47,475 research outputs found

    Sound Code Generation from Communicating Hybrid Models

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    Precise translation from hybrid models to code is difficult because models are defined in the continuous-time domain whereas code executes on digital computers in a discrete fashion. Traditional approach is to associate the model with a sampling rate before code generation, and rely on an approximate algorithm that computes the next state numerically. Depending on the choice of the sampling rate and the algorithm, the behavior of the code may vary significantly due to numerical errors, but the discrepancy has been addressed informally, making the analysis results at the model level less meaningful for implementation. Formal relationship between the model and the code becomes even more unclear when components of the code execute concurrently. In this paper, we propose a formal framework that addresses the issue of soundness of concurrent programs generated from communicating hybrid models. The motivation is that concurrent programs executing in different rates may cause an erroneous transition when transition conditions are evaluated using values from different time instances. The essence of our technique is to refine the model by tightening transition conditions according to the maximum errors due to different sampling rates. We claim that the generated code has a trace of discrete transitions that is equivalent to one of the traces observable from the model, and that the values of variables are bounded. Our framework demonstrates how hybrid models defined in the continuous time domain are translated into discretized models with or without consideration of errors due to asynchronous sampling, and finally into executable code with real-time scheduling

    Sound Code Generation From Hybrid System Models: Some Theoretical Results

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    Code generation from hybrid system models, a promising approach for producing reliable embedded systems, has been our research focus for some time now. In this report, we summarize the progress made thus far and provide directions for research towards realization of this goal

    Synthesizing SystemC Code from Delay Hybrid CSP

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    Delay is omnipresent in modern control systems, which can prompt oscillations and may cause deterioration of control performance, invalidate both stability and safety properties. This implies that safety or stability certificates obtained on idealized, delay-free models of systems prone to delayed coupling may be erratic, and further the incorrectness of the executable code generated from these models. However, automated methods for system verification and code generation that ought to address models of system dynamics reflecting delays have not been paid enough attention yet in the computer science community. In our previous work, on one hand, we investigated the verification of delay dynamical and hybrid systems; on the other hand, we also addressed how to synthesize SystemC code from a verified hybrid system modelled by Hybrid CSP (HCSP) without delay. In this paper, we give a first attempt to synthesize SystemC code from a verified delay hybrid system modelled by Delay HCSP (dHCSP), which is an extension of HCSP by replacing ordinary differential equations (ODEs) with delay differential equations (DDEs). We implement a tool to support the automatic translation from dHCSP to SystemC

    Multimedia content modeling and personalization

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    Combining SysML and AADL for the design, validation and implementation of critical systems

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    The realization of critical systems goes through multiple phases of specification, design, integration, validation, and testing. It starts from high-level sketches down to the final product. Model-Based Design has been acknowledged as a good conveyor to capture these steps. Yet, there is no universal solution to represent all activities. Two candidates are the OMG-based SysML to perform high-level modeling tasks, and the SAE AADL to perform lower-level ones, down to the implementation. The paper shares an experience on the seamless use of SysML and the AADL to model, validate/verify and implement a flight management system

    Judging Risk

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    Risk assessment plays an increasingly pervasive role in criminal justice in the United States at all stages of the process, from policing, to pre-trial, sentencing, corrections, and during parole. As efforts to reduce incarceration have led to adoption of risk-assessment tools, critics have begun to ask whether various instruments in use are valid and whether they might reinforce rather than reduce bias in criminal justice outcomes. Such work has neglected how decisionmakers use risk-assessment in practice. In this Article, we examine in detail the judging of risk assessment and we study why decisionmakers so often fail to consistently use such quantitative information
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