A study of software reliability growth model for time-dependent learning effects

Kuei-Chen Chiu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

This paper considered time-dependent learning effects in the software reliability growth model which Chiu et al. (2008) provided from the perspective of learning effects and would be able to reasonably describe the S-shaped and exponential-shaped types of behaviors simultaneously, and had better performance in fitting different data with consideration of a constant learning effect to enhance the model. This study assumed learning effects were depend on the process time and improved the model with linear-learning effect and exponential-learning effect to discuss when and what learning effects would occur in the software development process. This paper also verified the effectiveness of the proposed model with R square (Rsq) and compared with other models by using the comparison criteria with real data set. The results revealed that the proposed model shows good fitting in the data set which software development process exists time-dependent learning effects.

Original languageEnglish
Title of host publication2012 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2012
PublisherIEEE Computer Society
Pages1015-1019
Number of pages5
ISBN (Print)9781467329453
DOIs
Publication statusPublished - 2012 Jan 1
Event2012 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2012 - Hong Kong, China
Duration: 2012 Dec 102012 Dec 13

Publication series

NameIEEE International Conference on Industrial Engineering and Engineering Management
ISSN (Print)2157-3611
ISSN (Electronic)2157-362X

Other

Other2012 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2012
CountryChina
CityHong Kong
Period12-12-1012-12-13

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting (miscellaneous)
  • Industrial and Manufacturing Engineering
  • Safety, Risk, Reliability and Quality

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