based vehicle automation system. It reasons on a cross-layer model of the resulting system, which covers necessary aspects of a design in individual architectural views, e.g. safety and timing. In the synthesis stage of integration, our approach is capable of inserting enforcement mechanisms into the design to ensure adherence to the model. We present a use case description for an environment perception system, starting with a functional architecture, which is the basis for componentization of the cause effect chain. By tying the vehicle architecture to the cross-layer integration model, we are able to map the reasoning done during verification to vehicle behavior
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