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Combining Automatic Variability Analysis Tools: An SPL Approach for Building a Framework for Composition

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Computational Science and Its Applications – ICCSA 2018 (ICCSA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10963))

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Abstract

The automatic analysis of variability models is an important research field included in variability management activities. In the context of software product lines, it includes a set of methods and techniques aimed at verifying the design of the variability models in order to avoid inconsistencies during variability definition, implementation, and derivations activities. There exist several tools and proposals implementing the basic activities involved in this analysis process. However, the large number of them makes difficult to find and select the most suitable tool/set of tools to be applied in a particular SPL development. Taking into account this problem, our work aims at developing a framework, built as a software product line, that allows developers to compose/build automatic analysis tools according to their specific needs. We illustrate the proposal through possible instantiations of the framework.

This work is partially supported by the UNComa project 04/F009 “Reuso de Software orientado a Dominios - Parte II” part of the program “Desarrollo de Software Basado en Reuso - Parte II”.

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Notes

  1. 1.

    www.sat4j.org/.

  2. 2.

    https://www.ifis.uni-luebeck.de/~moeller/racer/index.html.

  3. 3.

    Each approach contains a large number of proposals, which extend different aspects.

  4. 4.

    http://www.jessrules.com.

  5. 5.

    https://protege.stanford.edu/.

  6. 6.

    http://variamos.com/home/.

  7. 7.

    http://www.swi-prolog.org/.

  8. 8.

    We use the OVM graphical notation for these variability models.

  9. 9.

    https://www.sei.cmu.edu/productlines/frame_report/all_three.htm.

  10. 10.

    https://angular.io/.

  11. 11.

    http://expressjs.com.

  12. 12.

    https://www.mongodb.com.

  13. 13.

    http://www.featureide.com/.

  14. 14.

    https://sse.uni-due.de/en/research/projects/varmod-prime/.

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Authors and Affiliations

  1. GIISCo Research Group, Faculty of Informatics, UNComa University, Neuquen, Argentina

    Agustina Buccella, Matias Pol’la, Esteban Ruiz de Galarreta & Alejandra Cechich

  2. Consejo Nacional de Investigaciones Científicas y Técnicas - CONICET, Buenos Aires, Argentina

    Agustina Buccella & Matias Pol’la

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Correspondence to Agustina Buccella .

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  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. Saint Petersburg State University, Saint Petersburg, Russia

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  5. Polytechnic University of Bari, Bari, Italy

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  6. University of Minho, Braga, Portugal

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  7. Monash University, Clayton, Victoria, Australia

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  8. Kyushu Sangyo University, Fukuoka shi, Fukuoka, Japan

    Bernady O. Apduhan

  9. Politecnico di Bari, Bari, Italy

    Eufemia Tarantino

  10. Myongji University, Yongin, Korea (Republic of)

    Yeonseung Ryu

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Buccella, A., Pol’la, M., de Galarreta, E.R., Cechich, A. (2018). Combining Automatic Variability Analysis Tools: An SPL Approach for Building a Framework for Composition. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2018. ICCSA 2018. Lecture Notes in Computer Science(), vol 10963. Springer, Cham. https://doi.org/10.1007/978-3-319-95171-3_34

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