Effect of change in environment on reliability growth modeling integrating fault reduction factor and change point: a general approach

Vikas Dhaka and Nidhi Nijhawan ()
Additional contact information
Vikas Dhaka: University of Delhi
Nidhi Nijhawan: University of Delhi

Annals of Operations Research, 2024, vol. 340, issue 1, No 10, 215 pages

Abstract: Abstract This paper presents a generalized software reliability modeling framework that predominantly encompasses randomness of field environment, fault reduction factor (FRF), and change point to study their simultaneous effect on software bug removal process. To address and capture unpredicted randomness of the field environment in testing phase it is assumed that the environment before and after a change point may not be the same and therefore there is a need to consider distinct environment factors before and after the change point in the modeling of bug removal action. Based on the general approach, three new change point-based software reliability growth models (SRGMs) are proposed incorporating time-dependent exponentiated Weibull (EW) FRF and distinct random environment distributions. To elaborate, in SRGM-I and SRGM-II, a steady environment is supposed before the change point whereas one-parameter exponential environment is assumed after the change point in SRGM-I and a two-parameter Gamma environment is considered after the change point in SRGM-II while in SRGM-III, exponential environment before change point and Gamma environment after change point are taken into consideration. In addition, a few established FRF-based models are deduced from the proposed general approach. Estimation of parameters of proposed SRGMs is carried out in two phases using three real test data sets and their validation is evaluated through several performance measures including coefficient of determination, mean square error, bias, variation, root mean square prediction error and Akaike information criteria. Fitting of the models to the datasets is also examined in related goodness of fit curves. Further, numerical illustration is worked out to conduct a cost-reliability assessment and suggest optimum release time.

Keywords: SRGM; Random environment; Fault reduction factor; Change point; Software reliability; Release time (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10479-022-05084-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:annopr:v:340:y:2024:i:1:d:10.1007_s10479-022-05084-6

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1007/s10479-022-05084-6

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().