Yasmine Charif

Methodology and Tool for Business Process Compensation Design

A typical e-business transaction takes hours or days to complete, involves a number of partners, and comprises many failure points. With short-lived transactions, database systems ensure atomicity by either committing all of the elements of the transaction, or by canceling all of them in case of a failure. With typical e-business transactions, strict atomicity is not practical, and we need a way of reversing the effects of those activities that cannot be rolled back: that is compensation. For a given business process, identifying the various failure points, and designing the appropriate compensation processes represents the bulk of process design effort. Yet, business analysts have little or no guidance. For a given failure point, there appears to be an infinite variety of ways to compensate for it. We recognize that compensation is a business issue, but we argue that it can be explained in terms of a handful of parameters within the context of the REA ontology, including things such as the type of activity, the type of resource, and organizational policies. We propose a three-step compensation design approach that 1) starts by abstracting a business process to focus on those activities that create/modify value, 2) compensates for those activities, individually, based on values of the compensation parameters, and 3) composes those compensations using a Saga-like approach. In this paper, we present our approach along with an implementation algorithm and propose a business ontology for compensation design.

Towards anticipatory service composition in Ambient Intelligence

Anticipatory cognitive mechanisms have been investigated so far in gaze control or in simple robot navigation. This is in order to build cognitive systems endowed with the ability to predict the outcome of their actions. However, research on the actual benefit of anticipatory behavior in Ambient Intelligence (AmI) for user assistance is still in its infancy. This paper proposes some use cases to illustrate the benefits of anticipatory service composition in AmI, highlights issues resulting from the incorporation of anticipation into ubiquitous environments, comes up with guideline principles and existing approaches that have shown promising results to address the identified challenges, and emphasizes the questions and issues that still need a suitable research program before they can be addressed.

Towards a Framework for Modeling Business Compensation Processes

A typical e-business transaction takes hours or days to complete, involves a number of partners, and comprises many failure points[8]. With short-lived transactions, database systems ensure atomicity by either committing all of the elements of the transaction, or by canceling all of them in case of a failure. With typical e-business transactions, strict atomicity is not practical, and we need a way of reversing the effects of those activities that cannot be rolled back: that is compensation. For a given business process, identifying the various failure points, and designing the appropriate compensation processes represents the bulk of process design effort[8]. Yet, business analysts have little or no guidance, as for a given failure point, there appears to be an infinite variety of ways to compensate for it. We recognize that compensation is a business issue, but we argue that it can be explained in terms of a handful of parameters within the context of REA ontology [20], including things such as the type of activity, the type of resource, and organizational policies. We propose a three-step process compensation design approach that 1) starts by abstracting a business process to focus on those activities that create/modify value, 2) compensates for those activities, individually, based on values of the compensation parameters, and 3) composes those compensations using a Saga-like approach [10]. In this paper, we present our approach, and discuss issues for future research.

E-Tourism Portal: A Case Study in Ontology-Driven Development

Software development is a fairly complex activity, that is both labour-intensive and knowledge-rich, and systematically delivering high-quality software that addresses the users’ needs, on-time, and within budget, remains an elusive goal. This is even more true for internet applications presents additional challenges, including, 1) a predominance of the highly volatile interaction logic, and 2) stronger time-to-market pressures. Model-driven development purports to alleviate the problem by slicing the development process into a sequence of semantics-preserving transformations that start with a computation-independent model, through to an architecture-neutral platform independent model (PIM), all the way to platform-specific model or code at the other end. That is the idea(l). In general, however, the semantic gap between the CIM and PIM is such that the transition between them is hard to formalize. In this paper, we present a case study where we used an ontology to drive the development of an e-tourism portal. Our project showed that it is possible to drive the development of an internet application from a semantic description of the business entities, and illustrated the effectiveness of this approach during maintenance. It also highlighted the kinds of trade-offs we needed to make to reconcile somewhat lofty design principles with the imperative of producing a product with reasonable quality.

A pattern-based approach to extract REA value models from business process models

Business models are economic models that describe the rationale of why organizations create and deliver value. These models focus on what organizations offer and why. Business process models capture business activities and the ways in which they are accomplished i.e. their coordination. They explain who is involved in the activities, and how and when these activities should be performed. This paper discusses the alignment between business models and business process models. It proposes a novel systematic method for extracting a value chain i.e. business model expressed in the Resources, Events, Agents REA ontology from a business process model expressed in Business Process Model and NotationTM. Our contribution is twofold: 1 from a theoretical standpoint we identified a set of structural and behavioural patterns that enable us to infer the corresponding REA value chain; 2 from a pragmatic perspective, our approach can be used to derive useful knowledge about the business process and serve as a starting point for business analysis.

Towards Simplifying and Automating Business Process Lifecycle Management in Hybrid Clouds

Business Process Management (BPM) software provides visibility into business processes in organizations of all sizes and helps increase process efficiency continuously. However, the time and effort involved in modeling, deploying and executing a business process is tremendous and as a result organizations struggle to agilely adapt business processes to dynamic business requirements. On the other hand, the growing popularity of cloud computing poses opportunities and challenges on how business processes can leverage resource outsourcing and elasticity. In light of the above, this paper presents a business process management platform that assists business analysts lacking necessary programming expertise by automating manual steps and providing guidance and recommendations to quickly and efficiently design, implement, deploy and execute business processes in a hybrid cloud environment.

Towards Automating Business Process Compensation Scoping Logic

Business process compensation is an error recovery strategy aiming at semantically reversing the effects of an interrupted business process execution and restoring it to a valid state. Studies have shown that modeling error handling in general, and compensation in particular, represents the bulk of process design efforts. To that end, we proposed in a previous work an approach to model semi-automatically compensation processes based on a business analysis within the REA framework, restoring it to its initial state. However, we argue that it is neither practical nor desirable to cancel the whole process in some situations. Instead, the process should be reversed to an intermediate state from which it could resume its execution. This work aims at solving this compensation scoping problem by inferring the possible “rollback points”. Our approach relies on a resource flow analysis within the context of an OCL-based behavioral specification of business process activities. In this paper, we present our slicing algorithm and lay our ground ideas on how we could identify possible candidates as process’ rollback activities.

Automating Reusable Workflow Development from Design to Instantiation

The proliferation of web services in both number and variety implies the co-existence of a wide number of service options, input/output data types, and encapsulations. Consequently, composing services into usable workflows has become increasingly development intensive. In order to leverage the design of a workflow and facilitate its reusability and maintenance, many research efforts have advocated to compose services at the type level instead of the instance level while using customized glue code to map service types to service instances. Another challenge then appears: Service types, either manually defined by domain experts or automatically generated from an ontology, cannot be automatically instantiated into concrete services due to the coarse granularity of service types and the complexity of input/output parameter mapping. This paper proposes a platform to automatically extract instantiable abstract operations from registered services and that enables the automatic generation of glue code that links concrete services to service types in order to produce reusable executable workflows.

Ontology-based model-driven development of a destination management portal: Experience and lessons learned: Model-driven development: Experience and lessons learned - Mili et al

We present a case study in model‐driven development of an e‐tourism portal that we chose to develop through generation from a domain model encoded as an ontology. We present (1) the requirements of e‐tourism portal, which dictated its high‐level design; (2) the principles behind our implementation strategy, including the use of a domain ontology as a starting model within the context of a model‐driven transformational approach; (3) the ontology development process and the code generation strategy used; and (4) the lessons learned. In particular, we compare our experiences to those reported in the model‐driven engineering (MDE) literature along 3 dimensions, ie, (1) the impact of MDE on the development process, (2) the choice of the modeling approach, and (3) the impact of code generation on design and code quality and testing. Overall, our experiences corroborated some of the theoretical claims and many of the practical experiences with MDE. Key findings include (1) model‐driven development makes maintenance, not development, more efficient; (2) it does require a higher skill level than traditional development; (3) clients and managers need to be educated into what incrementality means in a generative approach; (4) UML is neither necessary nor sufficient to handle the required representational flexibility; (5) it is difficult to build models that are good for both human consumption and code generation; and (6) it is difficult to generate code that is, simultaneously, efficient, pretty, and easy to maintain. We conclude by summarizing the findings of the paper.

Interpretable Classifier for Identifying High-Value Child Support Cases

This work brings interpretable and accurate data analytics to child support agencies with the goal of substantially increasing their effectiveness. In the realm of child support, a custodial parent may be entitled to periodic child support payments from the noncustodial parent. In order to analyze this process, we have gathered case data from several child support agencies. The objective of the work is to develop analytical models that characterize and predict high-value child support cases. High-value cases are those that result in successful payments and require far fewer resources for enforcement. We create interpretable and accurate scoring models to identify these cases so that the key attributes driving their prediction are easily understood by the caseworkers. This information may be integrated with case management systems to schedule and prioritize the caseload.