• DocumentCode
    155210
  • Title

    Exploring the Relationships between the Understandability of Architectural Components and Graph-Based Component Level Metrics

  • Author

    Stevanetic, Srdjan ; Zdun, Uwe

  • Author_Institution
    Software Archit. Res. Group, Univ. of Vienna, Vienna, Austria
  • fYear
    2014
  • fDate
    2-3 Oct. 2014
  • Firstpage
    353
  • Lastpage
    358
  • Abstract
    Architectural component models are frequently used as a central view of architectural descriptions of software systems and therefore play a crucial role in the whole development process and in achieving the desired software qualities. The components in those models represent important high level structural units that are often used to group either lower-level sub-components or classes in object-oriented design views. In this paper we present a study that examines the relationships between the effort required to understand a component, measured through the time that participants spent on studying a component, and a number of information theory based and the corresponding counting based metrics on graphs at the component level. The results show a statistically significant correlation between all of the metrics and the effort required to understand a component. In a multivariate regression analysis we obtained some reasonably well-fitting models that can be used to estimate the effort required to understand a component.
  • Keywords
    graph theory; regression analysis; software architecture; software metrics; software quality; architectural component models; counting-based metrics; effort estimation; graph-based component level metrics; high-level structural units; information theory; lower-level classes; lower-level subcomponents; model understandability; multivariate regression analysis; object-oriented design views; software development process; software qualities; software system architectural descriptions; statistical analysis; Complexity theory; Correlation; Information theory; Measurement; Object oriented modeling; Predictive models; Software systems; architectural components; empirical evaluation; software metrics; understandability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Quality Software (QSIC), 2014 14th International Conference on
  • Conference_Location
    Dallas, TX
  • ISSN
    1550-6002
  • Print_ISBN
    978-1-4799-7197-8
  • Type

    conf

  • DOI
    10.1109/QSIC.2014.21
  • Filename
    6958424