The need to extend business process languages with the capability to model complex data objects along with the control flow perspective has lead to significant practical and theoretical advances in the field of Business Process Modeling (BPM).On the practical side, there are several suites for control flow and data modeling; nonetheless, when it comes to formal verification, the data perspective is abstracted away due to the intrinsic difficulty of handling unbounded data. On the theoretical side, there is significant literature providing decidability results for expressive data-aware processes. However, they struggle to produce a concrete impact as being far from real BPM architectures and, most of all, not providing actual verification tools. In this paper we aim at bridging such a gap: we provide a concrete framework which, on the one hand, being based on Petri Nets and relational models, is close to the widely used BPM suites, and on the other is grounded on solid formal basis which allow to perform formal verification tasks. Moreover, we show how to encode our framework in an action language so as to perform reachability analysis using virtually any state-of-the-art planner.

In this paper we study when an LTL formula on finite traces (LTLf formula) is insensitive to infiniteness, that is, it can be correctly handled as a formula on infinite traces under the assumption that at a certain point the infinite trace starts repeating an end event forever, trivializing all other propositions to false. This intuition has been put forward and (wrongly) assumed to hold in general in the literature. We define a necessary and sufficient condition to characterize whether an LTLf formula is insensitive to infiniteness, which can be automatically checked by any LTL reasoner. Then, we show that typical LTLf specification patterns used in process and service modeling in CS, as well as trajectory constraints in Planning and transition-based LTLf specifications of action domains in KR, are indeed very often insensitive to infiniteness. This may help to explain why the assumption of interpreting LTL on finite and on infinite traces has been (wrongly) blurred. Possibly because of this blurring, virtually all literature detours to Buechi automata for constructing the NFA that accepts the traces satisfying an LTLf formula. As a further contribution, we give a simple direct algorithm for computing such NFA.

In this paper we look at the problem of composing services that export their behavior in terms of a transition system, characterizing the choices of actions given to a client at each point in time. The composition consists of synthesizing an orchestrator that coordinates the available services so as to mimic the desired target service asked by the client. Specifically, in this paper we study the "conformant form" of the problem, where available services are partially controllable and partially observable, and hence, the orchestrator has to make its decisions exploiting the observations made so far only. We give a sound and complete procedure to synthesize the orchestrator in such case, and characterize the computational complexity of the problem. The procedure is based on working with belief (or knowledge) states, a standard technique to tackle conformant planning. Moreover we show that, although in general unavoidable, the powerset construction at the base of the belief state approach can be delegated to the symbolic manipulations of the game-structure model checking tool (TLV), which can be used to efficiently implement the orchestrator synthesis procedure.