Detection Strategies for Modularity Anomalies: An Evaluation with Software Product Lines

  • Eduardo Fernandes
  • Priscila Souza
  • Kecia Ferreira
  • Mariza Bigonha
  • Eduardo Figueiredo
Conference paper
First Online:
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 558)

Abstract

A Software Product Line (SPL) is a configurable set of systems that share common and varying features. SPL requires a satisfactory code modularity for effective use. Therefore, modularity anomalies make software reuse difficult. By detecting and solving an anomaly, we may increase the software quality and ease reuse. Different detection strategies support the identification of modularity anomalies. However, we lack an investigation of their effectiveness in the SPL context. In this paper, after an evaluation of existing strategies, we compared four strategies from the literature for two modularity anomalies that affect SPLs: God Class and God Method. In addition, we proposed two novel detection strategies and compared them with the existing ones, using three SPLs. As a result, existing strategies showed high recall but low precision. In addition, when compared to detection strategies from the literature, our strategies presented comparable or higher recall and precision rates for some SPLs.

Keywords

Detection Strategies Modularity Anomalies Software Product Lines 
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Notes

Acknowledgements

This work was partially supported by CAPES, CNPq (grant 424340/2016-0), and FAPEMIG (grant PPM-00382-14).

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Eduardo Fernandes
    • 1
  • Priscila Souza
    • 1
  • Kecia Ferreira
    • 2
  • Mariza Bigonha
    • 1
  • Eduardo Figueiredo
    • 1
  1. 1.Federal University of Minas GeraisBelo HorizonteBrazil
  2. 2.Federal Center for Technological Education of Minas GeraisBelo HorizonteBrazil

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