1,437 research outputs found

    Refactoring Process Models in Large Process Repositories.

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    With the increasing adoption of process-aware information systems (PAIS), large process model repositories have emerged. Over time respective models have to be re-aligned to the real-world business processes through customization or adaptation. This bears the risk that model redundancies are introduced and complexity is increased. If no continuous investment is made in keeping models simple, changes are becoming increasingly costly and error-prone. Though refactoring techniques are widely used in software engineering to address related problems, this does not yet constitute state-of-the art in business process management. Process designers either have to refactor process models by hand or cannot apply respective techniques at all. This paper proposes a set of behaviour-preserving techniques for refactoring large process repositories. This enables process designers to eectively deal with model complexity by making process models better understandable and easier to maintain

    Keeping the Cost of Process Change Low through Refactoring

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    With the increasing adoption of process-aware information systems (PAIS) large process model repositories have emerged. Over time respective models have to be re-aligned to the real world business processes through customization or adaptation. This bears the risk that model redundancies are introduced and complexity is increased. If no continuous investment is made in keeping models simple, changes are becoming increasingly costly and error-prone. Although refactoring techniques are widely used in software engineering to address related problems, this does not yet constitute state-of-the art in business process management. Consequently, process designers either have to refactor process models by hand or can not apply respective techniques at all. In this paper we propose a set of techniques for refactoring large process repositories, which are behaviour-preserving. The proposed refactorings enable process designers to effectively deal with model complexity by making process models easier to change, less error-prone and better understandable

    What to Fix? Distinguishing between design and non-design rules in automated tools

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    Technical debt---design shortcuts taken to optimize for delivery speed---is a critical part of long-term software costs. Consequently, automatically detecting technical debt is a high priority for software practitioners. Software quality tool vendors have responded to this need by positioning their tools to detect and manage technical debt. While these tools bundle a number of rules, it is hard for users to understand which rules identify design issues, as opposed to syntactic quality. This is important, since previous studies have revealed the most significant technical debt is related to design issues. Other research has focused on comparing these tools on open source projects, but these comparisons have not looked at whether the rules were relevant to design. We conducted an empirical study using a structured categorization approach, and manually classify 466 software quality rules from three industry tools---CAST, SonarQube, and NDepend. We found that most of these rules were easily labeled as either not design (55%) or design (19%). The remainder (26%) resulted in disagreements among the labelers. Our results are a first step in formalizing a definition of a design rule, in order to support automatic detection.Comment: Long version of accepted short paper at International Conference on Software Architecture 2017 (Gothenburg, SE

    A Longitudinal Study of Identifying and Paying Down Architectural Debt

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    Architectural debt is a form of technical debt that derives from the gap between the architectural design of the system as it "should be" compared to "as it is". We measured architecture debt in two ways: 1) in terms of system-wide coupling measures, and 2) in terms of the number and severity of architectural flaws. In recent work it was shown that the amount of architectural debt has a huge impact on software maintainability and evolution. Consequently, detecting and reducing the debt is expected to make software more amenable to change. This paper reports on a longitudinal study of a healthcare communications product created by Brightsquid Secure Communications Corp. This start-up company is facing the typical trade-off problem of desiring responsiveness to change requests, but wanting to avoid the ever-increasing effort that the accumulation of quick-and-dirty changes eventually incurs. In the first stage of the study, we analyzed the status of the "before" system, which indicated the impacts of change requests. This initial study motivated a more in-depth analysis of architectural debt. The results of this analysis were used to motivate a comprehensive refactoring of the software system. The third phase of the study was a follow-on architectural debt analysis which quantified the improvements made. Using this quantitative evidence, augmented by qualitative evidence gathered from in-depth interviews with Brightsquid's architects, we present lessons learned about the costs and benefits of paying down architecture debt in practice.Comment: Submitted to ICSE-SEIP 201

    Äriprotsessimudelite ühildamine

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    Väitekirja elektrooniline versioon ei sisalda publikatsioone.Ettevõtted, kellel on aastatepikkune kogemus äriprotsesside haldamises, omavad sageli protsesside repositooriumeid, mis võivad endas sisaldada sadu või isegi tuhandeid äriprotsessimudeleid. Need mudelid pärinevad erinevatest allikatest ja need on loonud ning neid on muutnud erinevad osapooled, kellel on erinevad modelleerimise oskused ning praktikad. üheks sagedaseks praktikaks on uute mudelite loomine, kasutades olemasolevaid mudeleid, kopeerides neist fragmente ning neid seejärel muutes. See omakorda loob olukorra, kus protsessimudelite repositoorium sisaldab mudeleid, milles on identseid mudeli fragmente, mis viitavad samale alamprotsessile. Kui sellised fragmendid jätta konsolideerimata, siis võib see põhjustada repositooriumis ebakõlasid -- üks ja sama alamprotsess võib olla erinevates protsessides erinevalt kirjeldatud. Sageli on ettevõtetel mudelid, millel on sarnased eesmärgid, kuid mis on mõeldud erinevate klientide, toodete, äriüksuste või geograafiliste regioonide jaoks. Näiteks on äriprotsessid kodukindlustuse ja autokindlustuse jaoks sama ärilise eesmärgiga. Loomulikult sisaldavad nende protsesside mudelid mitmeid identseid alamfragmente (nagu näiteks poliisi andmete kontrollimine), samas on need protsessid mitmes punktis erinevad. Nende protsesside eraldi haldamine on ebaefektiivne ning tekitab liiasusi. Doktoritöös otsisime vastust küsimusele: kuidas identifitseerida protsessimudelite repositooriumis korduvaid mudelite fragmente, ning üldisemalt -- kuidas leida ning konsolideerida sarnasusi suurtes äriprotsessimudelite repositooriumites? Doktoritöös on sisse toodud kaks üksteist täiendavat meetodit äriprotsessimudelite konsolideerimiseks, täpsemalt protsessimudelite ühildamine üheks mudeliks ning mudelifragmentide ekstraktimine. Esimene neist võtab sisendiks kaks või enam protsessimudelit ning konstrueerib neist ühe konsolideeritud protsessimudeli, mis sisaldab kõikide sisendmudelite käitumist. Selline lähenemine võimaldab analüütikutel hallata korraga tervet perekonda sarnaseid mudeleid ning neid muuta sünkroniseeritud viisil. Teine lähenemine, alamprotsesside ekstraktimine, sisaldab endas sagedasti esinevate fragmentide identifitseerimist (protsessimudelites kloonide leidmist) ning nende kapseldamist alamprotsessideks

    Applying MDE tools to defining domain specific languages for model management

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    In the model driven engineering (MDE), modeling languages play a central role. They range from the most generic languages such as UML, to more individual ones, called domain-specific modeling languages (DSML). These languages are used to create and manage models and must accompany them throughout their life cycle and evolution. In this paper we propose a domain-specific language for model management, to facilitate the user's task, developed with techniques and tools used in the MDE paradigm.Fil: Pérez, Gabriela. Universidad Nacional de la Plata. Facultad de Informática. Laboratorio de Investigación y Formación en Informática Avanzada; ArgentinaFil: Irazábal, Jerónimo. Universidad Nacional de la Plata. Facultad de Informática. Laboratorio de Investigación y Formación en Informática Avanzada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Pons, Claudia Fabiana. Universidad Nacional de la Plata. Facultad de Informática. Laboratorio de Investigación y Formación en Informática Avanzada; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; ArgentinaFil: Giandini, Roxana Silvia. Universidad Nacional de la Plata. Facultad de Informática. Laboratorio de Investigación y Formación en Informática Avanzada; Argentin

    25 Desafíos de la Modelación de Procesos Semánticos

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    Process modeling has become an essential part of many organizations for documenting, analyzing and redesigning their business operations and to support them with suitable information systems. In order to serve this purpose, it is important for process models to be well grounded in for- mal and precise semantics. While behavioural semantics of process models are well understood, there is a considerable gap of research into the semantic aspects of their text labels and natural lan- guage descriptions. The aim of this paper is to make this research gap more transparent. To this end, we clarify the role of textual content in process models and the challenges that are associated with the interpretation, analysis, and improvement of their natural language parts. More specifically, we discuss particular use cases of semantic process modeling to identify 25 challenges. For each cha- llenge, we identify prior research and discuss directions for addressing themEl modelado de procesos se ha convertido en una parte esencial de muchas organizaciones para documentar, analizar, y rediseñar sus operaciones de negocios y apoyarlos con información apropiada. Para cumplir este fin, es importante para estos que estén completos dentro de una semántica formal y precisa. Mientras la semántica del comportamiento del modelado de procesos se entiende bien, hay una considerable laguna en la investigación entre los aspectos semánticos de sus rótulos textuales, y las descripciones en lenguaje natural. El objetivo de este artículo es hacer esta laguna en la investigación más transparente. Con este fin, clarificamos el papel del contenido textual en los modelos de proceso, y los retos relacionados con la interpretación, el análisis, y desarrollo de sus partes en lenguaje natural. De forma más específica, debatimos los casos particulares del uso del modelado de procesos semánticos para identificar 25 retos. Para cada reto, identificamos antes de la investigación y debatimos las direcciones para dirigirnos a ellos

    Abstraction, Visualization, and Evolution of Process Models

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    The increasing adoption of process orientation in companies and organizations has resulted in large process model collections. Each process model of such a collection may comprise dozens or hundreds of elements and captures various perspectives of a business process, i.e., organizational, functional, control, resource, or data perspective. Domain experts having only limited process modeling knowledge, however, hardly comprehend such large and complex process models. Therefore, they demand for a customized (i.e., personalized) view on business processes enabling them to optimize and evolve process models effectively. This thesis contributes the proView framework to systematically create and update process views (i.e., abstractions) on process models and business processes respectively. More precisely, process views abstract large process models by hiding or combining process information. As a result, they provide an abstracted, but personalized representation of process information to domain experts. In particular, updates of a process view are supported, which are then propagated to the related process model as well as associated process views. Thereby, up-to-dateness and consistency of all process views defined on any process model can be always ensured. Finally, proView preserves the behaviour and correctness of a process model. Process abstractions realized by views are still not sufficient to assist domain experts in comprehending and evolving process models. Thus, additional process visualizations are introduced that provide text-based, form-based, and hierarchical representations of process models. Particularly, these process visualizations allow for view-based process abstractions and updates as well. Finally, process interaction concepts are introduced enabling domain experts to create and evolve process models on touch-enabled devices. This facilitates the documentation of process models in workshops or while interviewing process participants at their workplace. Altogether, proView enables domain experts to interact with large and complex process models as well as to evolve them over time, based on process model abstractions, additional process visualizations, and process interaction concepts. The framework is implemented in a proof-ofconcept prototype and validated through experiments and case studies
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