EconPapers    
Economics at your fingertips  
 

Software reliability modeling based on NHPP for error occurrence in each fault with periodic debugging schedule

Sudipta Das, Damitri Kundu and Anup Dewanji

Communications in Statistics - Theory and Methods, 2022, vol. 51, issue 14, 4890-4902

Abstract: In this article, we discuss a continuous time software reliability model under the non homogeneous Poisson process (NHPP) assumption for error occurrence in each fault to suit periodic debugging, in which errors are not corrected at the instants of their detection but at some pre-specified debugging times. We describe maximum likelihood estimation for the model parameters and provide a computational method to estimate those parameters. This in turn helps to estimate the reliability of the software. We also discuss some asymptotic properties of the estimated model parameters, specially the number of errors initially present in the software. Finally, we investigate the finite sample properties of the estimates under a specific family of NHPP models, specially that of the initial number of errors, through simulation.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2020.1828462 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:51:y:2022:i:14:p:4890-4902

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2020.1828462

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:lstaxx:v:51:y:2022:i:14:p:4890-4902