58,489 research outputs found

    Recording, Documentation, and Information Management for the Conservation of Heritage Places: Guiding Principles

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    Provides guidance on integrating recording, documentation, and information management of territories, sites, groups of buildings, or monuments into the conservation process; evaluating proposals; consulting specialists; and controlling implementation

    Formal Verification of Security Protocol Implementations: A Survey

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    Automated formal verification of security protocols has been mostly focused on analyzing high-level abstract models which, however, are significantly different from real protocol implementations written in programming languages. Recently, some researchers have started investigating techniques that bring automated formal proofs closer to real implementations. This paper surveys these attempts, focusing on approaches that target the application code that implements protocol logic, rather than the libraries that implement cryptography. According to these approaches, libraries are assumed to correctly implement some models. The aim is to derive formal proofs that, under this assumption, give assurance about the application code that implements the protocol logic. The two main approaches of model extraction and code generation are presented, along with the main techniques adopted for each approac

    Creating Social and Health Equity: Adopting an Alberta Social Determinants of Health Framework

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    This discussion paper highlights the well-documented social factors that influence our health. In a time when the Alberta government is looking for the best innovative ideas around health care, we suggest that a social determinants approach would lead to ground breaking health care reform

    Quantitative Verification: Formal Guarantees for Timeliness, Reliability and Performance

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    Computerised systems appear in almost all aspects of our daily lives, often in safety-critical scenarios such as embedded control systems in cars and aircraft or medical devices such as pacemakers and sensors. We are thus increasingly reliant on these systems working correctly, despite often operating in unpredictable or unreliable environments. Designers of such devices need ways to guarantee that they will operate in a reliable and efficient manner. Quantitative verification is a technique for analysing quantitative aspects of a system's design, such as timeliness, reliability or performance. It applies formal methods, based on a rigorous analysis of a mathematical model of the system, to automatically prove certain precisely specified properties, e.g. ``the airbag will always deploy within 20 milliseconds after a crash'' or ``the probability of both sensors failing simultaneously is less than 0.001''. The ability to formally guarantee quantitative properties of this kind is beneficial across a wide range of application domains. For example, in safety-critical systems, it may be essential to establish credible bounds on the probability with which certain failures or combinations of failures can occur. In embedded control systems, it is often important to comply with strict constraints on timing or resources. More generally, being able to derive guarantees on precisely specified levels of performance or efficiency is a valuable tool in the design of, for example, wireless networking protocols, robotic systems or power management algorithms, to name but a few. This report gives a short introduction to quantitative verification, focusing in particular on a widely used technique called model checking, and its generalisation to the analysis of quantitative aspects of a system such as timing, probabilistic behaviour or resource usage. The intended audience is industrial designers and developers of systems such as those highlighted above who could benefit from the application of quantitative verification,but lack expertise in formal verification or modelling

    A Generic Framework for the Engineering of Self-Adaptive and Self-Organising Systems

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    This paper provides a unifying view for the engineering of self-adaptive (SA) and self-organising (SO) systems. We first identify requirements for designing and building trustworthy self-adaptive and self-organising systems. Second, we propose a generic framework combining design-time and run-time features, which permit the definition and analysis at design-time of mechanisms that both ensure and constrain the run-time behaviour of an SA or SO system, thereby providing some assurance of its self-* capabilities. We show how this framework applies to both an SA and an SO system, and discuss several current proof-of-concept studies on the enabling technologies
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