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Mathematical Problems in Engineering
Volume 2009, Article ID 581383, 15 pages
Research Article

Stochastic Differential Equation-Based Flexible Software Reliability Growth Model

1Department of Operational Research, University of Delhi, Delhi 110007, India
2S.S. College of Business Studies, University of Delhi, Delhi 110095, India
3Department of Social Management Engineering, Graduate School of Engineering, Tottori University, 4-101, Minnami, Koyama, Tottori 680-8552, Japan
4Department of Industrial and System Engineering, University of Pretoria, Pretoria 0002, South Africa

Received 28 November 2008; Accepted 14 April 2009

Academic Editor: Sergio Preidikman

Copyright © 2009 P. K. Kapur et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Several software reliability growth models (SRGMs) have been developed by software developers in tracking and measuring the growth of reliability. As the size of software system is large and the number of faults detected during the testing phase becomes large, so the change of the number of faults that are detected and removed through each debugging becomes sufficiently small compared with the initial fault content at the beginning of the testing phase. In such a situation, we can model the software fault detection process as a stochastic process with continuous state space. In this paper, we propose a new software reliability growth model based on Itô type of stochastic differential equation. We consider an SDE-based generalized Erlang model with logistic error detection function. The model is estimated and validated on real-life data sets cited in literature to show its flexibility. The proposed model integrated with the concept of stochastic differential equation performs comparatively better than the existing NHPP-based models.