Comparison for the accuracy of defect fix effort estimation

Author

Thaw, Tinzar ; Aung, Myintzu Phyo ; Wah, Naw Lay ; Nyein, Swe Swe ; Phyo, Zar Lwin ; Htun, Khaing Zarchi

Author_Institution

Univ. of Comput. Studies Mandalay, Mandalay, Myanmar

Volume

3

fYear

2010

fDate

16-18 April 2010

Abstract

Software defects have become the dominant cause of customer outage and the study of software errors has been necessitated by the emphasis on software reliability. Yet, software defects are not well enough understood to provide a clear methodology for avoiding or recovering from them. So software defect fix efforts play the critical role in software quality assurance. In this paper, the comparison of the defect fix effort estimation by using Self-Organizing Map in neural network is presented. To estimate the defect fix effort, KC3 static defect attributes that is one of the publicly available data from NASA products is used in this paper. To implement the SOM, finding different clusters from the SOM and for the calculation of fix effort time of defect SOM Toolbox in MATLAB 7.0.1 is used.

Keywords

mathematics computing; self-organising feature maps; software maintenance; MATLAB 7.0.1; SOM Toolbox; customer outage; defect fix effort estimation; neural network; self-organizing map; software defects; software errors; software quality assurance; Computer errors; Computer languages; Computer networks; Costs; MATLAB; NASA; Neural networks; Software maintenance; Software quality; Software reliability; Defects Estimation; Matlab7.0; Neural Network; SOM;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Engineering and Technology (ICCET), 2010 2nd International Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4244-6347-3

Type

conf

DOI

10.1109/ICCET.2010.5485813

Filename

5485813