Abstract: This paper presents a novel method for comparing computational properties of λ-terms that are typeable with intersection types, with respect to terms that are typeable with Curry types. We introduce a translation from intersection typing derivations to Curry typeable terms that is preserved by β-reduction: this allows the simulation of a computation starting from a term typeable in the intersection discipline by means of a computation starting from a simply typeable term. Our approach proves strong normalisation for the intersection system naturally by means of purely syntactical techniques. The paper extends the results presented in Bucciarelli et al. (1999) to the whole intersection type system of Barendregt, Coppo and Dezani, thus providing a complete proof of the conjecture, proposed in Leivant (1990), that all functions uniformly definable using intersection types are already definable using Curry types.

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: We present SAM, a symbolic model checker for ACTL, the action-based version of CTL. SAM relies on implicit representations of Labeled Transition Systems (LTSs), the semantic domain for ACTL formulae, and uses symbolic manipulation algorithms. SAM has been realized by translating (networks of) LTSs and, possibly recursive, ACTL formulae into BSP (Boolean Symbolic Programming), a programming language aiming at defining computations on boolean functions, and by using the BSP interpreter to carry out computations (i.e. verifications).

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.