Information Hiding, Inheritance and Concurrency

We aim to provide information hiding support in concurrent object-oriented programming languages. We study the issue of information hiding at the object level and class level, in the context of an object-oriented extension of the Join calculus a process calculus in the tradition of the Pi-calculus. At the object level, we improve a privacy mechanism proposed in prior work by defining a simpler chemical semantics for privacy control. At the class level, we propose a hiding mechanism by designing a new operation on classes. We define its formal semantics in terms of alpha-converting hidden names to fresh names, and its typing in terms of eliminating hidden names from class types. We study the standard soundness property of the type system, as well as specific properties concerning hiding. Some, if not most, of our choices in designing our system are motivated by implementation. As an evidence of practical significance, we implement our model in a prototyping system. From that experience we draw guidelines for a full-scale implementation

A Process Calculus for Dynamic Networks

In this paper we propose a process calculus framework for dynamic networks in which the network topology may change as computation proceeds. The proposed calculus allows one to abstract away from neighborhood-discovery computations and it contains features for broadcasting at multiple transmission ranges and for viewing networks at different levels of abstraction. We develop a theory of confluence for the calculus and we use the machinery developed towards the verification of a leader-election algorithm for mobile ad hoc networks

Process algebra modelling styles for biomolecular processes

We investigate how biomolecular processes are modelled in process algebras, focussing on chemical reactions. We consider various modelling styles and how design decisions made in the definition of the process algebra have an impact on how a modelling style can be applied. Our goal is to highlight the often implicit choices that modellers make in choosing a formalism, and illustrate, through the use of examples, how this can affect expressability as well as the type and complexity of the analysis that can be performed

Configurable Process Models as a Basis for Reference Modeling

Off-the-shelf packages such as SAP need to be configured to suit the requirements of an organization. Reference models support the configuration of these systems. Existing reference models use rather traditional languages. For example, the SAP reference model uses Eventdriven Process Chains (EPCs). Unfortunately, traditional languages like EPCs do not capture the configuration-aspects well. Consider for example the concept of "choice" in the control-flow perspective. Although any process modeling language, including EPCs, offers a choice construct (e.g., the XOR connector in EPCs), a single construct will not be able to capture the time dimension, scope, and impact of a decision. Some decisions are taken at run-time for a single case while other decisions are taken at build-time impacting a whole organization and all current and future cases. This position paper discusses the need for configurable process models as a basic building block for reference modeling. The focus is on the control-flow perspective. © Springer-Verlag Berlin Heidelberg 2006

Process Algebras

Process Algebras are mathematically rigorous languages with well defined semantics that permit describing and verifying properties of concurrent communicating systems. They can be seen as models of processes, regarded as agents that act and interact continuously with other similar agents and with their common environment. The agents may be real-world objects (even people), or they may be artifacts, embodied perhaps in computer hardware or software systems. Many different approaches (operational, denotational, algebraic) are taken for describing the meaning of processes. However, the operational approach is the reference one. By relying on the so called Structural Operational Semantics (SOS), labelled transition systems are built and composed by using the different operators of the many different process algebras. Behavioral equivalences are used to abstract from unwanted details and identify those systems that react similarly to external experiments

Concurrent constraint programming with process mobility

We propose an extension of concurrent constraint programming with primitives for process migration within a hierarchical network, and we study its semantics. To this purpose, we first investigate a "pure " paradigm for process migration, namely a paradigm where the only actions are those dealing with transmissions of processes. Our goal is to give a structural definition of the semantics of migration; namely, we want to describe the behaviour of the system, during the transmission of a process, in terms of the behaviour of the components. We achieve this goal by using a labeled transition system where the effects of sending a process, and requesting a process, are modeled by symmetric rules (similar to handshaking-rules for synchronous communication) between the two partner nodes in the network. Next, we extend our paradigm with the primitives of concurrent constraint programming, and we show how to enrich the semantics to cope with the notions of environment and constraint store. Finally, we show how the operational semantics can be used to define an interpreter for the basic calculus.

Design Environments for Complex Systems

The paper describes an approach for modeling complex systems by hiding as much formal details as possible from the user, still allowing verification and simulation of the model. The interface is based on UML to make the environment available to the largest audience. To carry out analysis, verification and simulation we automatically extract process algebras specifications from UML models. The results of the analysis is then reflected back in the UML model by annotating diagrams. The formal model includes stochastic information to handle quantitative parameters. We present here the stochastic -calculus and we discuss the implementation of its probabilistic support that allows simulation of processes. We exploit the benefits of our approach in two applicative domains: global computing and systems biology