Fault Removal Efficiency in Software Reliability Growth Model

Software Reliability is defined as the probability of free-failure operation for a specified period of time in a specified environment. Software Reliability Growth models (SRGM) have been developed to estimate software reliability measures such as number of remaining faults, software failure rate and Software Reliability. Imperfect debugging models are considered in these models. However, most SRGM assume that faults will eventually be removed. Fault removal efficiency in the existing models is limited. This paper aims to incorporate the fault removal efficiency in software reliability growth modeling. In this paper imperfect debugging is considered in the sense that new faults can be introduced into the software during debugging and the detected faults may not be removed completely. Key wordsNon-Homogeneous Poisson process (NHPP), Software Reliability Growth Model (SRGM), Fault Removal, Maximum-Likelihood Estimation, Software Testing, Software Reliability, Software Debugging Advances in Computational Research ISSN: 0975-3273 & E-ISSN: 0975-9085, Volume 4, Issue 1, 2012 Introduction over the last two decades modern society has become more increasingly dependent on hardware and software systems. Software Reliability is defined as the probability of free failure operation for a specified period of time in a specified environment. Since 1970’s many SRGM have been proposed for estimation of Reliability growth of products during software development processes. SRGM are applicable to the late stages of testing in software development and can provide information in useful in predicting and improving reliability of software products. In this paper, we propose a methodology to integrate a methodology in software reliability growth model. We are presents the formulation of the NHPP model addressing fault removal efficiency and fault introduction rate. The explicit solution of the mean value function for the proposed NHPP model is derived. This model considers the learning phenomenon Using an S -shaped fault detection rate function and introduces a constant fault introduction rate. Software Testing is the process of exercising a program with the specific intent of finding faults prior to delivery to the users. After testing debugging is performed by programmers to discover high defects. Software Reliability Modeling In the family of Software Reliability models, NHPP Software Reliability models have been widely used in analyzing and estimating the reliability related metrics of software products in many applications, such as telecommunications [6],[20] etc. This model considers the debugging process as a counting process, which follows a Poisson process with a time dependent intensity function. Existing NHPP Software Reliability models can be unified into a general NHPP function proposed by pham etc.[9].The primary task of using the NHPP models to estimate Software Reliability metrics is to determine the Poisson mean, which is known as the MVF. In this section, an NHPP model with fault removal efficiency is presented. The following are the assumptions for this model: 1. The Occurrence of software failures follows an NHPP. 2. The software failure rate at any time is a function of Fault Citation: Purnaiah B., Rama Krishna V. and Bala Venkata Kishore G. (2012) Fault Removal Efficiency in Software Reliability Growth Model. Advances in Computational Research, ISSN: 0975-3273 & E-ISSN: 0975-9085, Volume 4, Issue 1, pp.-74-77. Copyright: Copyright©2012 Purnaiah B., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.