10 research outputs found

    How to Handle Assumptions in Synthesis

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    The increased interest in reactive synthesis over the last decade has led to many improved solutions but also to many new questions. In this paper, we discuss the question of how to deal with assumptions on environment behavior. We present four goals that we think should be met and review several different possibilities that have been proposed. We argue that each of them falls short in at least one aspect.Comment: In Proceedings SYNT 2014, arXiv:1407.493

    MORPH: A Reference Architecture for Configuration and Behaviour Self-Adaptation

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    An architectural approach to self-adaptive systems involves runtime change of system configuration (i.e., the system's components, their bindings and operational parameters) and behaviour update (i.e., component orchestration). Thus, dynamic reconfiguration and discrete event control theory are at the heart of architectural adaptation. Although controlling configuration and behaviour at runtime has been discussed and applied to architectural adaptation, architectures for self-adaptive systems often compound these two aspects reducing the potential for adaptability. In this paper we propose a reference architecture that allows for coordinated yet transparent and independent adaptation of system configuration and behaviour

    Symbolic construction of GR(1) contracts for systems with full information

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    This work proposes a symbolic algorithm for the construction of assume-guarantee specifications that allow multiple agents to cooperate. Each agent is assigned goals expressed in a fragment of linear temporal logic known as generalized Streett with one pair, GR(1). These goals may be unrealizable, unless each agent makes additional assumptions, about the behavior of other agents. The algorithm constructs a contract among the agents, in that only the infinite behavior of the given goals is constrained, known as liveness, not the finite one, known as safety. This defers synthesis to a later stage of refinement, modularizing the design process. We prove that there exist GR(1) games that do not admit any refining GR(1) contract. For this reason, we formulate contracts with nested GR(1) properties and auxiliary communication variables, and prove that they always exist. The algorithm’s fixpoint structure is similar to GR(1) synthesis, enjoying time complexity polynomial in the number of states, and linear in number of recurrence goals

    Heuristics for the refinement of assumptions in generalized reactivity formulae

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    Reactive synthesis is concerned with automatically generating implementations from formal specifications. These specifications are typically written in the language of generalized reactivity (GR(1)), a subset of linear temporal logic capable of expressing the most common industrial specification patterns, and describe the requirements about the behavior of a system under assumptions about the environment where the system is to be deployed. Oftentimes no implementation exists which guarantees the required behavior under all possible environments, typically due to missing assumptions (this is usually referred to as unrealizability). To address this issue, new assumptions need to be added to complete the specification, a problem known as assumptions refinement. Since the space of candidate assumptions is intractably large, searching for the best solutions is inherently hard. In particular, new methods are needed to (i) increase the effectiveness of the search procedures, measured as the ratio between the number of solutions found and of refinements explored; and (ii) improve the results' quality, defined as the weakness of the solutions. In this thesis we propose a set of heuristics to meet these goals, and a methodology to assess and compare assumptions refinement methods based on quantitative metrics. The heuristics are in the form of algorithms to generate candidate refinements during the search, and quantitative measures to assess the quality of the candidates. We first discuss a heuristic method to generate assumptions that target the cause of unrealizability. This is done by selecting candidate refinement formulas based on Craig's interpolation. We provide a formal underpinning of the technique and evaluate it in terms of our new metric of effectiveness, as defined above, whose value is improved with respect to the state of the art. We demonstrate this on a set of popular benchmarks of embedded software. We then provide a formal, quantitative characterization of the permissiveness of environment assumptions in the form of a weakness measure. We prove that the partial order induced by this measure is consistent with the one induced by implication. The key advantage of this measure is that it allows for prioritizing candidate solutions, as we show experimentally. Lastly, we propose a notion of minimal refinements with respect to the observed counterstrategies. We demonstrate that exploring minimal refinements produces weaker solutions, and reduces the amount of computations needed to explore each refinement. However, this may come at the cost of reducing the effectiveness of the search. To counteract this effect, we propose a hybrid search approach in which both minimal and non-minimal refinements are explored.Open Acces

    Synthesizing nonanomalous event-based controllers for liveness goals

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    We present SGR(1), a novel synthesis technique and methodological guidelines for automatically constructing event-based behaviour models. Our approach works for an expressive subset of liveness properties, distinguishes between controlled and monitored actions, and differentiates system goals from environment assumptions. We show that assumptions must be modelled carefully in order to avoid synthesising anomalous behaviour models. We characterise non-anomalous models and propose assumption compatibility, a sufficient condition, as a methodological guideline.Fil: D'ippolito, Nicolás Roque. Imperial College London; Reino Unido. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Braberman, Victor Adrian. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Piterman, Nir. University of Leicester; Reino UnidoFil: Uchitel, Sebastian. Imperial College London; Reino Unido. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin
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