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Corrado Böhm, and Enrico Tronci. "X-Separability and Left-Invertibility in lambda-calculus." In Symposium on Logic in Computer Science (LICS), 320–328. Ithaca, New York, USA: IEEE Computer Society, 1987.
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Corrado Böhm, and Enrico Tronci. "X-separability and left-invertibility in the λ-calculus (extended abstract, invited paper)." In Proceedings of: Temi e prospettive della Logica e della Filosofia della Scienza contemporanea. Cesena - Italy, 1987.
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Corrado Böhm, Adolfo Piperno, and Enrico Tronci. "Solving Equations in λ-calculus." In Proc. of: Logic Colloquium 88. Padova - Italy, 1989.
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Andrea Bobbio, Ester Ciancamerla, Michele Minichino, and Enrico Tronci. "Functional analysis of a telecontrol system and stochastic measures of its GSM/GPRS connections." Archives of Transport – International Journal of Transport Problems 17, no. 3-4 (2005).
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Andrea Bobbio, Ester Ciancamerla, Saverio Di Blasi, Alessandro Iacomini, Federico Mari, Igor Melatti, Michele Minichino, Alessandro Scarlatti, Enrico Tronci, Roberta Terruggia et al. "Risk analysis via heterogeneous models of SCADA interconnecting Power Grids and Telco networks." In Proceedings of Fourth International Conference on Risks and Security of Internet and Systems (CRiSIS), 90–97., 2009. DOI: 10.1109/CRISIS.2009.5411974.
Abstract: The automation of power grids by means of supervisory control and data acquisition (SCADA) systems has led to an improvement of power grid operations and functionalities but also to pervasive cyber interdependencies between power grids and telecommunication networks. Many power grid services are increasingly depending upon the adequate functionality of SCADA system which in turn strictly depends on the adequate functionality of its communication infrastructure. We propose to tackle the SCADA risk analysis by means of different and heterogeneous modeling techniques and software tools. We demonstrate the applicability of our approach through a case study on an actual SCADA system for an electrical power distribution grid. The modeling techniques we discuss aim at providing a probabilistic dependability analysis, followed by a worst case analysis in presence of malicious attacks and a real-time performance evaluation.
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Andrea Bobbio, Sandro Bologna, Michele Minichino, Ester Ciancamerla, Piero Incalcaterra, Corrado Kropp, and Enrico Tronci. "Advanced techniques for safety analysis applied to the gas turbine control system of Icaro co generative plant." In X Convegno Tecnologie e Sistemi Energetici Complessi, 339–350. Genova, Italy, 2001.
Abstract: The paper describes two complementary and integrable approaches, a probabilistic one and a deterministic one, based on classic and advanced modelling techniques for safety analysis of complex computer based systems. The probabilistic approach is based on classical and innovative probabilistic analysis methods. The deterministic approach is based on formal verification methods. Such approaches are applied to the gas turbine control system of ICARO co generative plant, in operation at ENEA CR Casaccia. The main difference between the two approaches, behind the underlining different theories, is that the probabilistic one addresses the control system by itself, as the set of sensors, processing units and actuators, while the deterministic one also includes the behaviour of the equipment under control which interacts with the control system. The final aim of the research, documented in this paper, is to explore an innovative method which put the probabilistic and deterministic approaches in a strong relation to overcome the drawbacks of their isolated, selective and fragmented use which can lead to inconsistencies in the evaluation results.
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Novella Bartolini, and Enrico Tronci. "On Optimizing Service Availability of an Internet Based Architecture for Infrastructure Protection." In Cnip., 2006.
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Vadim Alimguzhin, Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. "Automatic Control Software Synthesis for Quantized Discrete Time Hybrid Systems." In Proceedings of the 51th IEEE Conference on Decision and Control, CDC 2012, December 10-13, 2012, Maui, HI, USA, 6120–6125. IEEE, 2012. Notes: Techreport version can be found at http://arxiv.org/abs/1207.4098. DOI: 10.1109/CDC.2012.6426260.
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Vadim Alimguzhin, Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. "On Model Based Synthesis of Embedded Control Software." In Proceedings of the 12th International Conference on Embedded Software, EMSOFT 2012, part of the Eighth Embedded Systems Week, ESWeek 2012, Tampere, Finland, October 7-12, 2012, edited by Ahmed Jerraya and Luca P. Carloni and Florence Maraninchi and John Regehr, 227–236. ACM, 2012. Notes: Techreport version can be found at arxiv.org. DOI: 10.1145/2380356.2380398.
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Vadim Alimguzhin, Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. A Map-Reduce Parallel Approach to Automatic Synthesis of Control Software. Vol. abs/1210.2276. CoRR, Technical Report, 2012.
Abstract: Many Control Systems are indeed Software Based Control Systems, i.e. control systems whose controller consists of control software running on a microcontroller device. This motivates investigation on Formal Model Based Design approaches for automatic synthesis of control software.
Available algorithms and tools (e.g., QKS) may require weeks or even months of computation to synthesize control software for large-size systems. This motivates search for parallel algorithms for control software synthesis.
In this paper, we present a map-reduce style parallel algorithm for control software synthesis when the controlled system (plant) is modeled as discrete time linear hybrid system. Furthermore we present an MPI-based implementation PQKS of our algorithm. To the best of our knowledge, this is the first parallel approach for control software synthesis.
We experimentally show effectiveness of PQKS on two classical control synthesis problems: the inverted pendulum and the multi-input buck DC/DC converter. Experiments show that PQKS efficiency is above 65%. As an example, PQKS requires about 16 hours to complete the synthesis of control software for the pendulum on a cluster with 60 processors, instead of the 25 days needed by the sequential algorithm in QKS.
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