390 research outputs found

    Arguing security: validating security requirements using structured argumentation

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    This paper proposes using both formal and structured informal arguments to show that an eventual realized system can satisfy its security requirements. These arguments, called 'satisfaction arguments', consist of two parts: a formal argument based upon claims about domain properties, and a set of informal arguments that justify the claims. Building on our earlier work on trust assumptions and security requirements, we show how using satisfaction arguments assists in clarifying how a system satisfies its security requirements, in the process identifying those properties of domains that are critical to the requirements

    The design process in MIKE

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    An integrated framework for representing design history

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    Design is a difficult and complex process requiring; creativity, experience, domain knowledge, and problem solving skills. Much of the information that is used and generated during the design process is rarely explicitly recorded. This includes the reasons why design decisions were made. This information is commonly referred to as design rationale (DR). As a result many of the tasks that are performed during the design process are still poorly understood and modifications to designs can have unforeseen and possibly dangerous consequences. [Continues.

    The treatment of non-functional requirements in MIKE

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    ... this paper it is shown how non-functional requirements are modelled in MIKE, an approach to the development of knowledge-based systems. A semi-formal hypermedia-based model is used to describe the results of the elicitation and interpretation of non-functional requirements and their relationships. Non-functional requirements are the driving force behind the decisions taken in the design phase of MIKE. The impact of non-functional requirements on design decisions and interdependencies between design decisions are explicitly recorded in an additional model in MIKE, thus resulting in a rich documentation of the rationale of design decisions and also providing an important contribution to the traceability of these requirement

    The treatment of non-functional requirements in MIKE

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    The treatment of non-functional requirements in MIKE

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    End-to-End Rationale Reconstruction

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    The logic behind design decisions, called design rationale, is very valuable. In the past, researchers have tried to automatically extract and exploit this information, but prior techniques are only applicable to specific contexts and there is insufficient progress on an end-to-end rationale information extraction pipeline. Here we outline a path towards such a pipeline that leverages several Machine Learning (ML) and Natural Language Processing (NLP) techniques. Our proposed context-independent approach, called Kantara, produces a knowledge graph representation of decisions and of their rationales, which considers their historical evolution and traceability. We also propose validation mechanisms to ensure the correctness of the extracted information and the coherence of the development process. We conducted a preliminary evaluation of our proposed approach on a small example sourced from the Linux Kernel, which shows promising results
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