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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." Int. J. Softw. Tools Technol. Transf. 8, no. 4 (2006): 397–409. Springer-Verlag. ISSN: 1433-2779. DOI: 10.1007/s10009-005-0216-7.
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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Giuseppe Della Penna, Daniele Magazzeni, Alberto Tofani, Benedetto Intrigila, Igor Melatti, and Enrico Tronci. "Automatic Synthesis of Robust Numerical Controllers." In Icas '07, 4. IEEE Computer Society, 2007. ISSN: 0-7695-2859-5. DOI: 10.1109/CONIELECOMP.2007.59.
Abstract: A major problem of numerical controllers is their robustness, i.e. the state read from the plant may not be in the controller table, although it may be close to some states in the table. For continuous systems, this problem is typically handled by interpolation techniques. Unfortunately, when the plant contains both continuous and discrete variables, the interpolation approach does not work well. To cope with this kind of systems, we propose a general methodology that exploits explicit model checking in an innovative way to automatically synthesize a (time-) optimal numerical controller from a plant specification and apply an optimized strengthening algorithm only on the most significant states, in order to reach an acceptable robustness degree. We implemented all the algorithms within our CGMurphi tool, an extension of the well-known CMurphi verifier, and tested the effectiveness of our approach by applying it to the well-known truck and trailer obstacles avoidance problem.
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Giuseppe Della Penna, Daniele Magazzeni, Alberto Tofani, Benedetto Intrigila, Igor Melatti, and Enrico Tronci. "Automated Generation Of Optimal Controllers Through Model Checking Techniques." In Informatics in Control Automation and Robotics. Selected Papers from ICINCO 2006, 107–119. Springer, 2008. DOI: 10.1007/978-3-540-79142-3_10.
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Giuseppe Della Penna, Alberto Tofani, Marcello Pecorari, Orazio Raparelli, Benedetto Intrigila, Igor Melatti, and Enrico Tronci. "A Case Study on Automated Generation of Integration Tests." In Fdl, 278–284. Ecsi, 2006. ISSN: 978-3-00-019710-9.
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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. ISBN: 978-1-4503-1425-1. Notes: Techreport version can be found at arxiv.org. DOI: 10.1145/2380356.2380398.
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Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. "From Boolean Relations to Control Software." In Proceedings of ICSEA 2011, The Sixth International Conference on Software Engineering Advances, 528–533. ThinkMind, 2011. ISSN: 978-1-61208-165-6. Notes: Best Paper Award.
Abstract: Many software as well digital hardware automatic synthesis methods define the set of implementations meeting the given system specifications with a boolean relation K. In such a context a fundamental step in the software (hardware) synthesis process is finding effective solutions to the functional equation defined by K. This entails finding a (set of) boolean function(s) F (typically represented using OBDDs, Ordered Binary Decision Diagrams) such that: 1) for all x for which K is satisfiable, K(x, F(x)) = 1 holds; 2) the implementation of F is efficient with respect to given implementation parameters such as code size or execution time. While this problem has been widely studied in digital hardware synthesis, little has been done in a software synthesis context. Unfortunately the approaches developed for hardware synthesis cannot be directly used in a software context. This motivates investigation of effective methods to solve the above problem when F has to be implemented with software. In this paper we present an algorithm that, from an OBDD representation for K, generates a C code implementation for F that has the same size as the OBDD for F and a WCET (Worst Case Execution Time) linear in nr, being n = |x| the number of input arguments for functions in F and r the number of functions in F.
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Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. "Linear Constraints as a Modeling Language for Discrete Time Hybrid Systems." In Proceedings of ICSEA 2012, The Seventh International Conference on Software Engineering Advances, 664–671. ThinkMind, 2012.
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Benedetto Intrigila, Daniele Magazzeni, Igor Melatti, and Enrico Tronci. "A Model Checking Technique for the Verification of Fuzzy Control Systems." In CIMCA '05: Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce Vol-1 (CIMCA-IAWTIC'06), 536–542. Washington, DC, USA: IEEE Computer Society, 2005. ISSN: 0-7695-2504-0-01. DOI: 10.1109/CIMCA.2005.1631319.
Abstract: Fuzzy control is well known as a powerful technique for designing and realizing control systems. However, statistical evidence for their correct behavior may be not enough, even when it is based on a large number of samplings. In order to provide a more systematic verification process, the cell-to-cell mapping technology has been used in a number of cases as a verification tool for fuzzy control systems and, more recently, to assess their optimality and robustness. However, cell-to-cell mapping is typically limited in the number of cells it can explore. To overcome this limitation, in this paper we show how model checking techniques may be instead used to verify the correct behavior of a fuzzy control system. To this end, we use a modified version of theMurphi verifier, which ease the modeling phase by allowing to use finite precision real numbers and external C functions. In this way, also already designed simulators may be used for the verification phase. With respect to the cell mapping technique, our approach appears to be complementary; indeed, it explores a much larger number of states, at the cost of being less informative on the global dynamic of the system.
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Benedetto Intrigila, Igor Melatti, Alberto Tofani, and Guido Macchiarelli. "Computational models of myocardial endomysial collagen arrangement." Computer Methods and Programs in Biomedicine 86, no. 3 (2007): 232–244. Elsevier North-Holland, Inc.. ISSN: 0169-2607. DOI: 10.1016/j.cmpb.2007.03.004.
Abstract: Collagen extracellular matrix is one of the factors related to high passive stiffness of cardiac muscle. However, the architecture and the mechanical aspects of the cardiac collagen matrix are not completely known. In particular, endomysial collagen contribution to the passive mechanics of cardiac muscle as well as its micro anatomical arrangement is still a matter of debate. In order to investigate mechanical and structural properties of endomysial collagen, we consider two alternative computational models of some specific aspects of the cardiac muscle. These two models represent two different views of endomysial collagen distribution: (1) the traditional view and (2) a new view suggested by the data obtained from scanning electron microscopy (SEM) in NaOH macerated samples (a method for isolating collagen from the other tissue). We model the myocardial tissue as a net of spring elements representing the cardiomyocytes together with the endomysial collagen distribution. Each element is a viscous elastic spring, characterized by an elastic and a viscous constant. We connect these springs to imitate the interconnections between collagen fibers. Then we apply to the net of springs some external forces of suitable magnitude and direction, obtaining an extension of the net itself. In our setting, the ratio forces magnitude /net extension is intended to model the stress /strain ratio of a microscopical portion of the myocardial tissue. To solve the problem of the correct identification of the values of the different parameters involved, we use an artificial neural network approach. In particular, we use this technique to learn, given a distribution of external forces, the elastic constants of the springs needed to obtain a desired extension as an equilibrium position. Our experimental findings show that, in the model of collagen distribution structured according to the new view, a given stress /strain ratio (of the net of springs, in the sense specified above) is obtained with much smaller (w.r.t. the other model, corresponding to the traditional view) elasticity constants of the springs. This seems to indicate that by an appropriate structure, a given stiffness of the myocardial tissue can be obtained with endomysial collagen fibers of much smaller size.
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Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. "Control Software Visualization." In Proceedings of INFOCOMP 2012, The Second International Conference on Advanced Communications and Computation, 15–20. ThinkMind, 2012. ISSN: 978-1-61208-226-4.
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