• International Journal of Reliability and Applications
• /
• v.4 no.3
• /
• pp.131-139
• /
• 2003

There is a new trend of incorporating software coverage metrics into software modelling. This paper proposes and empirically evaluates a software reliability growth model, which relates reliability to coverage. The proposed model is derived by modifying the assumptions on which Veevers and Marshall model is based.

• Communications for Statistical Applications and Methods
• /
• v.20 no.6
• /
• pp.467-474
• /
• 2013

It is common to measure multiple coverage metrics during software testing. Software reliability growth models and coverage growth functions have been applied to each coverage metric to evaluate software reliability; however, analysis results for the individual coverage metrics may conflict with each other. This paper proposes the virtual coverage metric of a normalized first principal component in order to avoid conflicting cases. The use of the virtual coverage metric causes a negligible loss of information.

• Journal of Korean Society for Quality Management
• /
• v.44 no.3
• /
• pp.565-574
• /
• 2016

Purpose: In this study, A reliability assurance model (or reliability program) is proposed to evaluate the reliability of an armed vehicle. The reliability assurance is performed through the reliability-centered activities in the K-000(armed vehicle) of D-Company Methods: By reflecting the current situations of korea defense industry, a reliability assurance model is built up based on the benchmarking results of world leading companies' best practices in same fields. So The reliability growth model is applied the Crow-AMSAA model Results: This research analysis the K-000(armed vehicle) of D-Company using the DT and OT failure data. and application case study by growth model of armed vehicles Conclusion: This research is result of application case study by growth model of armed vehicles.

• Communications for Statistical Applications and Methods
• /
• v.17 no.6
• /
• pp.909-916
• /
• 2010

A trend in software reliability engineering is to take into account the coverage growth behavior during testing. A coverage growth function that represents the coverage growth behavior is an essential factor in software reliability models. When multiple competitive coverage growth functions are available, there is a need for a criterion to select the best coverage growth functions. This paper proposes a selection criterion based on the prediction error. The conditional coverage growth function is introduced for predicting future coverage growth. Then the sum of the squares of the prediction error is defined and used for selecting the best coverage growth function.

• Proceedings of the Safety Management and Science Conference
• /
• 2004.11a
• /
• pp.269-276
• /
• 2004

Special, high technology developments and systems improvements become more necessary as the industrial society is becoming complex. When some systems are developed, it is common that developed systems have low-reliability in infant period. Some developed systems need tests to improve their reliability up to the respected level before adapting them. This paper aims at showing the testing program including the reliability growth model for reliability improvement of the Light Rail Transit

• Journal of Korean Society for Quality Management
• /
• v.34 no.3
• /
• pp.73-78
• /
• 2006

In this paper, we propose a software reliability growth model based on the testing domain in the software system, which is isolated by the executed test cases in software testing. In particular, our model assumes an imperfect debugging environment in which new faults are introduced in the fault-correction process, and is formulated as a nonhomogeneous Poisson process(NHPP). Further, it is applied to fault-detection data, the results of software reliability assessment are shown, and comparison of goodness-of-fit with the existing software reliability growth model is performed.

• Proceedings of the KSR Conference
• /
• 2005.05a
• /
• pp.187-192
• /
• 2005

Under development program for a complex system, the total system or major subsystems are tested to failure, system failure modes are analyzed, and design and engineering changes are made to eliminate these failure modes. If this TAAF(test-analyze-and-fix) process is continued, and modifications are made in a competent manner, then the system reliability increase. This paper presents the reliability growth theory and applies it to some subsystems during their development and initial production testing. The application of these techniques is a part of the product assurance function that plays an important role in product reliability improvement. In addition, the EN 50126 requires essentially reliability growth for RAM growth monitoring.

• International Journal of Reliability and Applications
• /
• v.7 no.2
• /
• pp.155-166
• /
• 2006

Many software reliability growth models (SRGMs) based on nonhomogeneous Poisson process (NHPP) have been developed and applied in practice. NHPP SRGMs are characterized by their mean value functions. Mean value functions are usually derived from differential equations representing the fault detection/removal process during testing. In this paper such differential equations are regarded as frameworks for generating mean value functions. Currently available frameworks are theoretically discussed with respect to capability of representing the fault detection/removal process. Then two general frameworks are proposed.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.47 no.10
• /
• pp.747-752
• /
• 2019

By using the failure information and the cumulative test execution time obtained by performing the reliability growth test, it is possible to estimate the parameter of the reliability growth model, and the Mean Time Between Failure (MTBF) of the product can be predicted through the parameter estimation. However the failure information could be acquired periodically or the number of sample data of the obtained failure information could be small. Because there are various constraints such as the cost and time of test or the characteristics of the product. This may cause the error of the parameter estimation of the reliability growth model to increase. In this study, the Bayesian method is applied to estimating the parameters of the reliability growth model when the number of sample data for the fault information is small. Simulation results show that the estimation accuracy of Bayesian method is more accurate than that of Maximum Likelihood Estimation (MLE) respectively in estimation the parameters of the reliability growth model.

• The KIPS Transactions:PartD
• /
• v.11D no.7 s.96
• /
• pp.1451-1458
• /
• 2004

Current software reliability growth models based on Gompertz growth curve are all logarithmic type. Software reliability growth models based on logarithmic type Gompertz growth curve has difficulties in parameter estimation. Therefore this paper proposes a software reliability growth model based on the logistic type Gompertz growth curie. Its usefulness is empirically verified by analyzing the failure data sets obtained from 13 different software projects. The parameters of model are estimated by linear regression through variable transformation or Virene's method. The proposed model is compared with respect to the average relative prediction error criterion. Experimental results show that the pro-posed model performs better the models based on the logarithmic type Gompertz growth curve.