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A Study of the Relationship Between Class Testability and Runtime Properties

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Evaluation of Novel Approaches to Software Engineering (ENASE 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 551))

Abstract

Software testing is known to be expensive, time consuming and challenging. Although previous research has investigated relationships between several software properties and software testability the focus has been on static software properties. In this work we present the results of an empirical investigation into the possible relationship between runtime properties (dynamic coupling and key classes) and class testability. We measure both properties using dynamic metrics and argue that data gathered using dynamic metrics are both broader and more precise than data gathered using static metrics. Based on statistical analysis, we find that dynamic coupling and key classes are significantly correlated with class testability. We therefore suggest that these properties could be used as useful indicators of class testability.

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Notes

  1. 1.

    https://developers.google.com/java-devtools/codepro/doc/

  2. 2.

    http://metrics2.sourceforge.net/

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Author information

Authors and Affiliations

  1. Department of Information Science, University of Otago, Dunedin, New Zealand

    Amjed Tahir & Stephen MacDonell

  2. SERL, School of Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand

    Stephen MacDonell & Jim Buchan

Authors
  1. Amjed Tahir
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  2. Stephen MacDonell
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  3. Jim Buchan
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Corresponding author

Correspondence to Amjed Tahir .

Editor information

Editors and Affiliations

  1. Wroclaw University of Economics, Wroclaw, Poland

    Leszek A. Maciaszek

  2. INSTICC, Polytechnic Institute of Setúbal, Setúbal, Portugal

    Joaquim Filipe

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Tahir, A., MacDonell, S., Buchan, J. (2015). A Study of the Relationship Between Class Testability and Runtime Properties. In: Maciaszek, L., Filipe, J. (eds) Evaluation of Novel Approaches to Software Engineering. ENASE 2014. Communications in Computer and Information Science, vol 551. Springer, Cham. https://doi.org/10.1007/978-3-319-27218-4_5

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  • DOI: https://doi.org/10.1007/978-3-319-27218-4_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27217-7

  • Online ISBN: 978-3-319-27218-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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