Wiem Khlif

Integrating semantics and structural information for BPMN model refactoring

Refactoring a business process model may enhance the understandability and/or ease the maintainability of the process. So far proposed refactoring approaches tackled only the structural aspect of a model. As we illustrate in this paper, combining the semantic aspect with the structural aspect further reduces the control flow complexity of a business process modeled in the Business Process Modelling Notation. Our refactoring method adapts a set of rules from the graph optimization domain. We illustrate the efficiency of a subset of the proposed rules through well-established complexity metrics.

A methodology for the semantic and structural restructuring of BPMN models

Purpose Restructuring a business process (BP) model may enhance the BP performance and improve its understandability. So-far proposed restructuring methods use either refactoring which focuses on structural aspects, social network discovery which uses semantic information to guide the affiliation process during its analysis, or social network rediscovery which uses structural information to identify clusters of actors according to their relationships. The purpose of this paper is to propose a hybrid method that exploits both the semantic and structural aspects of a BP model. Design/methodology/approach The proposed method first generates a social network from the BP model. Second, it applies hierarchical clustering to determine the performers’ partitions; this step uses the social context which specifies features related to performers, and two new distances that account for semantic and structural information. Finally, it applies a set of behavioral and organizational restructuring rules adapted from the graph optimization domain; each rule uses the identified performers’ partitions and the business context to reduce particular quality metrics. Findings The efficiency of the proposed method is illustrated through well-established complexity metrics. The illustration is made through the development of a tool that fully supports the proposed method and proposes a strategy for the application of the restructuring rules. Originality/value The proposed method has the merit of combining the semantic and structural aspects of a Business Process Modeling Notation model to identify restructuring operations whose ordered application reduces the complexity of the initial model.

Semantic and structural performer clustering in BPMN models transformed into social network models

Current trends in organization restructuring focus on the social relationships among the organizational actors in order to improve the business process. Proposed business process model restructuring approaches adopt either social network discovery or rediscovery techniques. Social network discovery uses semantic information to guide the affiliation process during its analyses, whereas social network rediscovery uses structural information to identify groups in the social network. In this paper, we propose a hybrid method that exploits both knowledge discovery and rediscovery to suggest a new structure of a business process model that is based on performers clustering. Using the context concept, the proposed method applies a hierarchical clustering algorithm to determine the performer partitions; the algorithm uses two newly defined distances that account for the semantic and structural information. The method is illustrated and evaluated experimentally to analyze its performance.

Designing BP-IS Aligned Models: An MDA-based Transformation Methodology.

The necessity of aligning an enterprise’s IS model to its business process model (BPM) is irrefutable. How to ensure the establishment and/or maintenance of this alignment remains, however, a pressing need for enterprises seeking to establish a new IS, better govern its enterprise architecture, and/or update its existing IS face to business-driven changes. The main difficulty of establishing/maintaining BP-IS models alignment stems from the divergent knowledge domains of the stakeholders (business process experts and software developers). To bridge the gap between these two stakeholders, this paper proposes an MDA compliant approach to automate the generation of UML class diagrams from BPMN models. The generated IS design can be used either to establish a new IS system, or analyze or maintain an existing one. The generation is defined in terms of transformations that ensure the alignment of the class diagram to the BPMN model by both accounting for the semantics and structure of the BPMN model, and providing for all business objects

Analyzing Functional Changes in BPMN Models using COSMIC.

When performing functional requirements analysis, software developers need to understand the application domain to fulfil organizational needs. This is essential for making trade-off decisions and achieving the success of the software development project. An application domain is dealt within the modelling phase of the business process lifecycle. Assuming that functional changes are inevitable, we propose to use the standard COSMIC to evaluate these changes and provide indicators of change status in the business domain. Expressing functional changes in terms of COSMIC Function Point units can be helpful in identifying changes leading to potential impact on the business processs functional size. In addition, we propose a top-down decomposition approach to specify requirements and analyse change impact on BPMN models at different

EVARES: A Quality-driven Refactoring Method for Business Process Models.

The business performance of an enterprise tightly depends on the quality of its business process model (BPM). This dependence prompted several propositions to improve quality sub-characteristics (e.g. modifiability and reusability) of a BPM through transformation operations to change the internal structure of the model while preserving its external behaviour. Each transformation may improve certain metrics related to one quality sub characteristic while degrading others. Consequently, one challenge of this model transformation-based quality improvement approach is how to identify the application order of the transformations to derive the “best” quality model. This paper proposes a local optimization-based, heuristic method to decide on the application order of the transformations to produce the best quality BPM. The method is guided by both the perspectives, and the impact of each transformation on the quality metrics pertinent to the perspectives as well as the quality sub characteristics of interest to the designer. The method’s and an experimental evaluation are presented.