Clara Ayora

VIVACE: A framework for the systematic evaluation of variability support in process-aware information systems

Context: The increasing adoption of process-aware information systems (PAISs) such as workow management systems, enterprise resource planning systems, or case management systems, together with the high variability in business processes (e.g., sales processes may vary depending on the respective products and countries), has resulted in large industrial process model repositories. To cope with this business process variability, the proper management of process variants along the entire process lifecycle becomes crucial. Objective: The goal of this paper is to develop a fundamental understanding of business process variability. In particular, the paper will provide a framework for assessing and comparing process variability approaches and the support they provide for the dierent phases of the business process life

Towards Run-Time Flexibility for Process Families: Open Issues and Research Challenges

The increasing adoption of process-aware information systems and the high variability of business processes in practice have resulted in process model repositories with large collections of related process variants (i.e., process families). Existing approaches for variability management focus on the modeling and configuration of process variants. However, case studies have shown that run-time configuration and re-configuration as well as the evolution of process variants are essential as well. Effectively handling process variants in these lifecycle phases requires deferring certain configuration decisions to the run-time, dynamically re-configuring process variants in response to contextual changes, adapting process variants to emerging needs, and evolving process families over time. In this paper, we characterize these flexibility needs for process families, discuss fundamental challenges to be tackled, and provide an overview of existing proposals made in this context.

A Qualitative Comparison of Approaches Supporting Business Process Variability

The increasing adoption of Process-Aware Information Systems, together with the reuse of process knowledge, has led to the emergence of process model repositories with large process families, i.e., collections of related process model variants. For managing such related model collections two types of approaches exist. While behavioral approaches take supersets of variants and derive a process variant by hiding and blocking process elements, structural approaches take a base process model as input and derive a process variant by applying a set of change operations to it. However, at the current stage no framework for assessing these approaches exists and it is not yet clear which approach should be better used and under which circumstances. Therefore, to give first insights about this issue, this work compares both approaches in terms of understandability of the produced process model artifacts, which is fundamental for the management of process families and the reuse of their contained process fragments. In addition, the comparison can serve as theoretical basis for conducting experiments as well as for fostering the development of tools managing business process variability.

Enhancing Modeling and Change Support for Process Families through Change Patterns

The increasing adoption of process-aware information systems (PAISs), together with the variability of business processes (BPs), has resulted in large collections of related process model variants (i.e., process families). To effectively deal with process families, several proposals (e.g., C-EPC, Provop) exist that extend BP modeling languages with variability-specific constructs. While fostering reuse and reducing modeling efforts, respective constructs imply additional complexity and demand proper support for process designers when creating and modifying process families. Recently, generic and language independent adaptation patterns were successfully introduced for creating and evolving single BP models. However, they are not sufficient to cope with the specific needs for modeling and evolving process families. This paper suggests a complementary set of generic and language-independent change patterns specifically tailored to the needs of process families. When used in combination with existing adaptation patterns, change patterns for process families will enable the modeling and evolution of process families at a high-level of abstraction. Further, they will serve as reference for implementing tools or comparing proposals managing process families.

Applying CVL to business process variability management

Business Processes (BP) exist in many variants depending on the application context. The use of variability mechanisms in BPs becomes essential for organizations to reduce development and maintenance efforts. However, such mechanisms entail big challenges. At design time, poor model specifications can turn process variants into difficult-to-maintain and understand artifacts. At runtime, process variants require continuous adaptations to achieve business goals in highly dynamic execution contexts. In order to address these challenges, in this paper we present a proposal to manage process variants at design time and runtime. At design time, process variants are modeled by combining a BP modeling language with the Common Variability Language. Then, at runtime, based on the created models and on the current context, process variants are adapted by means of MoRE-BP, a reconfiguration engine that is capable of performing dynamic adaptations automatically. An online-shop scenario illustrates our proposal and a proof-of-concept prototype validates its feasibility.

Do Models Improve the Understanding of Safety Compliance Needs?: Insights from a Pilot Experiment

Context. Many critical systems must meet safety compliance needs from safety standards. These standards are usually large textual documents whose compliance needs can be hard to understand. As a solution, the use of models has been proposed. Goal. We aim to provide evidence of the extent to which models improve the understanding of safety compliance needs. Method. We designed an experiment and ran a pilot to study the effectiveness, efficiency, and perceived benefits of understanding these needs, with the text of standards and with models in the form of UML object diagrams. Results. The overall results from 15 Bachelor students show that the effectiveness of understanding safety compliance needs increases very little with models (2%), and the efficiency even decreases (24%). Nonetheless, the results improve when the potential complexity in navigating the models is taken into account (15% effectiveness increase). The students find benefits in using the models but most consider that the models are hard to understand. Conclusions. The extent to which models improve the understanding of safety compliance needs seems to be lower than what the research community expects. New studies are necessary to confirm our initial insights.

Variability management in process families through change patterns

We present a set of change patterns for managing process families.The patters are derived from existing process variability-specific constructs.The patterns aim to reduce the effort for modeling and evolving a process family.They are validated through a case study to show the feasibility of their application. Context: The increasing adoption of process-aware information systems together with the high variability in business processes has resulted in collections of process families. These families correspond to a business process model and its variants, which can comprise hundreds or thousands of different ways of realizing this process. Managing process variability in this context can be very challenging, labor-intensive, and error-prone, and new approaches for managing process families are necessary.Objective: We aim to facilitate variability management in process families, ensure process family correctness, and reduce the effort needed for such purposes.Method: We have derived a set of change patterns for process families from variability-specific language constructs identified in the literature. For validation, we have conducted a case study with a safety standard in which we have measured the number of operations needed to model and evolve the variability of the standard with and without the patterns.Results: We present 10 change patterns for managing variability in process families and show how they can be implemented. The patterns support the modeling and evolution of process families and ensure process family correctness by automatically introducing and deleting modeling elements. The case study results show that the application of the defined change patterns can reduce the number of operations when modeling a process family by 34% and when evolving it by 40%.Conclusions: The application of the change patterns can help in effectively modeling and evolving large and highly-variable process families. Their application can also considerably reduce variability management effort.

Dealing with variability in Process-Aware Information Systems: language requirements, features, and existing proposals

The increasing adoption of Process-aware Information Systems (PAISs), together with the variability of Business Processes (BPs) across different application contexts, has resulted in large process model repositories with collections of related process model variants. To reduce both costs and occurrence of errors, the explicit management of variability throughout the BP lifecycle becomes crucial. In literature, several proposals dealing with BP variability have been proposed. However, the lack of a method for their systematic comparison makes it difficult to select the most appropriate one meeting current needs best. To close this gap, this work presents an evaluation framework that allows analyzing and comparing the variability support provided by existing proposals developed in the context of BP variability. The framework encompasses a set of language requirements as well as a set of variability support features. While language requirements allow assessing the expressiveness required to explicitly represent variability of different process perspectives, variability support features reflect the tool support required to properly cover such expressiveness. Our evaluation framework has been derived based on an in-depth analysis of several large real-world process scenarios, an extensive literature review, and an analysis of existing PAISs. In this vein, the framework helps to understand BP variability along the BP lifecycle. In addition, it supports PAISs engineers in deciding, which of the existing BP variability proposals meets best their needs.

An Experimental Evaluation of the Understanding of Safety Compliance Needs with Models

Context: Most safety-critical systems have to fulfil compliance needs specified in safety standards. These needs can be difficult to understand from the text of the standards, and the use of conceptual models has been proposed as a solution. Goal: We aim to evaluate the understanding of safety compliance needs with models. Method: We have conducted an experiment to study the effectiveness, efficiency, and perceived benefits in understanding these needs, with text of safety standards and with UML object diagrams. Results: Sixteen Bachelor students participated in the experiment. Their average effectiveness in understanding compliance needs and their average efficiency were higher with models (17% and 15%, respectively). However, the difference is not statistically significant. The students found benefits in using models, but on average they are undecided about their ease of understanding. Conclusions: Although the results are not conclusive enough, they suggest that the use of models could improve the understanding of safety compliance needs.