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Identifying and Prioritizing Architectural Debt Through Architectural Smells: A Case Study in a Large Software Company

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Software Architecture (ECSA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 11048))

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Abstract

Architectural technical debt can have a huge impact on software maintainability and evolution. Hence, different architectural violations, detected as architectural smells, need to be identified and refactored. In this paper, we conducted a multiple case-study on several architectural smells detected in four industrial projects. We conducted an in-depth investigation with a questionnaire, interviews and thorough inspection of the code with the practitioners. We evaluated the negative impact of the technical debt detected by the architectural smells, their difficulty to be refactored and the usefulness of the detection tool. The results show that practitioners appreciated the help of automatic detection, and that they prioritize refactoring architectural debt that causes more negative impact despite the higher refactoring effort.

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Notes

  1. 1.

    https://neo4j.com/.

  2. 2.

    For space reason, it is available at https://drive.google.com/file/d/160TA9Q9jUIUpTBp-Wg7zu87elVa3y1qr/view?usp=sharing.

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Acknowledgements

The research leading to these results has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 712949 (TECNIOspring PLUS) and from the Agency for Business Competitiveness of the Government of Catalonia. We thank Chalmers University of Technology and University of Gothenburg for the support.

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Authors and Affiliations

  1. Università degli Studi di Milano-Bicocca, Milan, Italy

    Francesca Arcelli Fontana & Andrea Biaggi

  2. CA Technologies, Barcelona, Spain

    Antonio Martini

  3. University of Oslo, Oslo, Norway

    Antonio Martini

  4. Alten Italia, Milano, Italy

    Riccardo Roveda

Authors
  1. Antonio Martini
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  2. Francesca Arcelli Fontana
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  3. Andrea Biaggi
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  4. Riccardo Roveda
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Corresponding author

Correspondence to Francesca Arcelli Fontana .

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Editors and Affiliations

  1. King Juan Carlos University, Móstoles, Madrid, Spain

    Carlos E. Cuesta

  2. School of Computer Sciences, Carnegie Mellon University, Pittsburgh, PA, USA

    David Garlan

  3. Technical University of Madrid, Madrid, Spain

    Jennifer Pérez

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Martini, A., Fontana, F.A., Biaggi, A., Roveda, R. (2018). Identifying and Prioritizing Architectural Debt Through Architectural Smells: A Case Study in a Large Software Company. In: Cuesta, C., Garlan, D., Pérez, J. (eds) Software Architecture. ECSA 2018. Lecture Notes in Computer Science(), vol 11048. Springer, Cham. https://doi.org/10.1007/978-3-030-00761-4_21

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  • DOI: https://doi.org/10.1007/978-3-030-00761-4_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00760-7

  • Online ISBN: 978-3-030-00761-4

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