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International Conference on Evaluation of Novel Approaches to Software Engineering

ENASE 2016: Evaluation of Novel Approaches to Software Engineering pp 66–88Cite as

Quantitative and Qualitative Empirical Analysis of Three Feature Modeling Tools

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 703))

Abstract

During the last couple of decades, feature modeling tools have played a significant role in the improvement of software productivity and quality by assisting tasks in software product line (SPL). SPL decomposes a large-scale software system in terms of their functionalities. The goal of the decomposition is to create well-structured individual software systems that can meet different users’ requirements. Thus, feature modeling tools provides means to manage the inter-dependencies among reusable common and variable functionalities, called features. There are several tools to support variability management by modeling features in SPL. The variety of tools in the current literature makes it difficult to understand what kinds of tasks are supported and how much effort can be reduced by using these tools. In this paper, we present the results of an empirical study aiming to support SPL engineers choosing the feature modeling tool that best fits their needs. This empirical study compares and analyzes three tools, namely SPLOT, FeatureIDE , and pure::variants . These tools are analyzed based on data from 119 participants. Each participant used one tool for typical feature modeling tasks, such as create a model, update a model, automated analysis of the model, and product configuration. Finally, analysis concerning the perceived ease of use, usefulness, effectiveness, and efficiency are presented.

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Notes

  1. 1.

    http://dl.acm.org/.

  2. 2.

    http://ieeexplore.ieee.org/.

  3. 3.

    http://link.springer.com/.

  4. 4.

    http://www.pure-systems.com/pure_variants.49.0.html.

  5. 5.

    http://www.splot-research.org.

  6. 6.

    http://featureide.cs.ovgu.de.

  7. 7.

    Federal University of Lavras.

  8. 8.

    Federal University of Minas Gerais.

  9. 9.

    Federal University of Juíz de Fora.

  10. 10.

    Pontifical Catholic University of Rio de Janeiro.

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Acknowledgements

This work was partially supported by CNPq (grant 202368/2014-9). We are grateful to the reviewers who contributed significantly to the improvement of the paper.

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Authors and Affiliations

  1. Otto-von-Guericke-University Magdeburg (OvGU), Magdeburg, Germany

    Juliana Alves Pereira & Gunter Saake

  2. Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil

    Kattiana Constantino & Eduardo Figueiredo

Authors
  1. Juliana Alves Pereira
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  2. Kattiana Constantino
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  3. Eduardo Figueiredo
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  4. Gunter Saake
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Corresponding author

Correspondence to Juliana Alves Pereira .

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Editors and Affiliations

  1. Wrocław University of Economics, Wrocław, Poland

    Leszek A. Maciaszek

  2. INSTICC and Instituto Politécnico de Setúbal, Setúbal, Portugal

    Joaquim Filipe

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Pereira, J.A., Constantino, K., Figueiredo, E., Saake, G. (2016). Quantitative and Qualitative Empirical Analysis of Three Feature Modeling Tools. In: Maciaszek, L., Filipe, J. (eds) Evaluation of Novel Approaches to Software Engineering. ENASE 2016. Communications in Computer and Information Science, vol 703. Springer, Cham. https://doi.org/10.1007/978-3-319-56390-9_4

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  • DOI: https://doi.org/10.1007/978-3-319-56390-9_4

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