DocumentCode
2417618
Title
A study of software reliability growth model for time-dependent learning effects
Author
Kuei-Chen Chiu
Author_Institution
Dept. of Bus. Adm., Hsing Kuo Univ. of Manage., Taiwan
fYear
2012
fDate
10-13 Dec. 2012
Firstpage
1015
Lastpage
1019
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.
Keywords
learning (artificial intelligence); program testing; software reliability; R square; Rsq; S-shaped behavior type; comparison criteria; constant learning effect; exponential-learning effect; exponential-shaped behavior types; linear-learning effect; process time; real data set; software development process; software reliability growth model; software testing; time-dependent learning effects; Analytical models; Computational modeling; Data models; Debugging; Mathematical model; Software; Software reliability; Non-Homogeneous Poisson Process (NHPP); Software reliability; learning effects; time-dependent learning effects;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Engineering and Engineering Management (IEEM), 2012 IEEE International Conference on
Conference_Location
Hong Kong
Type
conf
DOI
10.1109/IEEM.2012.6837894
Filename
6837894
Link To Document