Toni Mancini, Federico Mari, Annalisa Massini, Igor Melatti, Fabio Merli, and Enrico Tronci. "System Level Formal Verification via Model Checking Driven Simulation." In Proceedings of the 25th International Conference on Computer Aided Verification. July 13-19, 2013, Saint Petersburg, Russia, 296–312. Lecture Notes in Computer Science 8044. Springer - Verlag, 2013. ISSN: 0302-9743. DOI: 10.1007/978-3-642-39799-8_21.
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Vadim Alimguzhin, Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. "A Map-Reduce 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: 0302-9743. DOI: 10.1007/978-3-642-39176-7_4.
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Vadim Alimguzhin, Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. "On-the-Fly 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: 0302-9743. DOI: 10.1007/978-3-642-39176-7_5.
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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: 1942-2628.
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
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Ed Kuijpers, Luigi Carotenuto, Jean- Cristophe Malapert, Daniela Markov-Vetter, Igor Melatti, Andrea Orlandini, and Ranni Pinchuk. "Collaboration on ISS Experiment Data and Knowledge Representation." In Proc. of IAC 2012. Vol. D.5.11., 2012.
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Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. Quantized Feedback Control Software Synthesis from System Level Formal Specifications for Buck DC/DC Converters. Vol. abs/1105.5640. CoRR, Technical Report, 2011.
Abstract: Many Embedded Systems are indeed Software Based Control Systems (SBCSs), that is control systems whose controller consists of control software running on a microcontroller device. This motivates investigation on Formal Model Based Design approaches for automatic synthesis of SBCS control software. In previous works we presented an algorithm, along with a tool QKS implementing it, that from a formal model (as a Discrete Time Linear Hybrid System, DTLHS) of the controlled system (plant), implementation specifications (that is, number of bits in the Analog-to-Digital, AD, conversion) and System Level Formal Specifications (that is, safety and liveness requirements for the closed loop system) returns correct-by-construction control software that has a Worst Case Execution Time (WCET) linear in the number of AD bits and meets the given specifications. In this technical report we present full experimental results on using it to synthesize control software for two versions of buck DC-DC converters (single-input and multi-input), a widely used mixed-mode analog circuit.
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Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. From Boolean Functional Equations to Control Software. Vol. abs/1106.0468. CoRR, Technical Report, 2011.
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) at most O(nr), being n = |x| the number of arguments of functions in F and r the number of functions in F.
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T. Mancini, F. Mari, I. Melatti, I. Salvo, E. Tronci, J. K. Gruber, B. Hayes, M. Prodanovic, and L. Elmegaard. "User Flexibility Aware Price Policy Synthesis for Smart Grids." In Digital System Design (DSD), 2015 Euromicro Conference on, 478–485., 2015. DOI: 10.1109/DSD.2015.35.
Keywords: 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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T. Mancini, I. Melatti, and E. Tronci. "Any-horizon uniform random sampling and enumeration of constrained scenarios for simulation-based formal verification." IEEE Transactions on Software Engineering (2021): 1. ISSN: 1939-3520. Notes: To appear. DOI: 10.1109/TSE.2021.3109842.
Abstract: Model-based approaches to the verification of non-terminating Cyber-Physical Systems (CPSs) usually rely on numerical simulation of the System Under Verification (SUV) model under input scenarios of possibly varying duration, chosen among those satisfying given constraints. Such constraints typically stem from requirements (or assumptions) on the SUV inputs and its operational environment as well as from the enforcement of additional conditions aiming at, e.g., prioritising the (often extremely long) verification activity, by, e.g., focusing on scenarios explicitly exercising selected requirements, or avoiding </i>vacuity</i> in their satisfaction. In this setting, the possibility to efficiently sample at random (with a known distribution, e.g., uniformly) within, or to efficiently enumerate (possibly in a uniformly random order) scenarios among those satisfying all the given constraints is a key enabler for the practical viability of the verification process, e.g., via simulation-based statistical model checking. Unfortunately, in case of non-trivial combinations of constraints, iterative approaches like Markovian random walks in the space of sequences of inputs in general fail in extracting scenarios according to a given distribution (e.g., uniformly), and can be very inefficient to produce at all scenarios that are both legal (with respect to SUV assumptions) and of interest (with respect to the additional constraints). For example, in our case studies, up to 91% of the scenarios generated using such iterative approaches would need to be neglected. In this article, we show how, given a set of constraints on the input scenarios succinctly defined by multiple finite memory monitors, a data structure (scenario generator) can be synthesised, from which any-horizon scenarios satisfying the input constraints can be efficiently extracted by (possibly uniform) random sampling or (randomised) enumeration. Our approach enables seamless support to virtually all simulation-based approaches to CPS verification, ranging from simple random testing to statistical model checking and formal (i.e., exhaustive) verification, when a suitable bound on the horizon or an iterative horizon enlargement strategy is defined, as in the spirit of bounded model checking.
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I. Melatti, F. Mari, T. Mancini, M. Prodanovic, and E. Tronci. "A Two-Layer Near-Optimal Strategy for Substation Constraint Management via Home Batteries." IEEE Transactions on Industrial Electronics (2021): 1. Notes: To appear. DOI: 10.1109/TIE.2021.3102431.
Abstract: Within electrical distribution networks, substation constraints management requires that aggregated power demand from residential users is kept within suitable bounds. Efficiency of substation constraints management can be measured as the reduction of constraints violations w.r.t. unmanaged demand. Home batteries hold the promise of enabling efficient and user-oblivious substation constraints management. Centralized control of home batteries would achieve optimal efficiency. However, it is hardly acceptable by users, since service providers (e.g., utilities or aggregators) would directly control batteries at user premises. Unfortunately, devising efficient hierarchical control strategies, thus overcoming the above problem, is far from easy. We present a novel two-layer control strategy for home batteries that avoids direct control of home devices by the service provider and at the same time yields near-optimal substation constraints management efficiency. Our simulation results on field data from 62 households in Denmark show that the substation constraints management efficiency achieved with our approach is at least 82% of the one obtained with a theoretical optimal centralized strategy.
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