6,255 research outputs found

    An overview of decision table literature 1982-1995.

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    This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.

    Language support for dynamic, hierarchical data partitioning

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    On Provably Correct Decision-Making for Automated Driving

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    The introduction of driving automation in road vehicles can potentially reduce road traffic crashes and significantly improve road safety. Automation in road vehicles also brings several other benefits such as the possibility to provide independent mobility for people who cannot and/or should not drive. Many different hardware and software components (e.g. sensing, decision-making, actuation, and control) interact to solve the autonomous driving task. Correctness of such automated driving systems is crucial as incorrect behaviour may have catastrophic consequences. Autonomous vehicles operate in complex and dynamic environments, which requires decision-making and planning at different levels. The aim of such decision-making components in these systems is to make safe decisions at all times. The challenge of safety verification of these systems is crucial for the commercial deployment of full autonomy in vehicles. Testing for safety is expensive, impractical, and can never guarantee the absence of errors. In contrast, formal methods, which are techniques that use rigorous mathematical models to build hardware and software systems can provide a mathematical proof of the correctness of the system. The focus of this thesis is to address some of the challenges in the safety verification of decision-making in automated driving systems. A central question here is how to establish formal verification as an efficient tool for automated driving software development.A key finding is the need for an integrated formal approach to prove correctness and to provide a complete safety argument. This thesis provides insights into how three different formal verification approaches, namely supervisory control theory, model checking, and deductive verification differ in their application to automated driving and identifies the challenges associated with each method. It identifies the need for the introduction of more rigour in the requirement refinement process and presents one possible solution by using a formal model-based safety analysis approach. To address challenges in the manual modelling process, a possible solution by automatically learning formal models directly from code is proposed

    On-stack replacement, distilled

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    On-stack replacement (OSR) is essential technology for adaptive optimization, allowing changes to code actively executing in a managed runtime. The engineering aspects of OSR are well-known among VM architects, with several implementations available to date. However, OSR is yet to be explored as a general means to transfer execution between related program versions, which can pave the road to unprecedented applications that stretch beyond VMs. We aim at filling this gap with a constructive and provably correct OSR framework, allowing a class of general-purpose transformation functions to yield a special-purpose replacement. We describe and evaluate an implementation of our technique in LLVM. As a novel application of OSR, we present a feasibility study on debugging of optimized code, showing how our techniques can be used to fix variables holding incorrect values at breakpoints due to optimizations

    Multi-paradigm modelling for cyber–physical systems: a descriptive framework

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    The complexity of cyber–physical systems (CPSS) is commonly addressed through complex workflows, involving models in a plethora of different formalisms, each with their own methods, techniques, and tools. Some workflow patterns, combined with particular types of formalisms and operations on models in these formalisms, are used successfully in engineering practice. To identify and reuse them, we refer to these combinations of workflow and formalism patterns as modelling paradigms. This paper proposes a unifying (Descriptive) Framework to describe these paradigms, as well as their combinations. This work is set in the context of Multi-Paradigm Modelling (MPM), which is based on the principle to model every part and aspect of a system explicitly, at the most appropriate level(s) of abstraction, using the most appropriate modelling formalism(s) and workflows. The purpose of the Descriptive Framework presented in this paper is to serve as a basis to reason about these formalisms, workflows, and their combinations. One crucial part of the framework is the ability to capture the structural essence of a paradigm through the concept of a paradigmatic structure. This is illustrated informally by means of two example paradigms commonly used in CPS: Discrete Event Dynamic Systems and Synchronous Data Flow. The presented framework also identifies the need to establish whether a paradigm candidate follows, or qualifies as, a (given) paradigm. To illustrate the ability of the framework to support combining paradigms, the paper shows examples of both workflow and formalism combinations. The presented framework is intended as a basis for characterisation and classification of paradigms, as a starting point for a rigorous formalisation of the framework (allowing formal analyses), and as a foundation for MPM tool development

    FOAL 2004 Proceedings: Foundations of Aspect-Oriented Languages Workshop at AOSD 2004

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    Aspect-oriented programming is a paradigm in software engineering and FOAL logos courtesy of Luca Cardelli programming languages that promises better support for separation of concerns. The third Foundations of Aspect-Oriented Languages (FOAL) workshop was held at the Third International Conference on Aspect-Oriented Software Development in Lancaster, UK, on March 23, 2004. This workshop was designed to be a forum for research in formal foundations of aspect-oriented programming languages. The call for papers announced the areas of interest for FOAL as including, but not limited to: semantics of aspect-oriented languages, specification and verification for such languages, type systems, static analysis, theory of testing, theory of aspect composition, and theory of aspect translation (compilation) and rewriting. The call for papers welcomed all theoretical and foundational studies of foundations of aspect-oriented languages. The goals of this FOAL workshop were to: � Make progress on the foundations of aspect-oriented programming languages. � Exchange ideas about semantics and formal methods for aspect-oriented programming languages. � Foster interest within the programming language theory and types communities in aspect-oriented programming languages. � Foster interest within the formal methods community in aspect-oriented programming and the problems of reasoning about aspect-oriented programs. The papers at the workshop, which are included in the proceedings, were selected frompapers submitted by researchers worldwide. Due to time limitations at the workshop, not all of the submitted papers were selected for presentation. FOAL also welcomed an invited talk by James Riely (DePaul University), the abstract of which is included below. The workshop was organized by Gary T. Leavens (Iowa State University), Ralf L?ammel (CWI and Vrije Universiteit, Amsterdam), and Curtis Clifton (Iowa State University). The program committee was chaired by L?ammel and included L?ammel, Leavens, Clifton, Lodewijk Bergmans (University of Twente), John Tang Boyland (University of Wisconsin, Milwaukee), William R. Cook (University of Texas at Austin), Tzilla Elrad (Illinois Institute of Technology), Kathleen Fisher (AT&T Labs�Research), Radha Jagadeesan (DePaul University), Shmuel Katz (Technion�Israel Institute of Technology), Shriram Krishnamurthi (Brown University), Mira Mezini (Darmstadt University of Technology), Todd Millstein (University of California, Los Angeles), Benjamin C. Pierce (University of Pennsylvania), Henny Sipma (Stanford University), Mario S?udholt ( ?Ecole des Mines de Nantes), and David Walker (Princeton University). We thank the organizers of AOSD 2004 for hosting the workshop
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