
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.



Vadim Alimguzhin, Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. "OntheFly Control Software Synthesis." In Proceedings of International SPIN Symposium on Model Checking of Software (SPIN 2013), 61–80. Lecture Notes in Computer Science 7976. Springer  Verlag, 2013. ISSN: 03029743. ISBN: 9783642391750. DOI: 10.1007/9783642391767_5.



Vadim Alimguzhin, Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. "A MapReduce Parallel Approach to Automatic Synthesis of Control Software." In Proc. of International SPIN Symposium on Model Checking of Software (SPIN 2013), 43–60. Lecture Notes in Computer Science 7976. Springer  Verlag, 2013. ISSN: 03029743. ISBN: 9783642391750. DOI: 10.1007/9783642391767_4.



Verzino Giovanni, Federico Cavaliere, Federico Mari, Igor Melatti, Giovanni Minei, Ivano Salvo, Yuri Yushtein, and Enrico Tronci. "Model checking driven simulation of sat procedures." In Proceedings of 12th International Conference on Space Operations (SpaceOps 2012)., 2012. DOI: 10.2514/6.20121275611.



Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. "Synthesizing Control Software from Boolean Relations." International Journal on Advances in Software vol. 5, nr 3&4 (2012): 212–223. IARIA. ISSN: 19422628.
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 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. Moreover, a formal
proof of the proposed algorithm correctness is
also shown. Finally, we present experimental
results showing effectiveness of the proposed
algorithm.
Keywords: Control Software Synthesis; Embedded Systems; Model Checking



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



S. Sinisi, V. Alimguzhin, T. Mancini, E. Tronci, F. Mari, and B. Leeners. "Optimal Personalised Treatment Computation through In Silico Clinical Trials on Patient Digital Twins." Fundamenta Informaticae 174 (2020): 283–310. IOS Press. ISSN: 18758681. DOI: 10.3233/FI20201943.
Abstract: In Silico Clinical Trials (ISCT), i.e. clinical experimental campaigns carried out by means of computer simulations, hold the promise to decrease time and cost for the safety and efficacy assessment of pharmacological treatments, reduce the need for animal and human testing, and enable precision medicine. In this paper we present methods and an algorithm that, by means of extensive computer simulationbased experimental campaigns (ISCT) guided by intelligent search, optimise a pharmacological treatment for an individual patient (precision medicine ). We show the effectiveness of our approach on a case study involving a real pharmacological treatment, namely the downregulation phase of a complex clinical protocol for assisted reproduction in humans.
Keywords: Artificial Intelligence; Virtual Physiological Human; In Silico Clinical Trials; Simulation; Personalised Medicine; In Silico Treatment Optimisation



Q. M. Chen, A. Finzi, T. Mancini, I. Melatti, and E. Tronci. "MILP, PseudoBoolean, and OMT Solvers for Optimal FaultTolerant Placements of Relay Nodes in Mission Critical Wireless Networks." Fundamenta Informaticae 174 (2020): 229–258. IOS Press. ISSN: 18758681. DOI: 10.3233/FI20201941.
Abstract: In critical infrastructures like airports, much care has to be devoted in protecting radio communication networks from external electromagnetic interference. Protection of such missioncritical radio communication networks is usually tackled by exploiting radiogoniometers: at least three suitably deployed radiogoniometers, and a gateway gathering information from them, permit to monitor and localise sources of electromagnetic emissions that are not supposed to be present in the monitored area. Typically, radiogoniometers are connected to the gateway through relay nodes . As a result, some degree of faulttolerance for the network of relay nodes is essential in order to offer a reliable monitoring. On the other hand, deployment of relay nodes is typically quite expensive. As a result, we have two conflicting requirements: minimise costs while guaranteeing a given faulttolerance. In this paper, we address the problem of computing a deployment for relay nodes that minimises the overall cost while at the same time guaranteeing proper working of the network even when some of the relay nodes (up to a given maximum number) become faulty (faulttolerance ). We show that, by means of a computationintensive preprocessing on a HPC infrastructure, the above optimisation problem can be encoded as a 0/1 Linear Program, becoming suitable to be approached with standard Artificial Intelligence reasoners like MILP, PBSAT, and SMT/OMT solvers. Our problem formulation enables us to present experimental results comparing the performance of these three solving technologies on a real case study of a relay node network deployment in areas of the Leonardo da Vinci Airport in Rome, Italy.



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.



Toni Mancini, Federico Mari, Annalisa Massini, Igor Melatti, and Enrico Tronci. "System Level Formal Verification via Distributed MultiCore Hardware in the Loop Simulation." In Proc. of the 22nd Euromicro International Conference on Parallel, Distributed and NetworkBased Processing. IEEE Computer Society, 2014. DOI: 10.1109/PDP.2014.32.

