Parameterized Model-Checking for Timed-Systems with Conjunctive Guards (Extended Version)

In this work we extend the Emerson and Kahlon's cutoff theorems for process skeletons with conjunctive guards to Parameterized Networks of Timed Automata, i.e. systems obtained by an \emph{apriori} unknown number of Timed Automata instantiated from a finite set $U_1, \dots, U_n$ of Timed Automata templates. In this way we aim at giving a tool to universally verify software systems where an unknown number of software components (i.e. processes) interact with continuous time temporal constraints. It is often the case, indeed, that distributed algorithms show an heterogeneous nature, combining dynamic aspects with real-time aspects. In the paper we will also show how to model check a protocol that uses special variables storing identifiers of the participating processes (i.e. PIDs) in Timed Automata with conjunctive guards. This is non-trivial, since solutions to the parameterized verification problem often relies on the processes to be symmetric, i.e. indistinguishable. On the other side, many popular distributed algorithms make use of PIDs and thus cannot directly apply those solutions

Model Checking Grid Security

Grid computing is one of the leading forms of high performance computing. Security in the grid environment is a challenging issue that can be characterized as a complex system involving many subtleties that may lead designers into error. This is similar to what happens with security protocols where automatic verification techniques (specially model checking) have been proved to be very useful at design time. This paper proposes a formal verification methodology based on model checking that can be applied to host security verification for grid systems. The proposed methodology must take into account that a grid system can be described as a parameterized model, and security requirements can be described as hyperproperties. Unfortunately, both parameterized model checking and hyperproperty verification are, in general, undecidable. However, it has been proved that this problem becomes decidable when jobs have some regularities in their organization. Therefore, this paper presents a verification methodology that reduces a given grid system model to a model to which it is possible to apply a ‘‘cutoff’’ theorem (i.e., a requirement is satisfied by a system with an arbitrary number of jobs if and only if it is satisfied by a system with a finite number of jobs up to a cutoff size). This methodology is supported by a set of theorems, whose proofs are presented in this paper. The methodology is explained by means of a case study: the Condor system

From Service Identification to Service Selection: An Interleaved Perspective

Business process implementation can be fastened by identifying component services that can be used to implement one or more process tasks and by selecting them from a repository of already implemented services. In this paper, we provide an iterative procedure to address this issue, by combining the two macro-phases of service identification and service selection. Starting from a workflow-based specification of the business process, service identification is firstly executed. The result of this phase is a decomposition tree, where basic process tasks are progressively organized into sub-processes (the candidate services) by applying an agglomerative clustering algorithm, based on cohesion and coupling metrics. Within the decomposition tree, a set of candidate services that minimize the coupling/cohesion ratio for the overall process is chosen. The service selection phase works on this decomposition and looks for available services. If the service selection phase fails for some candidate services, a revised set of candidate services is selected by leveraging on the decomposition tree

From a Goal-Oriented Methodology to a BDI Agent Language: The Case of Tropos and Alan

R. Meersman, Z. Tari, P. Herrero et al. (Eds.

From service identification to service selection: an interleaved perspective (extended abstract)

Business process implementation can be fastened by identifying component services that can be used to implement one or more process tasks and by selecting them from a repository of already implemented services. In this paper, we propose an on-going work for the design of an iterative procedure to address this issue, by combining the two macro-phases of service identification and service selection. Starting from a workflow-based specification of the business process, service identification is firstly executed. The result of this phase is a decomposition tree, where basic process tasks are progressively organized into sub-processes (the candidate services) by applying an agglomerative clustering algorithm, based on cohesion and coupling metrics. Within the decomposition tree, a set of candidate services that minimize the coupling/cohesion ratio for the overall process is chosen. The service selection phase works on this decomposition and looks for available services. If the service selection phase fails for some candidate services, a revised set of candidate services is selected by leveraging on the decomposition tree