Variability management in process families through change patterns

© 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/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. (C) 2016 Elsevier B.V. All rights reserved.This work has been developed with the financial support of Spanish Ministry of Economy and Competitiveness under the project SMART-ADAPT TIN2013-42981-P. We also want to thank Barbara Weber and Manfred Reichert for their valuable input and feedback on the design and development of the set of change patterns for process families.Ayora Esteras, C.; Torres Bosch, MV.; De La Vara González, JL.; Pelechano Ferragud, V. (2016). Variability management in process families through change patterns. Information and Software Technology. 74:86-104. https://doi.org/10.1016/j.infsof.2016.01.007S861047

Enhancing Variability Modeling in Process-Aware Information Systems through Change Patterns

[EN] The increasing adoption of process-aware information systems (PAISs) 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. Modeling and managing process variability in this context can be very challenging due to the size of these families. Motivated by this challenge, several approaches enabling process variability have been developed. However, with these approaches PAIS engineers usually are required to model and manage one by one all the elements of a process family and ensure its correctness by their own. This can be tedious and error-prone especially when a process family comprises hundreds or thousands of process variants. For example, variability may not be properly reflected since PAIS engineers need to be aware of each variation of each process variant. Thus, there is a need of methods that allow PAIS engineers to model process variability more explicitly, especially at a level of abstraction higher than the one provided by the existing process variability approaches. However, how process variability is represented in existing approaches becomes critical for these methods (e.g., what language constructs are used to model process variability). In this context, the use of modeling patterns (reusable solutions to a commonly occurring problem) is a promising way to address these issues. For example, patterns have been proved as an efficient solution to model individual business processes. The objective of this thesis is to enhance the modeling of variability in process families through change patterns. First, we conduct a systematic study to analyze existing process variability approaches regarding their expressiveness with respect to process variability modeling as well as their process support. Thus, we can identify how process variability is actually modeled by existing approaches (i.e., a core set of variability-specific language constructs). In addition, based on the obtained empirical evidence, we derive the VIVACE framework, a complete characterization of process variability which comprises also a core set of features fostering process variability. VIVACE enables PAIS engineers to evaluate existing process variability approaches as well as to select that variability approach meeting their requirements best. In addition, it helps process engineers in dealing with PAISs supporting process variability. Second, to facilitate variability modeling in process families, based on the identified language constructs, we present a set of 10 change patterns and show how they can be implemented in a process variability approach. In particular, these patterns support process family modeling and evolution and are able to ensure process family correctness. In order to prove their effectiveness and analyze their suitability, we applied these change patterns in a real scenario. More concretely, we conduct a case study with a safety standard with a high degree of variability. The case study results show that the application of the change patterns can reduce the effort for process family modeling in a 34% and for evolution in a 40%. In addition, we have analyzed how PAIS engineers apply the patterns and their perceptions of this application. Most of them expressed some benefit when applying the change patterns, did not perceived an increase of mental effort for applying the patterns, and agreed upon the usefulness and ease of use of the patterns.[ES] La creciente adopción de sistemas de información dirigidos por procesos de negocio (PAIS) junto con la alta variabilidad en dichos procesos, han dado lugar a la aparición de colecciones de familias de procesos. Estas familias están constituidas por un modelo de proceso de negocio y sus variantes, las cuales pueden comprender entre cientos y miles de diferentes formas de llevar a cabo ese proceso. Gestionar la variabilidad en este contexto puede resultar muy difícil dado el tamaño que estas familias pueden alcanzar. Motivados por este desafío, se han desarrollado varias soluciones que permiten la gestión de la variabilidad en los procesos de negocio. Sin embargo, con estas soluciones los ingenieros deben crear y gestionar uno por uno todos los elementos de las familias de procesos y asegurar ellos mismos su corrección. Esto puede resultar tedioso y propenso a errores especialmente cuando las familias están compuestas de miles de variantes. Por ejemplo, la variabilidad puede no quedar adecuadamente representada ya que los ingenieros deben ser conscientes de todas y cada una de las variaciones de todas las variantes. Así, son necesarios nuevos métodos que permitan modelar la variabilidad de los procesos de una manera más explícita, a un nivel de abstracción más alto del proporcionado por las soluciones actuales. Sin embargo, cómo se representa la variabilidad en estos métodos resulta crítico (ej.: qué primitivas se utilizan). En este contexto, el uso de patrones de modelado (soluciones reutilizables a un problema recurrente) resultan un camino prometedor. Por ejemplo, los patrones han sido probados como una solución eficaz para gestionar procesos de negocio individuales. El objetivo de esta tesis es mejorar el modelado de la variabilidad en las familias de procesos a través del uso de patrones de cambio. En primer lugar, hemos llevado a cabo un estudio sistemático con el fin de analizar las soluciones existentes que permiten gestionar la variabilidad en los procesos, así como el soporte que estas proporcionan. Así, hemos sido capaces de identificar y analizar cuál es el conjunto básico de primitivas específicas para representar la variabilidad. Además, basándonos en la evidencia empírica obtenida, hemos derivado el marco de evaluación VIVACE, el cual recoge las primitivas de variabilidad y un conjunto básico de características que favorecen la variabilidad en los procesos. El principal objetivo de VIVACE es conformar una completa caracterización de la variabilidad en los procesos de negocio. Asimismo, VIVACE permite evaluar las soluciones que gestionan la variabilidad en los procesos, así como seleccionar la solución que se ajuste mejor a sus necesidades. Finalmente, VIVACE puede ayudar a los ingenieros a gestionar PAISs con variabilidad. En segundo lugar, para facilitar el modelado de la variabilidad en las familias de procesos, basándonos en las primitivas identificadas, hemos definido un conjunto de 10 patrones de cambio y hemos mostrado cómo estos patrones pueden ser implementados. En particular, estos patrones ayudan al modelado y la evolución de familias de procesos y son capaces de garantizar la corrección de la propia familia. Para probar su efectividad y analizar su idoneidad, hemos aplicado estos patrones de cambio en un escenario real. En concreto, hemos llevado a cabo un caso de estudio con un estándar de seguridad con un alto nivel de variabilidad. Los resultados de este caso demuestran que la aplicación de nuestros patrones de cambio puede reducir el esfuerzo para el modelado de familias de procesos en un 34% y para la evolución de esos modelos en un 40%. Además, hemos analizado cómo los ingenieros aplican los patrones y cuáles son sus percepciones de esta aplicación. Como resultado, la mayoría de ellos encontró beneficios al aplicar los patrones. Además, no percibieron un aumento en el esfuerzo mental necesario para aplicarlos y estuvieron de acuerdo en la utilid[CA] La creixent adopció de sistemes d'informació dirigits per processos de negoci (PAIS) junt amb l'alta variabilitat en eixos processos, han donat lloc a la aparició de col·leccions de famílies de processos. Estes famílies es formen de un model de procés de negoci i les seues variants, les quals poden comprendre entre cents i milers de diferents formes de dur a terme eixe procés. Modelar la variabilitat dels processos en este context pot resultar molt difícil donat la grandària que aquestes famílies poden aconseguir. Motivats per este desafiament, s'han desenvolupat diverses solucions que permeten la gestió de la variabilitat en els processos de negoci. No obstant, amb aquestes solucions els enginyers que treballen amb PAIS han de crear i gestionar un a un tots els elements de les famílies de processos i assegurar ells mateixos la seua correcció. Això pot resultar tediós i propens a errors especialment quan les famílies es componen de cents o milers de variants. Per exemple, la variabilitat pot no quedar adequadament representada ja que els enginyers han de ser conscients de totes i cadascuna una de les variacions de totes les variants. Per quest motiu, son necessaris nous mètodes que permeten als enginyers de PAIS modelar la variabilitat dels processos de manera més explícita, sobretot a un nivell d'abstracció més alt del proporcionat per les solucions actuals. No obstant, com es representa la variabilitat en aquestos mètodes resulta crític (ex.: quines primitives s'utilitzen per a modelar la variabilitat en els processos). En aquest context, l'ús de patrons de modelatge (solucions reutilitzables a un problema recurrent) resulten un camí prometedor. Per exemple, els patrons han sigut provats com una solució eficaç per modelar i gestionar processos de negoci individuals. L'objectiu d'aquesta tesi 'es millorar el modelatge de la variabilitat en les famílies de processos a través de l'ús de patrons de canvi. En primer lloc, hem dut a terme un estudi sistemàtic per a analitzar les solucions existents per a gestionar la variabilitat en els processos, així com el suport que aquestes proporcionen. D'aquesta manera, som capaços d'identificar i analitzar quin 'es el conjunt bàsic de primitives específiques per a representar la variabilitat. A més, basant-nos en l'evidència empírica obtinguda, hem derivat el marc d'evacuació VIVACE, el qual arreplega les primitives de variabilitat i un conjunt bàsic de característiques que afavoreixen la variabilitat en els processos. Així mateix, VIVACE permet als enginyers de PAIS avaluar les solucions per a gestionar la variabilitat en els processos, així com seleccionar la solució que s'ajusta millor a les seues necessitats. Finalment, VIVACE també pot ajudar als enginyers a gestionar PAISs que donen suport a aquesta variabilitat. En segon lloc, per a facilitar el modelatge de la variabilitat en les famílies de processos, basant-nos en les primitives identificades, hem definit un conjunt de 10 patrons de canvi i hem mostrat com aquestos poden ser implementats. En particular, estos patrons ajuden al modelatge i l'evolució de famílies de processos i garanteixen la correcció de la pròpia família. Per a provar la seua efectivitat i analitzar la seua idoneïtat, hem aplicat els patrons de canvi en un escenari real. En particular, hem dut a terme un cas d'estudi amb un estàndard de seguretat amb un alt nivell de variabilitat. Els resultats de aquest cas demostren que l'aplicació dels nostres patrons de canvi poden reduir l'esforç per al modelatge de famílies de processos en un 34% i per a l'evolució de eixos models en un 40%. A més, hem analitzat com els enginyers de PAIS apliquen els patrons i quines son les seues percepcions d'esta aplicació. Com a resultat, la majoria d'ells va trobar beneficis al aplicar els patrons de canvi. A més, no van percebre un augment en l'esforç mental necessari per a aplicar-los i van estar d'acord en la utilitat i fAyora Esteras, C. (2015). Enhancing Variability Modeling in Process-Aware Information Systems through Change Patterns [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/58426TESI

Change Patterns for Process Families

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

An extensible product structure model for product lifecycle management in the make-to-order environment

This paper presents a product structure model with a semantic representation technique that make the product structure extensible for developing product lifecycle management (PLM) systems that is flexible for make-to-order environment. In the make-to-order business context, each product could have a number of variants with slightly different constitutions to fulfill different customer requirements. All the variants of a family have common characteristics and each variant has its specific features. A master-variant pattern is proposed for building the product structure model to explicitly represent common characteristics and specific features of individual variants. The model is capable of enforcing the consistency of a family structure and its variant structure, supporting multiple product views, and facilitating the business processes. A semantic representation technique is developed that enables entity attributes to be defined and entities to be categorized in a neutral and semantic format. As a result, entity attributes and entity categorization can be redefined easily with its configurable capability for different requirements of the PLM systems. An XML-based language is developed for semantically representing entities and entity categories. A prototype as a proof-of-concept system is presented to illustrate the capability of the proposed extensible product structure model

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. 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Modeling Business Process Variability

This master thesis presents research findings on business process variability modeling. Its main goal is to analyze inherent problems of business process variability and solve them simply, innovatively and effectively. To achieve this goal, process variability is defined by analyzing scientific literature, its main problems identified and is illustrated using a healthcare running example: process variability is classified into process variability within the domain space and over time. These two forms of process variability respectively lead to process variability modeling and process model evolution problems. After defining the main problems inherent to process variability, the focus of this research project is defined: solving process variability modeling problems. First current business process modeling languages are evaluated to assess the effectiveness of their respective modeling concepts when modeling process variability, using a newly created set of evaluation criteria and the healthcare running example. The following business process modeling languages are evaluated: Event driven process chains (EPC), the Business Process Modeling Notation (BPMN) and Configurable EPC (C-EPC). Business process variability modeling and Software product line engineering have similar problems. Therefore the variability modeling concepts developed by software product line engineering are analyzed. Feature diagrams and software configuration management are the main variability management concepts provided by software product line engineering. To apply these variability management concepts to model process variability meant combining them with existing business modeling languages. Riebisch feature diagrams are combined with C-EPC to form Feature-EPC. Applying software configuration management, meant merging Change Oriented Versioning with basic EPC to create COV-EPC, and merging the Proteus Configuration Language with basic EPC to design PCL-EPC. Finally these newly created business process modeling languages are also evaluated using the newly designed evaluation criteria and the healthcare running example. EPC or BPMN are not suited to model business process variability within the domain space. C-EPC provide explicit means to model business process variability, however the process models tend to get big very fast. Furthermore the syntax, the contextual constraints and the semantics of the configuration requirements and guidelines used to configure the C-EPC process models are unclear. Feature-EPC improve C-EPC with domain modeling capability and clearly defined configuration rules: their syntax, contextual constraints and semantics have been clearly defined using a context free grammar in Backus-Naur form. Furthermore, consistent combinations of features and configuration rules are ensured using respectively constraints and a conflict resolution algorithm. However, Feature-EPC and C-EPC suffer from the same weakness: large configurable process models. In COV-EPC and PCL-EPC the problem of large configurable process models is solved. COV-EPC ensures consistent combinations of options and configuration rules using respectively validities and a conflict resolution algorithm. PCL-EPC guarantees consistent combinations of process fragments by means of a PCL specification

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