Software Reliability Models: Assumptions, Limitations, and Applicability

Goel, Amrit L.

doi:10.1109/tse.1985.232177

Cited by 759 publications

(281 citation statements)

References 27 publications

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“…To ensure the generality, we prefer to define the confidence of the software system as the probability that all the key parts of the system are executed satisfactorily in one round. This probabilistic definition is very similar to the one of software reliability in [21], except that the confidence is a broader concept. We can still use the work on software reliability [22,23] for reference.…”

Section: Confidence Estimation Of the Systemmentioning

confidence: 97%

A Trust-Based Approach to Estimating the Confidence of the Software System in Open Environments

Pan

2009

J. Comput. Sci. Technol.

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Emerging with open environments, the software paradigms, such as open resource coalition and Internetware, present several novel characteristics including user-centric, non-central control, and continual evolution. The goal of obtaining high confidence on such systems is more difficult to achieve. The general developer-oriented metrics and testing-based methods which are adopted in the traditional measurement for high confidence software seem to be infeasible in the new situation. Firstly, the software development is changed from the developer-centric to user-centric, while user's opinions are usually subjective, and cannot be generalized in one objective metric. Secondly, there is non-central control to guarantee the testing on components which formed the software system, and continual evolution makes it impossible to test on the whole software system. Therefore, this paper proposes a trust-based approach that consists of three sequential sub-stages: 1) describing metrics for confidence estimation from users; 2) estimating the confidence of the components based on the quantitative information from the trusted recommenders; 3) estimating the confidence of the whole software system based on the component confidences and their interactions, as well as attempts to make a step toward a reasonable and effective method for confidence estimation of the software system in open environments.

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Section: Confidence Estimation Of the Systemmentioning

confidence: 97%

A Trust-Based Approach to Estimating the Confidence of the Software System in Open Environments

Pan

2009

J. Comput. Sci. Technol.

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“…Okumoto [10] reviewed four analytical software reliability models which are used for estimating and monitoring software reliability. These models include Times Between failure Models, Failure Count Models, Fault Studying models and Input Domain Models.…”

Section: Literature Review 41 Parameter Estimation Using Maximum Likmentioning

confidence: 99%

A Review on Parameter Estimation Techniques of Software Reliability Growth Models

Bidhan¹,

Awasthi²

2014

IJCATR

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Software reliability is considered as a quantifiable metric, which is defined as the probability of a software to operate without failure for a specified period of time in a specific environment. Various software reliability growth models have been proposed to predict the reliability of a software. These models help vendors to predict the behaviour of the software before shipment. The reliability is predicted by estimating the parameters of the software reliability growth models. But the model parameters are generally in nonlinear relationships which creates many problems in finding the optimal parameters using traditional techniques like Maximum Likelihood and least Square Estimation. Various stochastic search algorithms have been introduced which have made the task of parameter estimation, more reliable and computationally easier. Parameter estimation of NHPP based reliability models, using MLE and using an evolutionary search algorithm called Particle Swarm Optimization, has been explored in the paper.

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“…A typical definition of software reliability is "the probability of the failure free operation of a computer program for a specified exposure period of time in a specified use environment" (IEEE, 1991;Boland, 2002;Khatatneh and Mustafa, 2009;Musa et al, 1984;Goel et al, 1985). Another definition of software reliability is "the probability of the product working correctly over a given period of time" (Mall, 2005).…”

Section: Introductionmentioning

confidence: 99%

“…It gives confidence about software correctness. Also it minimizes the additional cost of testing and improves software reliability (Goel, 1985). At the time of development of any product or system like commercial, military, or any other application, we need to ensure its reliability and consistency in its performance, because a system's reliability has a major impact on maintenance, repair costs, continuity of service, and customer satisfaction (Bhuyan et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Software Reliability Assesment using Neural Networks of Computational Intelligence Based on Software Failure Data

Bhuyan¹,

Mohapatra²,

Sethi³

2016

BJMC

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Abstract. The computational intelligence approach using Neural Network (NN) has been known to be very useful in predicting software reliability. Software reliability plays a key role in software quality. In order to improve accuracy and consistency of software reliability prediction, we propose the applicability of Feed Forward Back-Propagation Network (FFBPN) as a model to predict software reliability. The model has been applied on data sets collected across several standard software projects during system testing phase with fault removal. Unlike most connectionist models, our model attempt to compute average error (AE), the root mean square error (RMSE), normalized root mean square error (NRMSE), mean absolute error (MAE) simultaneously. A comparative study among the proposed feed-forward neural network with some traditional parametric software reliability growth model's performance is carried out. The results indicated in this work suggest that FFBPN model exhibit an accurate and consistent behavior in reliability prediction.

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Software Reliability Models: Assumptions, Limitations, and Applicability

Cited by 759 publications

References 27 publications

A Trust-Based Approach to Estimating the Confidence of the Software System in Open Environments

A Trust-Based Approach to Estimating the Confidence of the Software System in Open Environments

A Review on Parameter Estimation Techniques of Software Reliability Growth Models

Software Reliability Assesment using Neural Networks of Computational Intelligence Based on Software Failure Data

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