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Feature Level Complexity and Coupling Analysis in 4GL Systems

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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 10964))

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Abstract

Product metrics are widely used in the maintenance and evolution phase of software development to advise the development team about software quality. Although most of these metrics are defined for mainstream languages, several of them were adapted to fourth generation languages (4GL) as well. Usual concepts like size, complexity and coupling need to be re-interpreted and adapted to program elements defined by these languages. In this paper we take a further step in this process to address product line development in 4GL. Adopting product line architecture is a necessary step to handle challenges of a growing number of similar product variants. The product line adoption process itself is a tedious task where features of the product variants play crucial role. Features represent a higher level of abstraction that are cross-cutting to program elements of 4GL applications. We propose a set of metrics related to features by linking existing program elements to metrics and by relating features with each other. The focus of this study is on complexity and coupling metrics. We provide a metrics based analysis of several variants of a large scale industrial product line written in the Magic XPA 4GL language.

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Notes

  1. 1.

    http://www.raincode.com/fglroadmap.html.

  2. 2.

    http://www.magic-optimizer.com/.

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Acknowledgements

The project has been supported by the European Union, co-financed by the European Social Fund (EFOP-3.6.3-VEKOP-16-2017-00002). We acknowledge the help of Magic experts of the SZEGED Software Llc.

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Authors and Affiliations

  1. Department of Software Engineering, University of Szeged, Szeged, Hungary

    András Kicsi, Viktor Csuvik, László Vidács, Árpád Beszédes & Tibor Gyimóthy

  2. MTA-SZTE Research Group on Artificial Intelligence, University of Szeged, Szeged, Hungary

    László Vidács & Tibor Gyimóthy

Authors
  1. András Kicsi
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  2. Viktor Csuvik
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  3. László Vidács
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  4. Árpád Beszédes
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  5. Tibor Gyimóthy
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Correspondence to András Kicsi .

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Editors and Affiliations

  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

    Elena Stankova

  5. Polytechnic University of Bari, Bari, Italy

    Carmelo M. Torre

  6. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  7. Monash University, Clayton, Victoria, Australia

    David Taniar

  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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Kicsi, A., Csuvik, V., Vidács, L., Beszédes, Á., Gyimóthy, T. (2018). Feature Level Complexity and Coupling Analysis in 4GL Systems. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2018. ICCSA 2018. Lecture Notes in Computer Science(), vol 10964. Springer, Cham. https://doi.org/10.1007/978-3-319-95174-4_35

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  • DOI: https://doi.org/10.1007/978-3-319-95174-4_35

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