• DocumentCode
    2377119
  • Title

    A Novel Method to Measure Comprehensive Complexity of Software Based on the Metrics Statistical Model

  • Author

    Sepasmoghaddam, Alireza ; Rashidi, Hassan

  • Author_Institution
    Electr., Comput. & IT Eng. Dept., Islamic Azad Univ., Qazvin, Iran
  • fYear
    2010
  • fDate
    17-19 Nov. 2010
  • Firstpage
    520
  • Lastpage
    525
  • Abstract
    Calculating software complexity is one of the most challenging problems in the Software Engineering due to using them in estimating errors, having a landscape of software reliability, approximating costs of software implementation and maintenance, and delivering software with better quality. Most of the recent researches on calculating the software\´s complexity focus on special directions and goals. This paper presents a novel method for measuring comprehensive complexity of software based on Statistical model evaluation of the existing complexity metrics through modules. To reach this purpose, the amount of comprehensive complexity is achieved for every module by identifying statistical distribution of complexity metric quantities, normalization and their combination. Afterward, the comprehensive complexity of the software is calculated by composition of the module\´s complexity amounts. This method is applied on some samples of the "NASA Software Engineering laboratory" and some of its positive results are presented.
  • Keywords
    software maintenance; software metrics; software quality; software reliability; statistical distributions; metrics statistical model; software complexity; software engineering; software implementation; software maintenance; software quality; software reliability; statistical distribution; Comprehensive Complexity; Exponential Distribution; Module; NASA Metrics Data Program; Software Complexity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Modeling and Simulation (EMS), 2010 Fourth UKSim European Symposium on
  • Conference_Location
    Pisa
  • Print_ISBN
    978-1-4244-9313-5
  • Electronic_ISBN
    978-0-7695-4308-6
  • Type

    conf

  • DOI
    10.1109/EMS.2010.92
  • Filename
    5703738