Paper Info
Title
Comparing between Maximum Likelihood Estimator and Non-linear Regression Estimation Procedures for NHPP Software Reliability Growth Modelling
Abstract
Software Reliability Growth Models (SRGMs) have been used by engineers and managers for tracking and managing the reliability change of software to ensure required standard of quality is achieved before the software is released to the customer. SRGMs can be used during the project to help make testing resource allocation decisions and/ or it can be used after the testing phase to determine the latent faults prediction to assess the maturity of software artifact. A number of SRGMs have been proposed and to apply a given reliability model, defect inflow data is fitted to model equations. Two of the widely known and recommended techniques for parameter estimation are maximum likelihood and method of least squares. In this paper we compare between the two estimation procedures for their applicability in context of NHPP SRGMs. We also highlight a couple of practical considerations, reliability practitioners must be aware of when applying SRGMs.
Year
DOI
Venue
2013
10.1109/IWSM-Mensura.2013.37
IWSM/Mensura
Keywords
Field
DocType
software artifact,parameter estimation,reliability practitioner,maximum likelihood estimator,model equation,reliability model,reliability change,estimation procedure,non-linear regression estimation procedures,software reliability growth models,nhpp software reliability growth,testing phase,nhpp srgms,software reliability,software quality,regression analysis,maximum likelihood estimation,resource allocation
Least squares,Regression analysis,Computer science,Nonlinear regression,Resource allocation,Software,Software reliability testing,Estimation theory,Software quality,Reliability engineering
Conference
Citations 
PageRank 
References 
0
0.34
17
Authors
6
Name
Order
Citations
PageRank
Rakesh Rana1285.93
Miroslaw Staron248652.25
Christian Berger3314.73
jorgen hansson442135.04
Martin Nilsson500.34
Fredrik Törner6708.43