A Bottom-Up Quality Model for QVTo

Gerpheide, CM Christine; Schiffelers, R.R.H.; Serebrenik, Alexander

doi:10.1109/quatic.2014.18

Cited by 5 publications

(4 citation statements)

References 26 publications

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“…This paper directly extends the research on the QVTo quality model presented by Gerpheide et al (2014aGerpheide et al ( , (2014b. It does this primarily by leveraging the QVTo quality model to identify and develop tooling that directly helps practitioners develop high-quality QVTo transformations.…”

Section: Related Worksupporting

confidence: 74%

“…It does this primarily by leveraging the QVTo quality model to identify and develop tooling that directly helps practitioners develop high-quality QVTo transformations. In addition to presenting tooling, an elaboration on the approach to building the quality model, additional insights in evaluating the model, and a more in-depth look at the properties of the quality model itself were also provided in this paper in comparison to Gerpheide et al (2014aGerpheide et al ( , (2014b.…”

Section: Related Workmentioning

confidence: 99%

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Assessing and improving quality of QVTo model transformations

2015

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We investigate quality improvement in QVT operational mappings (QVTo) model transformations, one of the languages defined in the OMG standard on model-tomodel transformations. Two research questions are addressed. First, how can we assess quality of QVTo model transformations? Second, how can we develop higher-quality QVTo transformations? To address the first question, we utilize a bottom-up approach, starting with a broad exploratory study including QVTo expert interviews, a review of existing material, and introspection. We then formalize QVTo transformation quality into a QVTo quality model. The quality model is validated through a survey of a broader group of QVTo developers. We find that although many quality properties recognized as important for QVTo do have counterparts in general purpose languages, a number of them are specific to QVTo or model transformation languages. To address the second research question, we leverage the quality model to identify developer support tooling for QVTo. We then implemented and evaluated one of the tools, namely a code test coverage tool. In designing the tool, code coverage criteria for QVTo model transformations are also identified. The primary contributions of this paper are a QVTo quality model relevant to QVTo practitioners and an open-source code coverage tool already usable by QVTo transformation developers. Secondary contributions are a bottom-up approach to building a quality model, a validation approach leveraging developer perceptions to evaluate quality properties, code test coverage criteria for QVTo, and numerous directions for future research and tooling related to QVTo quality.

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Section: Related Worksupporting

confidence: 74%

Section: Related Workmentioning

confidence: 99%

Assessing and improving quality of QVTo model transformations

2015

Self Cite

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“…Several of these studies of either type have been conducted in the MDE domain and related fields. Modelling languages were investigated with a focus on the Systems Modeling Language (SysML) language (Wolny et al 2020), the QVT Operational (QVTo) standard (Gerpheide et al 2014(Gerpheide et al , 2016, and the application of modelling in Industry 4.0 (Wortmann et al 2020(Wortmann et al , 2017. Further MDE-related work investigates literature on models at runtime (Szvetits & Zdun 2016), software testing process models (Vukovic et al 2018), articles that appeared in the Journal of Software and Systems Modelling (Gray & Rumpe 2016), and quality in MDE (Goulão et al 2016).…”

Section: Related Workmentioning

confidence: 99%

Tolerance in Model-Driven Engineering: A Systematic Literature Review with Model-Driven Tool Support

Weidmann¹,

Kannan²,

Anjorin³

2021

Preprint

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Managing models in a consistent manner is an important task in the field of Model-Driven Engineering (MDE).Although restoring and maintaining consistency is desired in general, recent work has pointed out that always strictly enforcing consistency at any point of time is often not feasible in real-world scenarios, and sometimes even contrary to what a user expects from a trustworthy MDE tool. The challenge of tolerating inconsistencies has been discussed from different viewpoints within and outside the modelling community, but there exists no structured overview of existing and current work in this regard.In this paper, we provide such an overview to help join forces tackling the unresolved problems of tolerating inconsistencies in MDE. We follow the standard process of a Systematic Literature Review (SLR) to point out what tolerance means, how it relates to uncertainty, which examples for tolerant software systems have already been discussed, and which benefits and drawbacks tolerating inconsistencies entails. Furthermore, we propose a tool-chain that helps conducting SLRs in computer science and also eases the reproduction of results. Relevant meta-data of the collected sources is uniformly described in a textual modelling language and exported to the graph database Neo4j to query aggregated information.

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“…A significant amount of empirical evidence on the quality aspects of models (Falleri et al 2008;Vanderose and Habra 2008;Oliveira et al 2008), modelling languages, i.e., metamodels, (Karsai et al 2008), modelling tools (Bastarrica et al 2007), and transformations on models (Insfran et al 2008;Pilgrim 2008;Mohagheghi and Dehlen 2007;Gerpheide et al 2014) has been collected. Several quality models were proposed for models (Mohagheghi and Dehlen 2008;Lange and Chaudron 2005;Malik and Kumar 2009;Garcia Frey et al 2011) defining a diverse, usually ISO/IEC 9126 compliant, set of characteristics applicable to models (Mohagheghi et al 2009b).…”

Section: Related Workmentioning

confidence: 99%

Measuring the complexity of domain-specific languages developed using MDD

Slivnik

2015

Software Qual J

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The standard ISO/IEC 25010 (SQuaRE) defines appropriateness as one of the three components of functional suitability, the other two components being completeness and correctness. As users of domain-specific language (DSL) are quite often domain experts with limited programming skills, a DSL might be considered appropriate if the resulting domain-specific programs do not contain an excessive amount of nondomainrelated programming elements. This paper describes a metric for measuring the appropriateness of DSLs that are developed using model-driven development (MDD), its evaluation and use. The metric measures the depth of the deepest domain-specific command within abstract syntax trees generated by a DSL. It is aimed at being used during the development of a new DSL and for comparing different DSLs defined over the same domain. It is assumed that during MDD, the metamodel describes the domain-independent part of the DSL, while the model supplies the domain-specific part. This resembles the implementation of DSLs using existing metaprogramming tools that provide off-the-shelf implementations of programming constructs but require manual implementation of the domain-specific language elements.

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A Bottom-Up Quality Model for QVTo

Cited by 5 publications

References 26 publications

Assessing and improving quality of QVTo model transformations

Assessing and improving quality of QVTo model transformations

Tolerance in Model-Driven Engineering: A Systematic Literature Review with Model-Driven Tool Support

Measuring the complexity of domain-specific languages developed using MDD

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