
Federico Mari, Igor Melatti, Enrico Tronci, and Alberto Finzi. "A multihop advertising discovery and delivering protocol for multi administrative domain MANET." Mobile Information Systems 3, no. 9 (2013): 261–280. IOS Press. ISSN: 1574017x (Print) 1875905X (Online). DOI: 10.3233/MIS130162.



Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. "Model Based Synthesis of Control Software from System Level Formal Specifications." ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY 23, no. 1 (2014): Article 6. ACM. ISSN: 1049331X. DOI: 10.1145/2559934.



Giuseppe Della Penna, Benedetto Intrigila, Daniele Magazzeni, Igor Melatti, and Enrico Tronci. "CGMurphi: Automatic synthesis of numerical controllers for nonlinear hybrid systems." European Journal of Control 19, no. 1 (2013): 14–36. Elsevier NorthHolland, Inc.. ISSN: 09473580. DOI: 10.1016/j.ejcon.2013.02.001.



Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. "Linear Constraints and Guarded Predicates as a Modeling Language for Discrete Time Hybrid Systems." International Journal on Advances in Software vol. 6, nr 1&2 (2013): 155–169. IARIA. ISSN: 19422628.
Abstract: Model based design is particularly appealing in
software based control systems (e.g., embedded
software) design, since in such a case system
level specifications are much easier to define
than the control software behavior itself. In
turn, model based design of embedded systems
requires modeling both continuous subsystems
(typically, the plant) as well as discrete
subsystems (the controller). This is typically
done using hybrid systems. Mixed Integer Linear
Programming (MILP) based abstraction techniques
have been successfully applied to automatically
synthesize correctbyconstruction control
software for discrete time linear hybrid systems,
where plant dynamics is modeled as a linear
predicate over state, input, and next state
variables. Unfortunately, MILP solvers require
such linear predicates to be conjunctions of
linear constraints, which is not a natural way of
modeling hybrid systems. In this paper we show
that, under the hypothesis that each variable
ranges over a bounded interval, any linear
predicate built upon conjunction and disjunction
of linear constraints can be automatically
translated into an equivalent conjunctive
predicate. Since variable bounds play a key role
in this translation, our algorithm includes a
procedure to compute all implicit variable bounds
of the given linear predicate. Furthermore, we
show that a particular form of linear predicates,
namely guarded predicates, are a natural and
powerful language to succinctly model discrete
time linear hybrid systems dynamics. Finally, we
experimentally show the feasibility of our
approach on an important and challenging case
study taken from the literature, namely the
multiinput Buck DCDC Converter. As an example,
the guarded predicate that models (with 57
constraints) a 6inputs Buck DCDC Converter is
translated in a conjunctive predicate (with 102
linear constraints) in about 40 minutes.
Keywords: Modelbased software design; Linear predicates; Hybrid systems



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: 10.1007/9783319164809_52.



T. Mancini, F. Mari, A. Massini, I. Melatti, and E. Tronci. "Anytime system level verification via parallel random exhaustive hardware in the loop simulation." Microprocessors and Microsystems 41 (2016): 12–28. ISSN: 01419331. DOI: 10.1016/j.micpro.2015.10.010.
Abstract: Abstract System level verification of cyberphysical systems has the goal of verifying that the whole (i.e., software + hardware) system meets the given specifications. Model checkers for hybrid systems cannot handle system level verification of actual systems. Thus, Hardware In the Loop Simulation (HILS) is currently the main workhorse for system level verification. By using model checking driven exhaustive HILS, System Level Formal Verification (SLFV) can be effectively carried out for actual systems. We present a parallel random exhaustive HILS based model checker for hybrid systems that, by simulating all operational scenarios exactly once in a uniform random order, is able to provide, at any time during the verification process, an upper bound to the probability that the System Under Verification exhibits an error in a yettobesimulated scenario (Omission Probability). We show effectiveness of the proposed approach by presenting experimental results on SLFV of the Inverted Pendulum on a Cart and the Fuel Control System examples in the Simulink distribution. To the best of our knowledge, no previously published model checker can exhaustively verify hybrid systems of such a size and provide at any time an upper bound to the Omission Probability.
Keywords: Model Checking of Hybrid Systems; Model checking driven simulation; Hardware in the loop simulation



T. Mancini. "Now or Never: negotiating efficiently with unknown counterparts." In proceedings of the 22nd RCRA International Workshop. Ferrara, Italy. CEUR, 2015 (Colocated with the 14th Conference of the Italian Association for Artificial Intelligence (AI*IA 2015)). (2015).



B. Leeners, T. H. C. Kruger, K. Geraedts, E. Tronci, T. Mancini, F. Ille, M. Egli, S. RÃ¶blitz, L. Saleh, K. Spanaus et al. "Lack of Associations between Female Hormone Levels and Visuospatial Working Memory, Divided Attention and Cognitive Bias across Two Consecutive Menstrual Cycles." Frontiers in Behavioral Neuroscience 11 (2017): 120. ISSN: 16625153. DOI: 10.3389/fnbeh.2017.00120.
Abstract: Background: Interpretation of observational studies on associations between prefrontal cognitive functioning and hormone levels across the female menstrual cycle is complicated due to small sample sizes and poor replicability. Methods: This observational multisite study comprised data of n=88 menstruating women from Hannover, Germany, and Zurich, Switzerland, assessed during a first cycle and n=68 reassessed during a second cycle to rule out practice effects and falsepositive chance findings. We assessed visuospatial working memory, attention, cognitive bias and hormone levels at four consecutive timepoints across both cycles. In addition to interindividual differences we examined intraindividual change over time (i.e., withinsubject effects). Results: Oestrogen, progesterone and testosterone did not relate to interindividual differences in cognitive functioning. There was a significant negative association between intraindividual change in progesterone and change in working memory from preovulatory to midluteal phase during the first cycle, but that association did not replicate in the second cycle. Intraindividual change in testosterone related negatively to change in cognitive bias from menstrual to preovulatory as well as from preovulatory to midluteal phase in the first cycle, but these associations did not replicate in the second cycle. Conclusions: There is no consistent association between women's hormone levels, in particular oestrogen and progesterone, and attention, working memory and cognitive bias. That is, anecdotal findings observed during the first cycle did not replicate in the second cycle, suggesting that these are falsepositives attributable to random variation and systematic biases such as practice effects. Due to methodological limitations, positive findings in the published literature must be interpreted with reservation.



T. Mancini, F. Mari, A. Massini, I. Melatti, I. Salvo, and E. Tronci. "On minimising the maximum expected verification time." Information Processing Letters (2017). DOI: 10.1016/j.ipl.2017.02.001.



M. P. Hengartner, T. H. C. Kruger, K. Geraedts, E. Tronci, T. Mancini, F. Ille, M. Egli, S. RÃ¶blitz, R. Ehrig, L. Saleh et al. "Negative affect is unrelated to fluctuations in hormone levels across the menstrual cycle: Evidence from a multisite observational study across two successive cycles." Journal of Psychosomatic Research 99 (2017): 21–27. DOI: 10.1016/j.jpsychores.2017.05.018.

