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A quality driven extension to the QVT-relations transformation language

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Computer Science - Research and Development

Abstract

An emerging approach to software development is Model Driven Software Development (MDSD). It shifts the focus from source code to models, aims at cost reduction, risk mitigation, and eases the engineering of complex applications. System models can be used in the early development stages to verify certain relevant properties, such as performance, before source code is available and problems become hard and costly to solve. The present status of Model Driven Engineering (MDE) is still far from this ideal situation. A well-known problem is feedback provisioning, which arises when different solutions for the same design problem exist. An approach for feedback provisioning automation leverages model transformations, which glue together models in an MDSD setting, encapsulate the design rationale, and promote knowledge reuse and solutions otherwise available only to experienced engineers. In this article we present QVTR2, our solution to the feedback problem. QVTR2 is an extension of the QVT-Relations language with constructs to express design alternatives, their impact on non-functional metrics, and how to evaluate them and guide the engineers in the selection of the most appropriate solution. We demonstrate the effectiveness of our solution by using the QVTR2 engine to perform a modified version of the standard UML-to-RDBMS transformation in the context of a real e-commerce application, and by showing how we can guide a non-expert engineer in the selection of a solution that satisfies given performance requirements.

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Notes

  1. From this point ahead, we will use interchangeably the terms alternative, solution and variant.

  2. More details are available later and on the QVTR2 website at http://code.google.com/p/qvtr2/.

  3. Publicly available on the QVTR2 website at http://code.google.com/p/qvtr2/.

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Acknowledgements

This research was partially founded by the European Commission, IDEAS-ERC Project 227977-SMScom and EU FP7 Q-ImPrESS project.

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Authors and Affiliations

  1. DeepSE Group–Dipartimento di Elettronica e Informazione, Politecnico di Milano, Piazza Leonardo Da Vinci, 32-20133, Milano, Italy

    Mauro Luigi Drago, Carlo Ghezzi & Raffaela Mirandola

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  1. Mauro Luigi Drago
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  2. Carlo Ghezzi
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  3. Raffaela Mirandola
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Correspondence to Mauro Luigi Drago.

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Drago, M.L., Ghezzi, C. & Mirandola, R. A quality driven extension to the QVT-relations transformation language. Comput Sci Res Dev 30, 1–20 (2015). https://doi.org/10.1007/s00450-011-0202-0

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