• Convergence Security Journal
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• v.13 no.1
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• pp.3-10
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• 2013

In this paper, reliability software model considering fault detection rate based on observations from the process of software product testing was studied. Adding new fault probability using the S-shaped distribution model that is widely used in the field of reliability problems presented. When correcting or modifying the software, finite failure non-homogeneous Poisson process model was used. In a software failure data analysis considering the time-dependent fault detection rate, the parameters estimation using maximum likelihood estimation of failure time data and reliability make out.

• International Journal of Reliability and Applications
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• v.2 no.3
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• pp.199-207
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• 2001

The failure rate functions between successive failures are of concatenated form. We allow the parameters of failure rate function change after a certain failure and its fixing. We confine out attention to a model wherein the interfailure times are described by its failure rate function. We suggest an adaptive failure rate function with a change-point under the assumption that interfailure times are record value statistics from a Weibull distribution. The proposed model will be applied through a practical example of software failure data.

• Journal of the Korea Computer Industry Society
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• v.3 no.7
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• pp.837-844
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• 2002

In general, software test is carried out to detect or repair errors in system during software development process. Namely, we can evaluate software reliability through collecting and removing the faults detected in testing phase. Software reliability growth model evaluates reliability of software mathematically. Many kinds of software reliability growth modeling which modeling the processes of detecting, revising and removing the faults detected in testing phase have been proposed in many ways. and, it is assumed that almost of these modeling have one typed detect and show the uniformed detection rate. In this study, significance levels of the faults detected in test phase are classified according to how they can affect on the whole system and then the fault detection capability of them is applied. From this point of view, We here by propose a software reliability growth model with faults detection capability according considering fault significance levels and apply some fault data to this proposed model and finally verify its validity by comparing and estimating with the existing modeling.

• The Transactions of the Korea Information Processing Society
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• v.6 no.3
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• pp.615-621
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• 1999

On the aspect of on-time and development resource use, it is very important to predict the software release time during the software development process. In this paper, we present the optimal release problem based on the evaluation indicator and cost evaluation. And also we show the optimal release point considered with both of them. We applied the Exponential Software Reliability Growth Model(E-SRGM) and Testing-effort dependent Software Reliability Growth Model(Te-SRGM) and decided the software release time according to software reliability indicator. As a result of two models comparison, we verify the Te-SRGM is more adopted in our switching system software.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.4
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• pp.351-358
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• 2016

Science and technology is developing rapidly as more powerful software with the rapid development of software testing and reliability assessment by the difficulty increases with the complexity of the software features of the larger increases NHPP software reliability models for failure analysis can have, in the literature, exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, finite failure NHPP models that assuming the expected value of the defect and infinite failures NHPP models that repairing software failure point in time reflects the situation, were presented for comparing property. Commonly used in the field of software reliability based on Erlang distribution software reliability model finite failures and infinite failures were presented for performance comparative evaluation problem. As a result, finite failure model is better than infinite failure model effectively. The parameters estimation using maximum likelihood estimation in the course of this study was conducted. As the results of this research, software developers to identify software failure property be able to help is concluded.

• The KIPS Transactions:PartD
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• v.10D no.5
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• pp.829-836
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• 2003

Software Reliability Growth Model that have been studied variously. But measurement of correct parameter of this model is not easy. Specially, estimation of correct model about failure data must be establish and estimation of parameter can consist exactly. To get correct testing, we calculate the normal score and describe the normal probability plot. Use the normal probability plot, we estimate the distribution for failure data. In this paper, we estimate the software reliability growth model for through the normal probability plot. In this research, we applies software reliability growth model through distribution characteristics of failure data. If we see plot, we determine the software reliability growth model, we can make sure superior in model's performance estimation.

• Journal of Korean Society for Quality Management
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• v.37 no.3
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• pp.33-38
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• 2009

When we estimate the parameters of software reliability models, we usually use maximum liklihood estimator(MLE). But this method is required a large data set. In particular, when we want to estimate it with small observed data such as early stages of testing, we give rise to the non-existence of MLE. Therefore, it is interesting to look into the influence of parameter estimators obtained using MLE. In this paper, we use two non-homogenous poisson process software reliability growth model: delayed S-shaped model and log power model. In this paper, we calculate the sensitivity of estimators about failure intensity function for two SRGMs respectively.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.2
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• pp.171-177
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• 2016

Software reliability in the software development process is an important issue. Software process improvement helps in finishing with reliable software product. Infinite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this study, reliability software cost model considering shape parameter based on life distribution from the process of software product testing was studied. The cost comparison problem of the Lomax distribution reliability growth model that is widely used in the field of reliability presented. The software failure model was used the infinite failure non-homogeneous Poisson process model. The parameters estimation using maximum likelihood estimation was conducted. For analysis of software cost model considering shape parameter. In the process of change and large software fix this situation can scarcely avoid the occurrence of defects is reality. The conditions that meet the reliability requirements and to minimize the total cost of the optimal release time. Studies comparing emissions when analyzing the problem to help kurtosis So why Kappa efficient distribution, exponential distribution, etc. updated in terms of the case is considered as also worthwhile. In this research, software developers to identify software development cost some extent be able to help is considered.

• Journal of Information Technology Applications and Management
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• v.27 no.3
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• pp.69-75
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• 2020

In this paper, we applied the shape parameters of the exponentialized exponential life distribution widely used in the field of software reliability, and compared the reliability properties of the software using the non-homogeneous Poisson process in finite failure. In addition, the average value function is also a non-decreasing form. In the case of the larger the shape parameter, the smaller the estimated error in predicting the predicted value in comparison with the true value, so it can be regarded as an efficient model in terms of relative accuracy. Also, in the larger the shape parameter, the larger the estimated value of the coefficient of determination, which can be regarded as an efficient model in terms of suitability. So. the larger the shape parameter model can be regarded as an efficient model in terms of goodness-of-fit. In the form of the reliability function, it gradually appears as a non-increasing pattern and the higher the shape parameter, the lower it is as the mission time elapses. Through this study, software operators can use the pattern of mean square error, mean value, and hazard function as a basic guideline for exploring software failures.

• Journal of Korean Society for Quality Management
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• v.34 no.4
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• pp.133-138
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• 2006

In this paper, we propose a software reliability growth model (SRGM) based on the testing domain, which is isolated by the executed test cases. This model assumes an imperfect debugging environment in which new faults are introduced in the fault-correction process. We consider that the fault detection rate of NHPP model is changed in the proposed SRGM. We obtain the maximum likelihood estimate, and compare goodness-of-fit with another existing software reliability growth model.