Interactive Visual Analytics for Efficient Maintenance of Model Transformations

Rentschler, Andreas; Noorshams, Qais; Happe, Jens; Reussner, Ralf

doi:10.1007/978-3-642-38883-5_14

Cited by 6 publications

(3 citation statements)

References 12 publications

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“…Like any other software, transformations change over time [23,27,30]. As changes to transformations can invalidate previously produced models, these changes need to be propagated to existing models.…”

Section: Introductionmentioning

confidence: 99%

From out-place transformation evolution to in-place model patching

Bergmayr

Troya

Wimmer

2014

Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering

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Model transformation is a key technique to automate software engineering tasks. Like any other software, transformations are not resilient to change. As changes to transformations can invalidate previously produced models, these changes need to be reflected on existing models. Currently, revised out-place transformations are re-executed entirely to achieve this co-evolution task. However, this induces an unnecessary overhead, particularly when computation-intensive transformations are marginally revised, and if existing models have undergone updates prior the re-execution, these updates get discarded in the newly produced models.To overcome this co-evolution challenge, our idea is to infer from evolved out-place transformations patch transformations that propagate changes to existing models by re-executing solely the affected parts based on an in-place execution strategy. Thereby, existing models are only updated by a patch instead of newly produced. In this paper, we present the conceptual foundation of our approach and report on its evaluation in a real-world case study.

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Section: Introductionmentioning

confidence: 99%

From out-place transformation evolution to in-place model patching

Bergmayr

Troya

Wimmer

2014

Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering

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“…However, maintaining and evolving all the elements involved may be difficult [14]. Different approaches should be applied for model evolution [32], metamodel evolution [18] or transformation evolution [25], and it is even more complex when severeal related elements must evolve consistently [9]. Moreover, adoption of MDE approaches has been slow due to organizational and cultural issues, as well as tool immaturity [21,36].…”

Section: Related Workmentioning

confidence: 99%

Using megamodeling to improve industrial adoption of complex MDE solutions

Bastarrica

Simmonds

Silvestre

2014

Proceedings of the 6th International Workshop on Modeling in Software Engineering

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Companies formalize their software processes as a way of organizing their development projects. As each project has its own requirements and objectives, a family of processes is required in practice, in order to ensure that each project is handled appropriately. This family may be a collection of predefined processes, but can also be automatically generated by tailoring a general process to a project's context which requires formalization and tool support to be successful. Model-driven engineering provides a formal framework for defining the models and transformations required for automated process tailoring, but various types of models must be specified and evolved, limiting the industrial adoption of this approach. To address this problem, in this paper we propose a megamodel for automated process tailoring. Megamodeling provides an integrating framework for modeling in the large, including the definition and evolution of all models and transformations required for tailoring while hiding complexity. We report the application of our approach to the software development process of Rhiscom, a small Chilean company.

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“…In additional to visualizing metrics, they can also visualize structure of a piece of code, which can again be performed statically, between projects, or over time. An example is the transformation analysis tool by Rentschler et al (2013b), a visualization tool to help developers reduce intramodule dependencies and increase development speed by displaying a visual of dependencies between transformation mappings. Similar visual treatment could be provided for some of the high-level architecture or transformation-local metrics from the QVTo quality model, including ''Small interfaces to other modules,'' ''Short function chains,'' and ''Interdependent functions near each other.''…”

Section: Leveraging the Model In Developer Toolingmentioning

confidence: 99%

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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Interactive Visual Analytics for Efficient Maintenance of Model Transformations

Cited by 6 publications

References 12 publications

From out-place transformation evolution to in-place model patching

From out-place transformation evolution to in-place model patching

Using megamodeling to improve industrial adoption of complex MDE solutions

Assessing and improving quality of QVTo model transformations

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