Abstract: 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.

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 simulation-based 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.

Abstract: Text manipulation is one of the most common tasks for everyone using a computer. The increasing number of textual information in electronic format that every computer user collects everyday stresses the need of more powerful tools to interact with texts. Indeed, much work has been done to provide nonprogramming tools that can be useful for the most common text manipulation issues. Regular Expressions (RE), introduced by Kleene, are well–known in the formal language theory. RE received several extensions, depending on the application of interest. In almost all the implementations of RE search algorithms (e.g. the egrep [A] UNIX command, or the Perl [17] language pattern matching constructs) we find backreferences (as defind in [1]), i.e. expressions that make reference to the string matched by a previous subexpression. Generally speaking, it seems that all the kinds of synchronizations between subexpressions in a RE can be very useful when interacting with texts. Therefore, we introduce the Synchronized Regular Expressions (SRE) as a derivation of the Regular Expressions. We use SRE to present a formal study of the already known backreferences extension, and of a new extension proposed by us, which we call the synchronized exponents. Moreover, since we are talking about formalisms that should have a practical utility and can be used in the real world, we have the problem of how to present SRE to the final users. Therefore, in this paper we also propose a user–friendly syntax for SRE to be used in implementations of SRE–powered search algorithms.