Formal methods for a system of systems analysis framework applied to traffic management

Formal methods for systems and system of systems engineering (SoSE) can bring precision to architecting and design, and increased trustworthiness in verification; but they require the use of formal languages that are not broadly comprehensible to the various stakeholders. The evolution of Model Based Systems Engineering (MBSE) using the Systems Modeling Language (SysML) lies in a middle ground between legacy document-based SoSE and formal methods. SysML is a graphical language but not a formal language. Initiatives in the Object Management Group (OMG), such as the development of the Foundational Unified Modeling Language (fUML) seek to bring precise semantics to object-oriented modeling languages. Following the philosophy of fUML, we offer a framework for associating precise semantics with Unified Modeling Language (UML) and SysML models essential for SoSE architecting and design. Straightforward methods are prescribed to develop the essential models and to create semantic transformations between them. Matrix representations can be used to perform analyses that are concordant with the system of UML or SysML models that represent the system or SoS. The framework and methods developed in this paper are applied to a Traffic Management system of systems (TMSoS) that has been a subject of research presented at previous IEEE SoSE conferences

A formal transformation method for automated fault tree generation from a UML activity model

IEEE Fault analysis and resolution of faults should be part of any end-to-end system development process. This paper is concerned with developing a formal transformation method that maps control flows modeled in unified modeling language activities to semantically equivalent fault trees. The transformation method developed features the use of propositional calculus and probability theory. Fault propagation chains are introduced to facilitate the method. An overarching metamodel comprised of transformations between models is developed and is applied to an understood traffic management system of systems problem to demonstrate the approach. In this way, the relational structure of the system behavior model is reflected in the structure of the fault tree. The paper concludes with a discussion of limitations of the transformation method and proposes approaches to extend it to object flows, state machines, and functional allocations

Formal methods for a system of systems analysis framework applied to traffic management

Formal methods for systems and system of systems engineering (SoSE) can bring precision to architecting and design, and increased trustworthiness in verification; but they require the use of formal languages that are not broadly comprehensible to the various stakeholders. The evolution of Model Based Systems Engineering (MBSE) using the Systems Modeling Language (SysML) lies in a middle ground between legacy document-based SoSE and formal methods. SysML is a graphical language but not a formal language. Initiatives in the Object Management Group (OMG), such as the development of the Foundational Unified Modeling Language (fUML) seek to bring precise semantics to object-oriented modeling languages. Following the philosophy of fUML, we offer a framework for associating precise semantics with Unified Modeling Language (UML) and SysML models essential for SoSE architecting and design. Straightforward methods are prescribed to develop the essential models and to create semantic transformations between them. Matrix representations can be used to perform analyses that are concordant with the system of UML or SysML models that represent the system or SoS. The framework and methods developed in this paper are applied to a Traffic Management system of systems (TMSoS) that has been a subject of research presented at previous IEEE SoSE conferences

A demonstration of a service oriented virtual environment for complex system analysis

Distributed virtual simulation is increasingly in demand within the automotive industry. A distributed and networked approach to system level design and simulation stands to benefit from a unifying relational oriented modeling and simulation framework. This will permit innovative use of existing independent simulations for increased concurrency in design and verification and validation. This paper demonstrates an analysis of the vehicle as a complex system through the combination of a relational framework, high level syntax and semantics for representing models and distributed simulation. This promises to provide a rigorous, traceable and agile approach to conceptual vehicle design and analysis

Conversational intelligent tutoring systems for online learning: what do students and tutors say?

A futuristic Technology Enhanced Learning concept, a conversational Intelligent Tutoring System (ITS) for deployment in an e-learning context, is gradually becoming a reality thanks to the continuous advancement in Artificial Intelligence and to the worldwide increasing demand for online learning, especially during the pandemic. However, we do need to consider whether such technology will support student learning or make learning more difficult. In the absence of a mature conversational Intelligent Tutoring System, this article aims to address this question indirectly through an investigation of how students and tutors in an online learning programme perceive the concept of conversational Intelligent Tutoring Systems, such as a chatbot, for online learning. This is achieved by surveying students who are currently enrolled in an online programme and interviewing the tutors on the same programme. The research concludes that ITS would very likely enhance online learning experience for both students and tutors, but there are various concerns that must be addressed

BSafeML Research Data

  BSafeML is a SysML and SafeML profile that provides a model-based approach to hazard management. In this repository, we provide the relevant research data that are being cited in the paper, titled, 'BSafeML: A Model-based Hazard Management Technique based on SysML and SafeML'. There are four pieces of research data included Research Data A, which includes the XML file for the BSafeML profile that can be imported in any modeling environment, a 'readme' file that provides the instruction on how the profile can be imported and used in Sparx Enterprise Architect, and the application of BSafeML to the GDF case study. Research Data B, which is a text-based definition of BSafeML, to facilitate independent implementation of BSafeML. Research Data C, which includes diagrams extracted from the model as in Research Data A. Research Data D, which is the questionnaire designed to qualitatively evaluate BSafeML with relevant stakeholders. </ul

BSafeML: a model-based hazard management technique for safety-critical systems development

Effective management of hazards is at the heart of achieving acceptable safety for any safety-critical system. With the recent advancement in model-based systems engineering, various hazard management techniques have been proposed as a means to transition from a document-based paradigm, such as hazard logs implemented in a relational database to a model-based paradigm with standardized modeling languages. However, a review of the state-of-the-art has shown that the existing methods do not provide sufficient traceability to integrate hazard management with other system lifecycle activities. To address this gap, a new model-based hazard management technique, BSafeML, is developed. BSafeML is a unified modeling language profile, and a procedure extending the existing systems modeling language and SafeML profiles with language for modeling the behavior of hazards and mitigations. BSafeML integrates the structural and behavioral views of hazards, supporting traceability and semantic consistency over them and with the wider system-of-interest. Specific behaviors supported by BSafeML include accident sequences and ordered action of safety functions. BSafeML is evaluated in a case study of a waste package emplacement system in the context of geological disposal of radioactive waste. A hazard log, including a range of hazard types, is converted to model-based format with BSafeML. The evaluation is further supported by a stakeholder survey that revealed mostly positive attitudes toward the safety function modeling by BSafeML.</p

Analysis of the vehicle as a complex system, EPSRC

Analysis of the vehicle as a complex system, EPSR

Requirements rationalization and synthesis enabled by model synchronization

In the international standard for system and software engineering ISO/IEC/IEEE 15288: 2015, the output of the stakeholder needs and the business or mission analysis technical processes are transformed into a technical view of the system by the system requirements definition process. In model-based systems engineering, functional needs can be modeled by use case diagrams. Intended outcomes of system requirements definition include resolution of disagreement about requirements, explicit agreement between stakeholders, and traceability. However, stakeholder needs are often elicited in a siloed manner and may be inconsistent. The lack of mathematically based systematic approaches for requirements definition poses a challenge to model-based transformation of needs into a technical view of the system that achieves agreement between stakeholders. This article specifies and demonstrates mathematical frameworks for rationalizing and synthesizing functional needs that have been captured through an elicitation process. Benefits of this approach include but are not limited to supporting rigorous identification and resolution of disagreements and facilitating systematic analysis of change impact to achieve stakeholder agreement all with minimal intervention by the system engineers. </p

The exploration of the future teaching mode in post-pandemic higher education

Covid-19 has changed the study life of many people with many courses in higher education being moved online. With the situation continuing like this, it is worthwhile to ask the questions such as: is the current provision of online education effective? Will the pandemic change higher education for ever? And what is the future of higher education post-pandemic? To answer these questions, we have conducted a survey to the students at the University of York. The survey provides some clarifications for the current state of online learning. It is discovered that while the adoption of online learning is continuously increasing, the current provision of online teaching during the pandemic has plenty of room to improve. Most participants believe that blended learning e.g. flipped classroom is the future of education post-pandemic; this is in contrast with a small number of participants who believe the in-class teaching is the future of education. In the process of arriving the conclusion, we have also learned a number of best practices for online learning. It is anticipated that the evidence collected from this study will shed light for university senior management to make strategic decisions in preparation for the future of education post-pandemic