Software Reliability Growth Modeling: Models and Applications

Yamada, Shigeru; Osaki, Shunji

doi:10.1109/tse.1985.232179

Cited by 335 publications

(169 citation statements)

References 15 publications

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“…Using the total software cost evaluated by cost criterion, the cost of testing-effort expenditures during software testing and development phase, and the cost of correcting errors before and after release are given by [34], [33], [31], [21], [14], [10], [11], [5], [9], [7].…”

Section: Software Release-time Based On Costreliability Criteriamentioning

confidence: 99%

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Software Reliability Growth Modeling with New Modified Weibull Testing–effort and Optimal Release Policy

Quadri¹,

Ahmad²

2010

IJCA

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In software development life cycle, software testing is one of the most important tasks; and in the testing, software reliably is very important aspect for any category of software systems. A number of testing-effort functions for software reliability growth model based on non-homogeneous Poisson process (NHPP) have been proposed in the past. Although these models are quite helpful for software developers and have been widely accepted and applied in the industries and research centers, we still need to put more testing-effort functions into software reliability growth model for accuracy on estimate of the parameters. In this paper, we will consider the case where the time dependent behaviors of testingeffort expenditures are described by New Modified Weibull Distribution (NMWD). Software Reliability Growth Models (SRGM) based on the NHPP are developed which incorporates the (NMWD) testing-effort expenditure during the softwaretesting phase. It is assumed that the error detection rate to the amount of testing-effort spent during the testing phase is proportional to the current error content. Model parameters are estimated by Least Square and Maximum Likelihood estimation techniques, and software measures are investigated through numerical experiments on real data from various software projects. The evaluation results are analyzed and compared with other existing models to show that the proposed SRGM with (NMWD) testing-effort has a fairly better faults prediction capability and it depicts the real-life situation more faithfully. This model can be applied to a wide range of software system. In addition, the optimal release policy for this model, based on reliability criterion is discussed.

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Section: Software Release-time Based On Costreliability Criteriamentioning

confidence: 99%

“…The testing-effort can be represented as the number of CPU hours; the number of executed test cases; etc. [31], [36], [33]. Most of these works on SRGM based on NHPP assuming that the time-dependent behavior of test-effort expenditure is either exponential, Weibull, logistic or generalized logistic curve.…”

Section: Introductionmentioning

confidence: 99%

Software Reliability Growth Modeling with New Modified Weibull Testing–effort and Optimal Release Policy

Quadri¹,

Ahmad²

2010

IJCA

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“…Discovering the confidence intervals of software reliability is done in the field of software reliability because it can enhance the decision of software releases and control the related expenditures for software testing [1]. First, Yamada and Osaki [2] considered that the maximum likelihood estimates concerning the confidence interval of the mean value function can be estimated. Yin and Trivedi [3] present the confidence bounds for the model parameters via the Bayesian approach.…”

Section: Introductionmentioning

confidence: 99%

A Software Reliability Model with a Weibull Fault Detection Rate Function Subject to Operating Environments

Song¹,

Chang²,

Pham³

2017

Preprint

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ABSTRACT:The main focus when developing software is to improve the reliability and stability of a software system. When software systems are introduced, these systems are used in field environments that are the same as or close to those used in the development-testing environment; however, they may also be used in many different locations that may differ from the environment in which they were developed and tested. In this paper, we propose a new software reliability model that takes into account the uncertainty of operating environments. The explicit mean value function solution for the proposed model is presented. Examples are presented to illustrate the goodness-of-fit of the proposed model and several existing non-homogeneous Poisson process (NHPP) models and confidence intervals of all models based on two sets of failure data collected from software applications. The results show that the proposed model fits the data more closely than other existing NHPP models to a significant extent.

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“…Various models for software reliability are available and these are mostly based on the non -homogeneous Poisson process with a mean value function [1,2,3,4,5]. Software reliability growth models using non-homogeneous Poisson processes (NHPP's) are studied by Shigeru Yamuda and Shurji Osaki (1985).…”

Section: Introductionmentioning

confidence: 99%