Rosario Pugliese, and Enrico Tronci. "Automatic Verification of a Hydroelectric Power Plant." In Third International Symposium of Formal Methods Europe (FME), Co-Sponsored by IFIP WG 14.3, edited by M. - C. Gaudel and J. Woodcock, 425–444. Lecture Notes in Computer Science 1051. Oxford, UK: Springer, 1996. ISSN: 3-540-60973-3. DOI: 10.1007/3-540-60973-3_100.
Abstract: We analyze the specification of a hydroelectric power plant by ENEL (the Italian Electric Company). Our goal is to show that for the specification of the plant (its control system in particular) some given properties hold. We were provided with an informal specification of the plant. From such informal specification we wrote a formal specification using the CCS/Meije process algebra formalism. We defined properties using μ-calculus. Automatic verification was carried out using model checking. This was done by translating our process algebra definitions (the model) and μ-calculus formulas into BDDs. In this paper we present the informal specification of the plant, its formal specification, some of the properties we verified and experimental results.
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T. Mancini, F. Mari, I. Melatti, I. Salvo, and E. Tronci. "An Efficient Algorithm for Network Vulnerability Analysis Under Malicious Attacks." In Foundations of Intelligent Systems – 24th International Symposium, ISMIS 2018, Limassol, Cyprus, October 29-31, 2018, Proceedings, 302–312., 2018. Notes: Best Paper. DOI: 10.1007/978-3-030-01851-1_29.
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Toni Mancini, Enrico Tronci, Ivano Salvo, Federico Mari, Annalisa Massini, and Igor Melatti. "Computing Biological Model Parameters by Parallel Statistical Model Checking." International Work Conference on Bioinformatics and Biomedical Engineering (IWBBIO 2015) 9044 (2015): 542–554. DOI: 10.1007/978-3-319-16480-9_52.
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Marco Martinelli, Enrico Tronci, Giovanni Dipoppa, and Claudio Balducelli. "Electric Power System Anomaly Detection Using Neural Networks." In 8th International Conference on: Knowledge-Based Intelligent Information and Engineering Systems (KES), edited by M. G. Negoita, R. J. Howlett and L. C. Jain, 1242–1248. Lecture Notes in Computer Science 3213. Wellington, New Zealand: Springer, 2004. ISSN: 3-540-23318-0. DOI: 10.1007/978-3-540-30132-5_168.
Abstract: The aim of this work is to propose an approach to monitor and protect Electric Power System by learning normal system behaviour at substations level, and raising an alarm signal when an abnormal status is detected; the problem is addressed by the use of autoassociative neural networks, reading substation measures. Experimental results show that, through the proposed approach, neural networks can be used to learn parameters underlaying system behaviour, and their output processed to detecting anomalies due to hijacking of measures, changes in the power network topology (i.e. transmission lines breaking) and unexpected power demand trend.
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Giuseppe Della Penna, Benedetto Intrigila, Igor Melatti, Enrico Tronci, and Marisa Venturini Zilli. "Bounded Probabilistic Model Checking with the Mur$\varphi$ Verifier." In Formal Methods in Computer-Aided Design, 5th International Conference, FMCAD 2004, Austin, Texas, USA, November 15-17, 2004, Proceedings, edited by A. J. Hu and A. K. Martin, 214–229. Lecture Notes in Computer Science 3312. Springer, 2004. ISSN: 3-540-23738-0. DOI: 10.1007/978-3-540-30494-4_16.
Abstract: In this paper we present an explicit verification algorithm for Probabilistic Systems defining discrete time/finite state Markov Chains. We restrict ourselves to verification of Bounded PCTL formulas (BPCTL), that is, PCTL formulas in which all Until operators are bounded, possibly with different bounds. This means that we consider only paths (system runs) of bounded length. Given a Markov Chain $\cal M$ and a BPCTL formula Φ, our algorithm checks if Φ is satisfied in $\cal M$. This allows to verify important properties, such as reliability in Discrete Time Hybrid Systems. We present an implementation of our algorithm within a suitable extension of the Mur$\varphi$ verifier. We call FHP-Mur$\varphi$ (Finite Horizon Probabilistic Mur$\varphi$) such extension of the Mur$\varphi$ verifier. We give experimental results comparing FHP-Mur$\varphi$ with (a finite horizon subset of) PRISM, a state-of-the-art symbolic model checker for Markov Chains. Our experimental results show that FHP-Mur$\varphi$ can effectively handle verification of BPCTL formulas for systems that are out of reach for PRISM, namely those involving arithmetic operations on the state variables (e.g. hybrid systems).
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Giuseppe Della Penna, Benedetto Intrigila, Igor Melatti, Enrico Tronci, and Marisa Venturini Zilli. "Integrating RAM and Disk Based Verification within the Mur$\varphi$ Verifier." In Correct Hardware Design and Verification Methods, 12th IFIP WG 10.5 Advanced Research Working Conference, CHARME 2003, L'Aquila, Italy, October 21-24, 2003, Proceedings, edited by D. Geist and E. Tronci, 277–282. Lecture Notes in Computer Science 2860. Springer, 2003. ISSN: 3-540-20363-X. DOI: 10.1007/978-3-540-39724-3_25.
Abstract: We present a verification algorithm that can automatically switch from RAM based verification to disk based verification without discarding the work done during the RAM based verification phase. This avoids having to choose beforehand the proper verification algorithm. Our experimental results show that typically our integrated algorithm is as fast as (sometime faster than) the fastest of the two base (i.e. RAM based and disk based) verification algorithms.
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Giuseppe Della Penna, Benedetto Intrigila, Igor Melatti, Enrico Tronci, and Marisa Venturini Zilli. "Finite Horizon Analysis of Markov Chains with the Mur$\varphi$ Verifier." In Correct Hardware Design and Verification Methods, 12th IFIP WG 10.5 Advanced Research Working Conference, CHARME 2003, L'Aquila, Italy, October 21-24, 2003, Proceedings, edited by D. Geist and E. Tronci, 394–409. Lecture Notes in Computer Science 2860. Springer, 2003. ISSN: 3-540-20363-X. DOI: 10.1007/978-3-540-39724-3_34.
Abstract: In this paper we present an explicit disk based verification algorithm for Probabilistic Systems defining discrete time/finite state Markov Chains. Given a Markov Chain and an integer k (horizon), our algorithm checks whether the probability of reaching an error state in at most k steps is below a given threshold. We present an implementation of our algorithm within a suitable extension of the Mur$\varphi$ verifier. We call the resulting probabilistic model checker FHP-Mur$\varphi$ (Finite Horizon Probabilistic Mur$\varphi$). We present experimental results comparing FHP-Mur$\varphi$ with (a finite horizon subset of) PRISM, a state-of-the-art symbolic model checker for Markov Chains. Our experimental results show that FHP-Mur$\varphi$ can handle systems that are out of reach for PRISM, namely those involving arithmetic operations on the state variables (e.g. hybrid systems).
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Ester Ciancamerla, Michele Minichino, Stefano Serro, and Enrico Tronci. "Automatic Timeliness Verification of a Public Mobile Network." In 22nd International Conference on Computer Safety, Reliability, and Security (SAFECOMP), edited by S. Anderson, M. Felici and B. Littlewood, 35–48. Lecture Notes in Computer Science 2788. Edinburgh, UK: Springer, 2003. ISSN: 978-3-540-20126-7. DOI: 10.1007/978-3-540-39878-3_4.
Abstract: This paper deals with the automatic verification of the timeliness of Public Mobile Network (PMN), consisting of Mobile Nodes (MNs) and Base Stations (BSs). We use the Mur$\varphi$ Model Checker to verify that the waiting access time of each MN, under different PMN configurations and loads, and different inter arrival times of MNs in a BS cell, is always below a preassigned threshold. Our experimental results show that Model Checking can be successfully used to generate worst case scenarios and nicely complements probabilistic methods and simulation which are typically used for performance evaluation.
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Giuseppe Della Penna, Benedetto Intrigila, Igor Melatti, Enrico Tronci, and Marisa Venturini Zilli. "Finite Horizon Analysis of Stochastic Systems with the Mur$\varphi$ Verifier." In Theoretical Computer Science, 8th Italian Conference, ICTCS 2003, Bertinoro, Italy, October 13-15, 2003, Proceedings, edited by C. Blundo and C. Laneve, 58–71. Lecture Notes in Computer Science 2841. Springer, 2003. ISSN: 3-540-20216-1. DOI: 10.1007/978-3-540-45208-9_6.
Abstract: Many reactive systems are actually Stochastic Processes. Automatic analysis of such systems is usually very difficult thus typically one simplifies the analysis task by using simulation or by working on a simplified model (e.g. a Markov Chain). We present a Finite Horizon Probabilistic Model Checking approach which essentially can handle the same class of stochastic processes of a typical simulator. This yields easy modeling of the system to be analyzed together with formal verification capabilities. Our approach is based on a suitable disk based extension of the Mur$\varphi$ verifier. Moreover we present experimental results showing effectiveness of our approach.
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Federico Mari, and Enrico Tronci. "CEGAR Based Bounded Model Checking of Discrete Time Hybrid Systems." In Hybrid Systems: Computation and Control (HSCC 2007), edited by A. Bemporad, A. Bicchi and G. C. Buttazzo, 399–412. Lecture Notes in Computer Science 4416. Springer, 2007. DOI: 10.1007/978-3-540-71493-4_32.
Abstract: Many hybrid systems can be conveniently modeled as Piecewise Affine Discrete Time Hybrid Systems PA-DTHS. As well known Bounded Model Checking (BMC) for such systems comes down to solve a Mixed Integer Linear Programming (MILP) feasibility problem. We present a SAT based BMC algorithm for automatic verification of PA-DTHSs. Using Counterexample Guided Abstraction Refinement (CEGAR) our algorithm gradually transforms a PA-DTHS verification problem into larger and larger SAT problems. Our experimental results show that our approach can handle PA-DTHSs that are more then 50 times larger than those that can be handled using a MILP solver.
Keywords: Model Checking, Abstraction, CEGAR, SAT, Hybrid Systems, DTHS
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