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Mancini, Toni; Mari, Federico; Massini, Annalisa; Melatti, Igor; Tronci, Enrico |
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Simulator Semantics for System Level Formal Verification |
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2015 |
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Proceedings Sixth International Symposium on Games, Automata, Logics and Formal Verification (GandALF 2015), |
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MCLab @ davi @ |
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125 |
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Alimguzhin, V.; Mari, F.; Melatti, I.; Tronci, E.; Ebeid, E.; Mikkelsen, S.A.; Jacobsen, R.H.; Gruber, J.K.; Hayes, B.; Huerta, F.; Prodanovic, M. |
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A Glimpse of SmartHG Project Test-bed and Communication Infrastructure |
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2015 |
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Digital System Design (DSD), 2015 Euromicro Conference on |
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225-232 |
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Batteries; Control systems; Databases; Production; Sensors; Servers; Smart grids; Grid State Estimation; Peak Shaving; Policy Robustness Verification; Price Policy Synthesis |
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Sapienza @ preissler @ Alimguzhin_etal2015 |
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127 |
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Mancini, T.; Mari, F.; Melatti, I.; Salvo, I.; Tronci, E. |
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Title |
An Efficient Algorithm for Network Vulnerability Analysis Under Malicious Attacks |
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2018 |
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Foundations of Intelligent Systems – 24th International Symposium, ISMIS 2018, Limassol, Cyprus, October 29-31, 2018, Proceedings |
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302-312 |
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MCLab @ davi @ DBLP:conf/ismis/ManciniMMST18 |
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176 |
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Mancini, T.; Mari, F.; Melatti, I.; Salvo, I.; Tronci, E.; Gruber, J.K.; Hayes, B.; Prodanovic, M.; Elmegaard, L. |
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User Flexibility Aware Price Policy Synthesis for Smart Grids |
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2015 |
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Digital System Design (DSD), 2015 Euromicro Conference on |
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478-485 |
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Contracts; Current measurement; Load management; Power demand; Power measurement; State estimation; Substations; Grid State Estimation; Peak Shaving; Policy Robustness Verification; Price Policy Synthesis |
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Sapienza @ preissler @ Mancini_etal2015_3 |
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136 |
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Mancini, T. ; Mari, F.; Massini, A.; Melatti, I.; Salvo, I.; Tronci, E. |
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Title |
On minimising the maximum expected verification time |
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2017 |
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Information Processing Letters |
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Sapienza @ mari @ |
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163 |
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Ehrig, R.; Dierkes, T.; Schaefer, S.; Roeblitz, S.; Tronci, E.; Mancini, T.; Salvo, I.; Alimguzhin, V.; Mari, F.; Melatti, I.; Massini, A.; Leeners, B.; Krueger, T.H.C.; Egli, M.; Ille, F. |
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An integrative approach for model driven computation of treatments in reproductive medicine |
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2015 |
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Proceedings of the 15th International Symposium on Mathematical and Computational Biology (BIOMAT 2015), Rorkee, India |
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Sapienza @ preissler @ Ehrig_etal2015 |
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144 |
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Mancini, T.; Mari, F.; Melatti, I.; Salvo, I.; Tronci, E.; Gruber, J.; Hayes, B.; Prodanovic, M.; Elmegaard, L. |
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Title |
Parallel Statistical Model Checking for Safety Verification in Smart Grids |
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2018 |
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2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) |
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1-6 |
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MCLab @ davi @ mancini-etal:2018:smartgridcomm |
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170 |
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Mancini, T.; Mari, F.; Massini, A.; Melatti, I.; Salvo, I.; Sinisi, S.; Tronci, E.; Ehrig, R.; Röblitz, S.; Leeners, B. |
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Computing Personalised Treatments through In Silico Clinical Trials. A Case Study on Downregulation in Assisted Reproduction |
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2018 |
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25th RCRA International Workshop on “Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion” (RCRA 2018) |
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MCLab @ davi @ |
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175 |
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Mancini, T.; Mari, F.; Massini, A.; Melatti, I.; Tronci, E. |
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Title |
On Checking Equivalence of Simulation Scripts |
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2021 |
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Journal of Logical and Algebraic Methods in Programming |
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100640 |
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Formal verification, Simulation based formal verification, Formal Verification of cyber-physical systems, System-level formal verification |
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To support Model Based Design of Cyber-Physical Systems (CPSs) many simulation based approaches to System Level Formal Verification (SLFV) have been devised. Basically, these are Bounded Model Checking approaches (since simulation horizon is of course bounded) relying on simulators to compute the system dynamics and thereby verify the given system properties. The main obstacle to simulation based SLFV is the large number of simulation scenarios to be considered and thus the huge amount of simulation time needed to complete the verification task. To save on computation time, simulation based SLFV approaches exploit the capability of simulators to save and restore simulation states. Essentially, such a time saving is obtained by optimising the simulation script defining the simulation activity needed to carry out the verification task. Although such approaches aim to (bounded) formal verification, as a matter of fact, the proof of correctness of the methods to optimise simulation scripts basically relies on an intuitive semantics for simulation scripting languages. This hampers the possibility of formally showing that the optimisations introduced to speed up the simulation activity do not actually omit checking of relevant behaviours for the system under verification. The aim of this paper is to fill the above gap by presenting an operational semantics for simulation scripting languages and by proving soundness and completeness properties for it. This, in turn, enables formal proofs of equivalence between unoptimised and optimised simulation scripts. |
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2352-2208 |
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MCLab @ davi @ Mancini2021100640 |
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183 |
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Cavaliere, Federico; Mari, Federico; Melatti, Igor; Minei, Giovanni; Salvo, Ivano; Tronci, Enrico; Verzino, Giovanni; Yushtein, Yuri |
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Model Checking Satellite Operational Procedures |
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2011 |
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DAta Systems In Aerospace (DASIA), Org. EuroSpace, Canadian Space Agency, CNES, ESA, EUMETSAT. San Anton, Malta, EuroSpace. |
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We present a model checking approach for the automatic verification of satellite operational procedures (OPs). Building a model for a complex system as a satellite is a hard task. We overcome this obstruction by using a suitable simulator (SIMSAT) for the satellite. Our approach aims at improving OP quality assurance by automatic exhaustive exploration of all possible simulation scenarios. Moreover, our solution decreases OP verification costs by using a model checker (CMurphi) to automatically drive the simulator. We model OPs as user-executed programs observing the simulator telemetries and sending telecommands to the simulator. In order to assess feasibility of our approach we present experimental results on a simple meaningful scenario. Our results show that we can save up to 90% of verification time. |
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Sapienza @ mari @ Dasia11 |
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