International Journal of Cooperative Information Systems

The ability to describe business processes as executable models has always been one of the fundamental premises of workflow management. Yet, the tacit nature of human knowledge is often an obstacle to eliciting accurate process models. On the other hand, the result of process modeling is a static plan of action, which is difficult to adapt to changing procedures or to different business goals. In this article, we attempt to address these problems by approaching workflow management with a combination of learning and planning techniques. Assuming that processes cannot be fully described at build-time, we make use of learning techniques, namely Inductive Logic Programming (ILP), in order to discover workflow activities and to describe them as planning operators. These operators will be subsequently fed to a partial-order planner in order to find the process model as a planning solution. The continuous interplay between learning, planning and execution aims at arriving at a feasible plan by successive refinement of the operators. The approach is illustrated in two simple scenarios. Following a discussion of related work, the paper concludes by presenting the main challenges that remain to be solved.

Nowadays, Enterprise Application Integration (EAI) constitutes a real and growing need for most of enterprises, particularly for large and dynamic ones. Actually, the major problem of EAI is the heterogeneity problem, especially the semantic one. This latter is not correctly addressed by today's integration solutions, which focus mainly on syntactical integration. Dealing with the semantic aspect, which will certainly promote EAI by providing it more consistency and robustness, needs some appropriate principles such as ontology urbanization and mediation. These latter that constitute the main focus of this paper aim to favor the semantic application integration allowing to correctly capture, structure, master and reason upon the semantics, which currently constitutes a big challenge for several enterprises that are in quest of more flexibility and manageability.

To manage the development of cooperative information systems that support the dynamics and mobility of modern businesses, separation of concern mechanisms and abstractions are needed. Model driven development (MDD) approaches utilize abstraction and transformation to handle complexity. In MDD, specifying transformations between models at various levels of abstraction can be a complex task. Specifying transformations for pervasive system services that are tangled with other system services is particularly difficult because the elements to be transformed are distributed across a model. This paper presents an aspect oriented model driven framework (AOMDF) that facilitates separation of pervasive services and supports their transformation across different levels of abstraction. The framework facilitates composition of pervasive services with enterprise services at various levels of abstraction. The framework is illustrated using an example in which a platform independent model of a banking service is transformed to a platform specific model.

The use of open, Internet-based communications for business-to-business (B2B) interactions requires accountability for and acknowledgment of the actions of participants. Accountability and acknowledgment can be achieved by the systematic maintenance of an irrefutable audit trail to render the interaction non-repudiable. To safeguard the interests of each party, the mechanisms used to meet this requirement should ensure fairness. That is, misbehavior should not disadvantage well-behaved parties. Despite the fact that Web services are increasingly used to enable B2B interactions, there is currently no systematic support to deliver such guarantees. This paper introduces a flexible framework to support fair non-repudiable B2B interactions based on a trusted delivery agent. A Web services implementation is presented. The role of the delivery agent can be adapted to different end user capabilities and to meet different application requirements.

In a model-driven design process the interaction between application parts can be described at various levels of platform-independence. At the lowest level of platform-independence, interaction is realized by interaction mechanisms provided by specific middleware platforms. At higher levels of platform-independence, interaction must be described in such a way that it can be further refined and realized onto a number of different middleware platforms, each with its particular interaction mechanisms and implementation constraints. In this paper, we investigate concepts that support interaction design at various levels of middleware-platform-independence. In addition, we propose design operations for interaction refinement. The application of these operations to source designs results in target designs that take into account implementation constraints imposed by platforms, while preserving characteristics prescribed in source designs. Target designs are related to source designs by conformance. We discuss how transformation and conformance can be related, such that transformations indeed preserve the characteristics prescribed by a source design.

Understanding nonfunctional aspects of system behavior is an essential component of practical software development and maintenance. Many nonfunctional system properties, such as reliability and availability, involve time and probabilities. In this paper, we present a framework for runtime verification and prediction of timed and probabilistic nonfunctional properties of component-based architectures, built using the Meta-Object Facility and the Distributed Management Task Force's Common Information Model (CIM) standard. We describe a Microsoft .NET-based implementation of our framework. We define a language for describing timed probabilistic behavior based on Probabilistic Computational Tree Logic (PCTL). We provide a formal semantics for this language in terms of observed application execution traces. The semantics is interesting in that it permits checking of required timing behavior both over the overall average of traces and also over local "trends" in traces. The latter aspect of the semantics is achieved by incorporating exponential smoothing prediction techniques into the truth function for statements of our language. The semantics is generic over the aspects of an application that are represented by states and state transitions. This enables the language to be used to describe a wide range of nonfunctional properties for runtime verification and prediction purposes. We explain how statements of our language are used to define precise contracts for system monitoring, through relating the semantics to an extended CIM monitoring infrastructure.

This paper presents a formal system for reasoning about violations of obligations in contracts. The system is based on the formalism for the representation of contrary-to-duty obligations. These are the obligations that take place when other obligations are violated as typically applied to penalties in contracts. The paper shows how this formalism can be mapped onto the key policy concepts of a contract specification language, called Business Contract Language (BCL), previously developed to express contract conditions for run time contract monitoring. The aim of this mapping is to establish a formal underpinning for this key subset of BCL.