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Article
Publication date: 25 January 2008

Nesar Ahmad, M.U. Bokhari, S.M.K. Quadri and M.G.M. Khan

The purpose of this research is to incorporate the exponentiated Weibull testing‐effort functions into software reliability modeling and to estimate the optimal software release…

Abstract

Purpose

The purpose of this research is to incorporate the exponentiated Weibull testing‐effort functions into software reliability modeling and to estimate the optimal software release time.

Design/methodology/approach

This paper suggests a software reliability growth model based on the non‐homogeneous Poisson process (NHPP) which incorporates the exponentiated Weibull (EW) testing‐efforts.

Findings

Experimental results on actual data from three software projects are compared with other existing models which reveal that the proposed software reliability growth model with EW testing‐effort is wider and effective SRGM.

Research limitations/implications

This paper presents a SRGM using a constant error detection rate per unit testing‐effort.

Practical implications

Software reliability growth model is one of the fundamental techniques to assess software reliability quantitatively. The results obtained in this paper will be useful during the software testing process.

Originality/value

The present scheme has a flexible structure and may cover many of the earlier results on software reliability growth modeling. In general, this paper also provides a framework in which many software reliability growth models can be described.

Details

International Journal of Quality & Reliability Management, vol. 25 no. 2
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 1 April 1996

Nalina Suresh, A.N.V. Rao and A.J.G. Babu

Most of the existing software reliability models assume time between failures to follow an exponential distribution. Develops a reliability growth model based on non‐homogeneous…

1076

Abstract

Most of the existing software reliability models assume time between failures to follow an exponential distribution. Develops a reliability growth model based on non‐homogeneous Poisson process with intensity function given by the power law, to predict the reliability of a software. Several authors have suggested the use of the non‐homogeneous Poisson process to assess the reliability growth of software and to predict their failure behaviour. Inference procedures considered by these authors have been Bayesian in nature. Uses an unbiased estimate of the failure rate for prediction. Compares the performance of this model with Bayes empirical‐Bayes models and a time series model. The model developed is realistic, easy to use, and gives a better prediction of reliability of a software.

Details

International Journal of Quality & Reliability Management, vol. 13 no. 3
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 25 November 2021

Saurabh Panwar, Vivek Kumar, P.K. Kapur and Ompal Singh

Software testing is needed to produce extremely reliable software products. A crucial decision problem that the software developer encounters is to ascertain when to terminate the…

Abstract

Purpose

Software testing is needed to produce extremely reliable software products. A crucial decision problem that the software developer encounters is to ascertain when to terminate the testing process and when to release the software system in the market. With the growing need to deliver quality software, the critical assessment of reliability, cost of testing and release time strategy is requisite for project managers. This study seeks to examine the reliability of the software system by proposing a generalized testing coverage-based software reliability growth model (SRGM) that incorporates the effect of testing efforts and change point. Moreover, the strategic software time-to-market policy based on costreliability criteria is suggested.

Design/methodology/approach

The fault detection process is modeled as a composite function of testing coverage, testing efforts and the continuation time of the testing process. Also, to assimilate factual scenarios, the current research exhibits the influence of software users refer as reporters in the fault detection process. Thus, this study models the reliability growth phenomenon by integrating the number of reporters and the number of instructions executed in the field environment. Besides, it is presumed that the managers release the software early to capture maximum market share and continue the testing process for an added period in the user environment. The multiattribute utility theory (MAUT) is applied to solve the optimization model with release time and testing termination time as two decision variables.

Findings

The practical applicability and performance of the proposed methodology are demonstrated through real-life software failure data. The findings of the empirical analysis have shown the superiority of the present study as compared to conventional approaches.

Originality/value

This study is the first attempt to assimilate testing coverage phenomenon in joint optimization of software time to market and testing duration.

Details

International Journal of Quality & Reliability Management, vol. 39 no. 3
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 1 March 2003

Yasuhiko Nishio and Tadashi Dohi

The software reliability models to describe the reliability growth phenomenon are formulated by any stochastic point process with state‐dependent or time‐dependent intensity…

Abstract

The software reliability models to describe the reliability growth phenomenon are formulated by any stochastic point process with state‐dependent or time‐dependent intensity function. On the other hand, to deal with the environmental data, which consists of covariates influencing times to software failure, it may be useful to apply the Cox’s proportional hazards model for assessing the software reliability. In this paper, we review the proportional hazards software reliability models and discuss the problem to determine the optimal software release time under the expected total software cost criterion. Numerical examples are devoted to examine the dependence of the covariate structure in both the software reliability prediction and the optimal software release decision.

Details

Journal of Quality in Maintenance Engineering, vol. 9 no. 1
Type: Research Article
ISSN: 1355-2511

Keywords

Article
Publication date: 27 July 2021

Avinash Kumar Shrivastava and Ruchi Sharma

The purpose of this paper is to develop a new software reliability growth model considering different fault distribution function before and after the change point.

Abstract

Purpose

The purpose of this paper is to develop a new software reliability growth model considering different fault distribution function before and after the change point.

Design/methodology/approach

In this paper, the authors have developed a framework to incorporate change-point in developing a hybrid software reliability growth model by considering different distribution functions before and after the change point.

Findings

Numerical illustration suggests that the proposed model gives better results in comparison to the existing models.

Originality/value

The existing literature on change point-based software reliability growth model assumes that the fault correction trend before and after the change is governed by the same distribution. This seems impractical as after the change in the testing environment, the trend of fault detection or correction may not follow the same trend; hence, the assumption of same distribution function may fail to predict the potential number of faults. The modelling framework assumes different distributions before and after change point in developing a software reliability growth model.

Details

International Journal of Quality & Reliability Management, vol. 39 no. 5
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 16 February 2023

Vibha Verma, Sameer Anand and Anu Gupta Aggarwal

The software development team reviews the testing phase to assess if the reliability growth of software is as per plan and requirement and gives suggestions for improvement. The…

Abstract

Purpose

The software development team reviews the testing phase to assess if the reliability growth of software is as per plan and requirement and gives suggestions for improvement. The objective of this study is to determine the optimal review time such that there is enough time to make judgments about changes required before the scheduled release.

Design/methodology/approach

Testing utilizes majority of time and resources, assures reliability and plays a critical role in release and warranty decision-making reviews necessary. A very early review during testing may not give useful information for analyzing or improving project performance, and a very late review may delay product delivery and lead to opportunity loss for developers. Therefore, it is assumed that the optimal time for review is in the later stage of testing when the fault removal rate starts to decline. The expression for this time point is determined using the S-curve 2-D software reliability growth model (SRGM).

Findings

The methodology has been illustrated using the real-life fault datasets of Tandem computers and radar systems resulting in optimal review time of 14 weeks and 26 months, respectively, which is neither very early in testing nor very near to the scheduled release. The developer can make changes (more resources or postpone release) to expedite the process.

Originality/value

Most of the literature studies focus on determination of optimal testing or release time to achieve considerable reliability within the budget, but in this study, the authors determine the optimal review time during testing using SRGM to ensure the considerable reliability at release.

Details

International Journal of Quality & Reliability Management, vol. 40 no. 9
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 1 October 2006

Y. Tamura, S. Yamada and M. Kimura

The aim of this paper is to propose a software reliability growth model based on stochastic differential equations for the integration testing phase of distributed development…

Abstract

Purpose

The aim of this paper is to propose a software reliability growth model based on stochastic differential equations for the integration testing phase of distributed development environment.

Design/methodology/approach

A client/server system (CSS), which is a new development method, has come into existence as a result of the progress of networking technology by UNIX systems. On the other hand, the effective testing method for distributed development environment has only a few presented. The method of software reliability assessment considering the interaction among software components in a distributed one is discussed.

Findings

Conventional software reliability growth models for system testing phase in distributed development environment have included many unknown parameters. Especially, the effective estimation method in terms of these unknown parameters, which means the proportion of the total testing‐load for the software component, has never been presented. This software reliability growth model can be easily applied in distributed software development, because the model has a simple structure.

Practical implications

This model is very useful for software developers in terms of practical reliability assessment in the actual distributed development environment.

Originality/value

The method of software reliability assessment considering the interaction among software components in distributed development environment is proposed. Additionally, several numerical examples for the actual data are presented.

Details

Journal of Quality in Maintenance Engineering, vol. 12 no. 4
Type: Research Article
ISSN: 1355-2511

Keywords

Article
Publication date: 12 January 2010

N. Ahmad, M.G.M. Khan and L.S. Rafi

The purpose of this paper is to investigate how to incorporate the exponentiated Weibull (EW) testing‐effort function (TEF) into inflection S‐shaped software reliability growth

Abstract

Purpose

The purpose of this paper is to investigate how to incorporate the exponentiated Weibull (EW) testing‐effort function (TEF) into inflection S‐shaped software reliability growth models (SRGMs) based on non‐homogeneous Poisson process (NHPP). The aim is also to present a more flexible SRGM with imperfect debugging.

Design/methodology/approach

This paper reviews the EW TEFs and discusses inflection S‐shaped SRGM with EW testing‐effort to get a better description of the software fault detection phenomenon. The SRGM parameters are estimated by weighted least square estimation (WLSE) and maximum‐likelihood estimation (MLE) methods. Furthermore, the proposed models are also discussed under imperfect debugging environment.

Findings

Experimental results from three actual data applications are analyzed and compared with the other existing models. The findings reveal that the proposed SRGM has better performance and prediction capability. Results also confirm that the EW TEF is suitable for incorporating into inflection S‐shaped NHPP growth models.

Research limitations/implications

This paper presents the WLSE results with equal weight. Future research may be carried out for unequal weights.

Practical implications

Software reliability modeling and estimation are a major concern in the software development process, particularly during the software testing phase, as unreliable software can cause a failure in the computer system that can be hazardous. The results obtained in this paper may facilitate the software engineers, scientists, and managers in improving the software testing process.

Originality/value

The proposed SRGM has a flexible structure and may capture features of both exponential and S‐shaped NHPP growth models for failure phenomenon.

Details

International Journal of Quality & Reliability Management, vol. 27 no. 1
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 28 February 2020

Adarsh Anand, Jasmine Kaur and Shinji Inoue

The purpose of the present work is to mathematically model the reliability growth of a multi-version software system that is affected by infected patches.

Abstract

Purpose

The purpose of the present work is to mathematically model the reliability growth of a multi-version software system that is affected by infected patches.

Design/methodology/approach

The work presents a mathematical model that studies the reliability change due to the insertion of an infected patch in multi-version software. Various distribution functions have been considered to highlight the varied aspects of the model. Furthermore, weighted criteria approach has been discussed to facilitate the choice of the model.

Findings

The model presented here is able to quantify the effect of an infected patch on multi-version software. The model captures the hike in bug content due to an infected patch.

Originality/value

Multi-version systems have been studied widely, but the role of an infected patch has not been yet explored. The effect of an infected patch has been quantified by modeling the extra bugs generated in the system. This bug count would prove helpful in further studies for optimal resource allocation and testing effort allocation.

Details

International Journal of Quality & Reliability Management, vol. 37 no. 6/7
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 1 October 2000

Yi‐Ping Chang

Non‐homogeneous Poisson process (NHPP) models, as the stochastic models frequently employed in reliability engineering, have been successfully used in the reliability study of…

Abstract

Non‐homogeneous Poisson process (NHPP) models, as the stochastic models frequently employed in reliability engineering, have been successfully used in the reliability study of software systems. The software reliability based on NHPP models was proposed by Goel and Okumoto. In general, the software reliability will increase along with the correction of the software errors. This idea gives rise to a hypothesis: extending the time on the software reliability test could result in obtaining a higher reliability. Nevertheless, the scheme was found to be discrepant for some NHPP models, which are utilized in the analysis. As this often occurs in practice, the reliability outcome could differ from its appropriate estimation when the test procedures are intentionally terminated prior to the end of the required testing time span. An “above average software reliability” is proposed in this paper to accomplish the inconsistency. Under the investigation of “average software reliability”, a higher software reliability can be achieved as long as the testing time increases. Also, in this paper, an optimal software release policy is proposed to explore the issue of compromising the expenses on software development and software reliability improvement.

Details

International Journal of Quality & Reliability Management, vol. 17 no. 7
Type: Research Article
ISSN: 0265-671X

Keywords

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