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Assessing the User-Perceived Quality of Source Code Components Using Static Analysis Metrics

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Software Technologies (ICSOFT 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 868))

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Abstract

Nowadays, developers tend to adopt a component-based software engineering approach, reusing own implementations and/or resorting to third-party source code. This practice is in principle cost-effective, however it may also lead to low quality software products, if the components to be reused exhibit low quality. Thus, several approaches have been developed to measure the quality of software components. Most of them, however, rely on the aid of experts for defining target quality scores and deriving metric thresholds, leading to results that are context-dependent and subjective. In this work, we build a mechanism that employs static analysis metrics extracted from GitHub projects and defines a target quality score based on repositories’ stars and forks, which indicate their adoption/acceptance by developers. Upon removing outliers with a one-class classifier, we employ Principal Feature Analysis and examine the semantics among metrics to provide an analysis on five axes for source code components (classes or packages): complexity, coupling, size, degree of inheritance, and quality of documentation. Neural networks are thus applied to estimate the final quality score given metrics from these axes. Preliminary evaluation indicates that our approach effectively estimates software quality at both class and package levels.

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Authors and Affiliations

  1. Electrical and Computer Engineering Department, Aristotle University of Thessaloniki, Thessaloniki, Greece

    Valasia Dimaridou, Alexandros-Charalampos Kyprianidis, Michail Papamichail, Themistoklis Diamantopoulos & Andreas Symeonidis

Authors
  1. Valasia Dimaridou
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  2. Alexandros-Charalampos Kyprianidis
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  3. Michail Papamichail
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  4. Themistoklis Diamantopoulos
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  5. Andreas Symeonidis
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Corresponding author

Correspondence to Themistoklis Diamantopoulos .

Editor information

Editors and Affiliations

  1. King Juan Carlos University, Madrid, Spain

    Enrique Cabello

  2. University of Coimbra, Coimbra, Portugal

    Jorge Cardoso

  3. Wroclaw University of Economics, Wroclaw, Poland

    Leszek A. Maciaszek

  4. Computer Science, University of Twente, Enschede, The Netherlands

    Marten van Sinderen

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Dimaridou, V., Kyprianidis, AC., Papamichail, M., Diamantopoulos, T., Symeonidis, A. (2018). Assessing the User-Perceived Quality of Source Code Components Using Static Analysis Metrics. In: Cabello, E., Cardoso, J., Maciaszek, L., van Sinderen, M. (eds) Software Technologies. ICSOFT 2017. Communications in Computer and Information Science, vol 868. Springer, Cham. https://doi.org/10.1007/978-3-319-93641-3_1

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  • DOI: https://doi.org/10.1007/978-3-319-93641-3_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-93640-6

  • Online ISBN: 978-3-319-93641-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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