• DocumentCode
    2793271
  • Title

    A Method for an Accurate Early Prediction of Faults in Modified Classes

  • Author

    Tomaszewski, Piotr ; Grahn, Håkan ; Lundberg, Lars

  • Author_Institution
    Sch. of Eng., Blekinge Inst. of Technol., Ronneby
  • fYear
    2006
  • fDate
    24-27 Sept. 2006
  • Firstpage
    487
  • Lastpage
    496
  • Abstract
    In this paper we suggest and evaluate a method for predicting fault densities in modified classes early in the development process, i.e., before the modifications are implemented. We start by establishing methods that according to literature are considered the best for predicting fault densities of modified classes. We find that these methods can not be used until the system is implemented. We suggest our own methods, which are based on the same concept as the methods suggested in the literature, with the difference that our methods are applicable before the coding has started. We evaluate our methods using three large telecommunication systems produced by Ericsson. We find that our methods provide predictions that are of similar quality to the predictions based on metrics available after the code is implemented. Our predictions are, however, available much earlier in the development process. Therefore, they enable better planning of efficient fault prevention and fault detection activities
  • Keywords
    software metrics; software performance evaluation; Ericsson; accurate early fault prediction; fault density prediction; fault detection; fault prevention; modified class fault; software metrics; telecommunication systems; Costs; Documentation; Fault detection; Fault diagnosis; Inspection; Predictive models; Programming; Software design; Software systems; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Maintenance, 2006. ICSM '06. 22nd IEEE International Conference on
  • Conference_Location
    Philadelphia, PA
  • ISSN
    1063-6773
  • Print_ISBN
    0-7695-2354-4
  • Type

    conf

  • DOI
    10.1109/ICSM.2006.6
  • Filename
    4021378