MDE Adoption in Industry: Challenges and Success Criteria

Mohagheghi, Parastoo; Fernández, Miguel A.; Martell, Juan A.; Fritzsche, Mathias; Gilani, Wasif

doi:10.1007/978-3-642-01648-6_6

Cited by 49 publications

(22 citation statements)

References 5 publications

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“…However, for the industrial context, specialized websites (grey literature 12 ) make significant contributions to the quality from a practitioners' perspective. We found 49 industrial MDE Quality evidence in industry MDE Quality evidence in academic & research Industrial issue 01 (Vara and Marcos, 2012;Cuadrado et al, 2014;Hutchinson et al, 2014;Bertrand Portier, 2009;Haan, 2008;Whittle et al, 2014;Dubray, 2011;Linders, 2015;Tone, 2010;Finnie, 2015;Klinke, 2008;Vallecillo, 2014;Hebig and Bendraou, 2014;Brown, 2009;DenHaan, 2009DenHaan, , 2011bPierson, 2007;Cabot, 2009;Brambilla, 2016;OMG, 2016;Mohagheghi et al, 2009b;Igarza et al, 2012;Clark and Muller, 2012;Whittle et al, 2015;Aranda et al, 2012;Baker et al, 2005;Whittle et al, 2013;Cuadrado et al, 2014;Hoang, 2012;Platania, 2016;Fournier, 2008) (Agner et al, 2013;Panach et al, 2015a;Davies et al, 2006;Mussbacher et al, 2014;Quintero and Muñoz, 2011;Quintero et al, 2012;Poruban et al, 2014;Bruel et al, 2015;…”

Section: Findings In the Literature Review Of Mismatchmentioning

confidence: 86%

“…This issue leads to problems with the followings: customization, tailoring, and interoperability among modelling tools (Burden et al, 2014) (Mohagheghi et al, 2013b), management of traceability with several tools (Mohagheghi et al, 2013b), the high level of expertise and effort required to develop a MDE tool (Burden et al, 2014) (Mohagheghi et al, 2013b), tool integration (Baker et al, 2005) (Burden et al, 2014) (Mohagheghi and Dehlen, 2008b) (Mohagheghi et al, 2013a), the dissatisfaction of MDE practicioners with the available tools (Tomassetti et al, 2012), the lack of technological maturity of the tools (Mohagheghi et al, 2013a), the scaling of the tools to large system development (Mohagheghi and Dehlen, 2008b), poor user experience (Mohagheghi et al, 2009b), too many dependencies for adopting MDE tools (Whittle et al, 2013), and poor performance (Baker et al, 2005).…”

Section: Tools As a Way To Increase Complexitymentioning

confidence: 99%

“…Other roadmaps as presented in (Kolovos et al, 2013;Mohagheghi et al, 2009b;Rios et al, 2006;Vallecillo, 2010) address specific concerns about MDE applicability, with informal considerations about its the adoption in real scenarios, and lack of relation to any IS foundations. These quality issues that we have described in Section 3 show a gap between the real application of MDE and its foundational principles.…”

Section: Open Challenges In the Evaluation Of The Quality Of Modellinmentioning

confidence: 99%

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Considerations about quality in model-driven engineering

et al. 2016

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Giraldo-Velásquez, FD.; España Cubillo, S.; Pastor López, O.; Giraldo, WJ. (2016). Considerations about quality in model-driven engineering. Software Quality Journal. 1-66. doi:10.1007/s11219-016-9350-6. Considerations about quality in model-driven engineeringCurrent state and challenges.Fáber D. Giraldo · Sergio España · Oscar Pastor · William J. GiraldoReceived: date / Accepted: date Abstract The virtue of quality is not itself a subject; it depends on a subject. In the software engineering field, quality means good software products that meet customer expectations, constraints, and requirements. Despite the numerous approaches, methods, descriptive models and tools, that have been developed, a level of consensus has been reached by software practitioners. However, in the modeldriven engineering (MDE) field, which has emerged from software engineering paradigms, quality continues to be a great challenge since the subject is not fully defined. The use of models alone is not enough to manage all of the quality issues at the modelling language level.In this work, we present the current state and some relevant considerations regarding quality in MDE, by identifying current categories in quality conception and by highlighting quality issues in real applications of the model-driven initiatives.We identified sixteen categories in the definition of quality in MDE. From this identification, by applying an adaptive sampling approach, we discovered the five most influential authors for the works that propose definitions of quality. These include (in order): the OMG standards (e.g., MDA, UML, MOF, OCL, SysML), the ISO standards for software quality models (e.g., 9126 and 25000), Krogstie, Lindland, and Moody. We also discovered families of works about quality, i.e., works that belong to the same author or topic.Seventy-three works were found with evidence of the mismatch between the academic/research field of quality evaluation of modelling languages and actual MDE practice in industry. We demonstrate that this field does not currently solve quality issues reported in industrial scenarios. The evidence of the mismatch was grouped in eight categories, four for academic/research evidence and four for industrial reports. These categories were detected based on the scope proposed in each one of the academic/research works and from the questions and issues raised by real practitioners.We then proposed a scenario to illustrate quality issues in a real information system project in which multiple modelling languages were used. For the evaluation of the quality of this MDE scenario, we chose one of the most cited and influential quality frameworks; it was detected from the information obtained in the identification of the categories about quality definition for MDE. We demonstrated that the selected framework falls short in addressing the quality issues. Finally, based on the findings, we derive eight challenges for quality evaluation in MDE projects that current quality initiatives do not address sufficiently.

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Section: Findings In the Literature Review Of Mismatchmentioning

confidence: 86%

Section: Tools As a Way To Increase Complexitymentioning

confidence: 99%

Section: Open Challenges In the Evaluation Of The Quality Of Modellinmentioning

confidence: 99%

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Considerations about quality in model-driven engineering

et al. 2016

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“…Their findings suggest that model-based approaches were useful for investigating some problems of complex systems, although the methodology and tools were immature and not generally perceived as easy to use. MDE experiences within Telefonica [34] and SAP are described in [32]. The common challenges faced by both companies are the skill set or training in MDE (meta-modelling, domain specific languages) required by developers (domain experts) and the lack of tool support.…”

Section: Tdl Modellingmentioning

confidence: 99%

Model-based tool support for Tactical Data Links: an experience report from the defence domain

et al. 2015

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The Tactical Data Link (TDL) allows the exchange of information between cooperating platforms as part of an integrated Command and Control (C 2 ) system. Information exchange is facilitated by adherence to a complex, message-based protocol defined by document-centric standards. In this paper we report on a recent body of work investigating migration from a document-centric to a model-centric approach within the context of the TDL domain, motivated by a desire to achieve a positive Return on Investment (RoI). The model-centric approach makes use of the Epsilon technology stack and provides a significant improvement to both the level of abstraction and rigour of the network design. It is checkable by a machine and, by virtue of an MDA-like approach to the separation of domains and model transformation between domains, is open to integration with other models to support more complex workflows, such as by providing the results of interoperability analyses in human-readable domain-specific reports conforming to an accepted standard.

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“…Other roadmaps as presented in (Kolovos et al, 2013;Mohagheghi et al, 2009c;Rios et al, 2006;Vallecillo, 2010) address specific concerns about MDE applicability, with informal considerations about its the adoption in real scenarios, and lack of relation to any IS foundations. These quality issues that we have described in Section 2.3 show a gap between the real application of MDE and its foundational principles.…”

mentioning

confidence: 99%

A framework for evaluating the quality of modelling languages in MDE environments A framework for evaluating the quality of modelling languages in MDE environments

Velásquez¹,

Danilo²

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MDE Adoption in Industry: Challenges and Success Criteria

Cited by 49 publications

References 5 publications

Considerations about quality in model-driven engineering

Considerations about quality in model-driven engineering

Model-based tool support for Tactical Data Links: an experience report from the defence domain

A framework for evaluating the quality of modelling languages in MDE environments A framework for evaluating the quality of modelling languages in MDE environments

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