15,304 research outputs found

    Analysis as first-class citizens – an application to Architecture Description Languages

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    Architecture Description Languages (ADLs) support modeling and analysis of systems through models transformation and exploration. Various contributions made proposals to bring verification capabilities to designers through model-based frame- works and illustrated benefits to the overall system quality. Model-level analyses are usually performed as an exogenous, unidirectional and semantically weak transformation towards a third-party model. We claim such process can be incomplete and/or inefficient because gathered results lead to evolution of the primary model. This is particularly problematic for the design of Distributed Real-Time Embedded (DRE) systems that has to tackle many concerns like time, security or safety. In this paper, we argue why analysis should no longer be considered as a side step in the design process but, rather, should be embedded as a first-class citizen in the model itself. We review several standardized architecture description languages, which consider analysis as a goal. As an element of solution, we introduce current work on the definition of a language dedicated to the analysis of models within the scope of one particular ADL, namely the Architecture Analysis and Design Language (AADL)

    Managing knowledge for capability engineering

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    The enterprises that deliver capability are trying to evolve into through-life businesses by shifting away from the traditional pattern of designing and manufacturing successive generations of products, towards a new paradigm centred on support, sustainability and the incremental enhancements of existing capabilities from technology insertions and changes to process. The provision of seamless through-life customer solutions depends heavily on management of information and knowledge between, and within the different parts of the supply chain enterprise. This research characterised and described Capability Engineering (CE) as applied in the defence enterprise and identified to BAE Systems important considerations for managing knowledge within that context. The terms Capability Engineering and Through Life Capability Management (TLCM), used synonymously in this thesis, denote a complex evolving domain that requires new approaches to better understand the different viewpoints, models and practices. The findings and novelty of this research is demonstrated through the following achievements: Defined the problem space that Requirements Engineers can use in through-life management projects. Made a contribution to the development of models for Systems Architects to enable them to incorporate ‘soft’ systems within their consideration. Independently developed a TLCM activity model against which BAE Systems validated the BAE Systems TLCM activity model, which is now used by UK Ministry of Defence (MoD). Developed, and published within INCOSE1, the INCOSE Capability Engineering ontology. Through the novel analysis of a directly applicable case study, highlighted to Functional Delivery Managers the significance of avoiding the decoupling of information and knowledge in the context of TLCM. Through experimentation and knowledge gained within this research, identified inadequacies in the TechniCall (rapid access to experts) service which led to the generation of requirements for an improved service which is now being implemented by BAE Systems. The results showed that managing knowledge is distinct when compared to information management. Over-reliance on information management in the absence of tacit knowledge can lead to a loss in the value of the information, which can result in unintended consequences. Capability is realised through a combination of component systems and Capability Engineering is equivalent to a holistic perspective of Systems Engineering. A sector-independent Capability Engineering ontology is developed to enable semantic interoperability between different domains i.e. defence, rail and information technology. This helped to better understand the dependencies of contributing component systems within defence, and supported collaboration across different domains. Although the evaluation of the ontology through expert review has been accomplished; the ontology, KM analysis framework and soft systems transitioning approach developed still need to undergo independent verification and validation. This requires application to other case studies to check and exploit their suitability. This Engineering Doctorate research has been disseminated through a number of peer reviewed publications

    A Semi-Automated Approach for the Co-Refinement of Requirements and Architecture Models

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    Requirements and architecture specifications are strongly related as the second provides a solution to a problem stated by the first. This coupling is typically realized by traceability links and maintaining such links becomes extremely difficult as both requirements and architecture specifications frequently evolve, and in particular when the architecture is refined providing an increasing level of details. In such case, not only the traceability must evolve but the requirements must be refined as well. We present a novel semi-automated approach to evolve non-functional requirements and their traceability links following system's architecture refinement in the context of design space exploration and automated code generation. The approach has been prototyped for AADL models refined with the RAMSES tool and for model transformations implemented as Story Diagrams

    Traceability support in software product lines

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    Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Informática.Traceability is becoming a necessary quality of any modern software system. The complexity in modern systems is such that, if we cannot rely on good techniques and tools it becomes an unsustainable burden, where software artifacts can hardly be linked to their initial requirements. Modern software systems are composed by a many artifacts (models, code, etc.). Any change in one of them may have repercussions on many components. The assessment of this impact usually comes at a high cost and is highly error-prone. This complexity inherent to software development increases when it comes to Software Product Line Engineering. Traceability aims to respond to this challenge, by linking all the software artifacts that are used, in order to reason about how they influence each others. We propose to specify, design and implement an extensible Traceability Framework that will allow developers to provide traceability for a product line, or the possibility to extend it for other development scenarios. This MSc thesis work is to develop an extensible framework, using Model-Driven techniques and technologies, to provide traceability support for product lines. We also wish to provide basic and advanced traceability queries, and traceability views designed for the needs of each user

    Integration of Quality Attributes in Software Product Line Development

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    Different approaches for building modern software systems in complex and open environments have been proposed in the last few years. Some efforts try to apply Software Product Line (SPL) approach to take advantage of the massive reuse for producing software systems that share a common set of features. In general quality assurance is a crucial activity for success in software industry, but it is even more important when talking about Software Product Lines since the intensive reuse of assets makes the quality attributes (a measurable physical or abstract property of an entity) of the assets to be transmitted to the whole SPL scope. However, despite the importance that quality has in software product line development, most of the methodologies being applied in Software Product Line Development focus only on managing the commonalities and variability within the product line and not giving support to the non--¿ functional requirements that the products must fit. The main goal of this master final work is to introduce quality attributes in early stages of software product line development processes by means of the definition of a production plan that, on one hand, integrates quality as an additional view for describing the extension of the software product line and, on the other hand introduces the quality attributes as a decision factor during product configuration and when selecting among design alternatives. Our approach has been defined following the Model--¿ Driven Software Development paradigm. Therefore all the software artifacts defined had its correspondent metamodels and the processes defined rely on automated model transformations. Finally in order to illustrate the feasibility of the approach we have integrated the quality view in an SPL example in the context of safety critical embedded systems on the automotive domain.González Huerta, J. (2011). Integration of Quality Attributes in Software Product Line Development. http://hdl.handle.net/10251/15835Archivo delegad

    A model-based approach to System of Systems risk management

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    The failure of many System of Systems (SoS) enterprises can be attributed to the inappropriate application of traditional Systems Engineering (SE) processes within the SoS domain, because of the mistaken belief that a SoS can be regarded as a single large, or complex, system. SoS Engineering (SoSE) is a sub-discipline of SE; Risk Management and Modelling and Simulation (M&S) are key areas within SoSE, both of which also lie within the traditional SE domain. Risk Management of SoS requires a different approach to that currently taken for individual systems; if risk is managed for each component system then it cannot be assumed that the aggregated affect will be to mitigate risk at the SoS level. A literature review was undertaken examining three themes: (1) SoS Engineering (SoSE), (2) M&S and (3) Risk. Theme 1 of the literature provided insight into the activities comprising SoSE and its difference from traditional SE with risk management identified as a key activity. The second theme discussed the application of M&S to SoS, providing an output, which supported the identification of appropriate techniques and concluding that, the inherent complexity of a SoS required the use of M&S in order to support SoSE activities. Current risk management approaches were reviewed in theme 3 as well as the management of SoS risk. Although some specific examples of the management of SoS risk were found, no mature, general approach was identified, indicating a gap in current knowledge. However, it was noted most of these examples were underpinned by M&S approaches. It was therefore concluded a general approach SoS risk management utilising M&S methods would be of benefit. In order to fill the gap identified in current knowledge, this research proposed a new model based approach to Risk Management where risk identification was supported by a framework, which combined SoS system of interest dimensions with holistic risk types, where the resulting risks and contributing factors are captured in a causal network. Analysis of the causal network using a model technique selection tool, developed as part of this research, allowed the causal network to be simplified through the replacement of groups of elements within the network by appropriate supporting models. The Bayesian Belief Network (BBN) was identified as a suitable method to represent SoS risk. Supporting models run in Monte Carlo Simulations allowed data to be generated from which the risk BBNs could learn, thereby providing a more quantitative approach to SoS risk management. A method was developed which provided context to the BBN risk output through comparison with worst and best-case risk probabilities. The model based approach to Risk Management was applied to two very different case studies: Close Air Support mission planning and the Wheat Supply Chain, UK National Food Security risks, demonstrating its effectiveness and adaptability. The research established that the SoS SoI is essential for effective SoS risk identification and analysis of risk transfer, effective SoS modelling requires a range of techniques where suitability is determined by the problem context, the responsibility for SoS Risk Management is related to the overall SoS classification and the model based approach to SoS risk management was effective for both application case studies

    Clafer: Lightweight Modeling of Structure, Behaviour, and Variability

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    Embedded software is growing fast in size and complexity, leading to intimate mixture of complex architectures and complex control. Consequently, software specification requires modeling both structures and behaviour of systems. Unfortunately, existing languages do not integrate these aspects well, usually prioritizing one of them. It is common to develop a separate language for each of these facets. In this paper, we contribute Clafer: a small language that attempts to tackle this challenge. It combines rich structural modeling with state of the art behavioural formalisms. We are not aware of any other modeling language that seamlessly combines these facets common to system and software modeling. We show how Clafer, in a single unified syntax and semantics, allows capturing feature models (variability), component models, discrete control models (automata) and variability encompassing all these aspects. The language is built on top of first order logic with quantifiers over basic entities (for modeling structures) combined with linear temporal logic (for modeling behaviour). On top of this semantic foundation we build a simple but expressive syntax, enriched with carefully selected syntactic expansions that cover hierarchical modeling, associations, automata, scenarios, and Dwyer's property patterns. We evaluate Clafer using a power window case study, and comparing it against other notations that substantially overlap with its scope (SysML, AADL, Temporal OCL and Live Sequence Charts), discussing benefits and perils of using a single notation for the purpose
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