Title :
Comparing between Maximum Likelihood Estimator and Non-linear Regression Estimation Procedures for NHPP Software Reliability Growth Modelling
Author :
Rana, Rakesh ; Staron, Miroslaw ; Berger, Claire ; Hansson, Jorgen ; Nilsson, Martin ; Torner, Fredrik
Author_Institution :
Comput. Sci. & Eng., Chalmers/ Univ. of Gothenburg, Gothenburg, Sweden
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.
Keywords :
least squares approximations; maximum likelihood estimation; program testing; regression analysis; resource allocation; software quality; software reliability; software standards; NHPP SRGM; latent faults prediction; least squares; maximum likelihood estimator; nonlinear regression estimation; parameter estimation; reliability change; reliability model; resource allocation decisions testing; software artifact; software quality standard; software reliability growth models; testing phase; Data models; Mathematical model; Maximum likelihood estimation; Predictive models; Software; Software reliability; Asymptote prediction; BPRE; Maximum likelihood estimation; Non-linear Regression; Predictive relative error (PRE); Software reliability growth model (SRGM); unbiased;
Conference_Titel :
Software Measurement and the 2013 Eighth International Conference on Software Process and Product Measurement (IWSM-MENSURA), 2013 Joint Conference of the 23rd International Workshop on
Conference_Location :
Ankara
DOI :
10.1109/IWSM-Mensura.2013.37