Model-Aware Software Engineering - A Knowledge-based Approach to Model-Driven Software Engineering

Buchmann, Robert Andrei; Cinpoeru, Mihai; Harkai, Alisa; Karagiannis, Dimitris

doi:10.5220/0006694102330240

Cited by 17 publications

(6 citation statements)

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“…Its key characteristic is that the developed software uses a model base at run-time as a complement to its more traditional database/data sources. Model queries (Buchmann et al, 2018) and service-based Volume 44 10.17705/1CAIS.04432 Paper 32…”

Section: Figure 2 the Omilab Digital Ecosystemmentioning

confidence: 99%

“…These mechanisms enrich the AMME framework with additional steps to achieve a full-fledged software development method (see Buchmann et al, 2018) or, if approached from a knowledge management perspective, a knowledge conversion cycle that supports the development of knowledge-driven digital products (Karagiannis, Buchmann, & Walch, 2017).…”

Section: Figure 6 the Enterknow Model-aware Software Engineering Promentioning

confidence: 99%

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An Open Platform for Modeling Method Conceptualization: The OMiLAB Digital Ecosystem

Bork¹,

Buchmann²,

Karagiannis³

et al. 2019

CAIS

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This paper motivates, describes, demonstrates in use, and evaluates the Open Models Laboratory (OMiLAB)-an open digital ecosystem designed to help one conceptualize and operationalize conceptual modeling methods. The OMiLAB ecosystem, which a generalized understanding of "model value" motivates, targets research and education stakeholders who fulfill various roles in a modeling method's lifecycle. While we have many reports on novel modeling methods and tools for various domains, we lack knowledge on conceptualizing such methods via a full-fledged dedicated open ecosystem and a methodology that facilitates entry points for novices and an open innovation space for experienced stakeholders. This gap continues due to the lack of an open process and platform for 1) conducting research in the field of modeling method design, 2) developing agile modeling tools and model-driven digital products, and 3) experimenting with and disseminating such methods and related prototypes. OMiLAB incorporates principles, practices, procedures, tools, and services required to address the issues above since it focuses on being the operational deployment for a conceptualization and operationalization process built on several pillars: 1) a granularly defined "modeling method" concept whose building blocks one can customize for the domain of choice, 2) an "agile modeling method engineering" framework that helps one quickly prototype modeling tools, 3) a model-aware "digital product design lab", and 4) dissemination channels for reaching a global community. In this paper, we demonstrate and evaluate the OMiLAB in research with two selected application cases for domain-and case-specific requirements. Besides these exemplary cases, OMiLAB has proven to effectively satisfy requirements that almost 50 modeling methods raise and, thus, to support researchers in designing novel modeling methods, developing tools, and disseminating outcomes. We also measured OMiLAB's educational impact.

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Section: Figure 2 the Omilab Digital Ecosystemmentioning

confidence: 99%

Section: Figure 6 the Enterknow Model-aware Software Engineering Promentioning

confidence: 99%

An Open Platform for Modeling Method Conceptualization: The OMiLAB Digital Ecosystem

Bork¹,

Buchmann²,

Karagiannis³

et al. 2019

CAIS

Self Cite

View full text Add to dashboard Cite

show abstract

“…The success of the proposed treatments manifests in the availability of publishable research results authored by master students and presented in prestigious conferencessee BIR 2019 [17], ENASE 2018 [29], ICEIS 2018 [30] CAISE 2018 workshops [25] and PoEM 2018 workshops [31]. This has been a premiere in the first author's institution and further inspires industry collaborations on model-driven engineering for which students have, for the first time, a holistic understanding of the nature of models and how they can drive the engineering of other types of artifacts even when models do not play the role of graphical documentation.…”

Section: Requirements and Treatmentsmentioning

confidence: 99%

Conceptual Modeling Education as a “Design Problem”

Buchmann

Ghiran

Döller

et al. 2019

CSIMQ

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This article frames Conceptual Modeling education as a design problem, in the sense of the Design Science research framework, motivated by student preconceptions and oversimplifications causing a gap between how the discipline is perceived at bachelor level and the holistic understanding of model value that is required for research work. The treatment to this design problem must comprise teaching approaches and artifacts capable of positioning Conceptual Modeling as a standalone discipline having a value proposition for any application domain, rather than a technique subordinated to other disciplines. The underpinning thesis is that modeling languages should be primarily understood as purposeful knowledge schemas that can be subjected to agile adaptations in support of model-driven systems or knowledge processes, by analogy to how a database schema is evolved in response to changing requirements of a data-driven system or data analytics needs. This thesis is supported by enablers provided by the Open Models Laboratory and the Agile Modeling Method Engineering frameworkresources that support the development of treatments to the design problem framed by the article.

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“…Recent research in model-driven engineering introduced two novel notions: (a) "technologyspecific" modeling languages, a kind of domain-specific modeling languages where, instead of domain concepts, the language must assimilate technology-specific constructs as first order modeling citizens [1] and (b) "model-aware software engineering" (MASE), a flavor of modeldriven engineering where models interact with running software through semantic technology [2].…”

Section: Introductionmentioning

confidence: 99%

“…Design Science [3] was engaged as a research method and MASE [2] as an engineering method, combining Agile Modeling Method Engineering (AMME) [4] (used for the implementation of the diagrammatic modeling tool) with Resource Description Framework (RDF) [5] as semantic bridge between the PHP development environment and the technologyspecific models.…”

Section: Introductionmentioning

confidence: 99%

Agile Development of PHP Websites: A Model-Aware Approach

Gog

2020

CSIMQ

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The Design Science research method was hereby employed to develop an artifact that demonstrates the experimental “model-aware” software engineering methodology in the context of PHP Web development – a “low code” development approach with code templates generated from technology-specific models. The proof-of-concept consists of two interacting components: a custom diagrammatic modeling environment and model-driven generated PHP pages. The interaction between the two components conforms the engineering method labelled as “Model-aware software engineering” (MASE) – a flavor of model-driven engineering recently introduced in research projects as a hybridization of the Agile Modeling Method Engineering (AMME) framework and the Resource Description Framework (RDF). The experimental MASE method is employed here to demonstrate its feasibility for the common Model-View-Controller (MVC) website development pattern, thus showing potential to support common Web development work.

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Model-Aware Software Engineering - A Knowledge-based Approach to Model-Driven Software Engineering

Cited by 17 publications

References 0 publications

An Open Platform for Modeling Method Conceptualization: The OMiLAB Digital Ecosystem

An Open Platform for Modeling Method Conceptualization: The OMiLAB Digital Ecosystem

Conceptual Modeling Education as a “Design Problem”

Agile Development of PHP Websites: A Model-Aware Approach

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