• Journal of the Korea Society of Computer and Information
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• v.1 no.1
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• pp.195-210
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• 1996

For predicting the parameters and estimating the goodness of fit reliability growth model based on NHPP(Non Homogeneous Poission Process) among various reliability growth models, a Delayed S Shaped SRGM Tool is designed and Implemented. The Implemented tool is applied to real software error data, and the result Is compared and annalized.

• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.409-420
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• 2001

Recently a new approach to evaluation of software reliability, one of important attributes of a software system, during testing has been devised. This approach utilizes test coverage information. The coverage-based software reliability growth models recently appeared in the literature are first reviewed and classified into two classes. Inherent problems of each of the two classes are then discussed and their validity is empirically investigated. In addition, a new mean value function in coverage and a heuristic procedure for selecting the best coverage are proposed.

• The Korean Journal of Applied Statistics
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• v.23 no.3
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• pp.573-584
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• 2010

This paper considers the differences in the software execution environments in the testing phase and the operational phase to determine the optimal release time and warranty period of software systems. We formulate equations for the total expected software cost until the end of the software life cycle based on the NHPP. In addition, we derive the optimal release time that minimizes the total expected software cost for an imperfect debugging software reliability model. Finally, we analyze the sensitivity of the optimal testing and maintenance design related to variation of the cost model parameters based on the fault data observed in the actual testing process, and discuss the quantitative properties of the proposed model.

• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.387-392
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• 2001

This Many software projects collect grouped failure data (failures in some failure interval or in variable time interval) rather than individual failure times or failure count data during the testing or operational phase. This paper presents the neural network (NN) modeling for grouped failure data that is able to predict cumulative failures in the variable future time. The two variant models of cascade-correlation learning (CasCor) algorithm are presented. Suggested models are compared with other well-known NN models and statistical software reliability growth models (SRGMs). Experimental results show that the suggested models show better predictability.

• The Journal of Fisheries Business Administration
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• v.33 no.2
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• pp.75-98
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• 2002

As a contribution to developing fishery stock assessment, optimum sustainable yield and its international standards such as MSY, MEY, and dynamic MEY for six recommended fisheries are developed using bio-economic models. For selecting the appropriate model, five models - Schaefer, Schnute, Walters and Hilborn, Fox, and CY&P models are tested in effort and catch data of six species. Surprisingly all the models except the CY&P model failed to satisfy statistical standards such as goodness-of-fitness and reliability. Generally, the CY&P model holds good fitness and statistically significant level for all of six fisheries. However, the CY&P model for squid, where the intrinsic growth rate is high, could not explain MSY, MEY, and dynamic MEY appropriately. This study makes a contribution to develop the modified model for the intrinsic growth rate of 1. The reformulated model represents the results reasonably even though the estimated equation has not good fitness. Although most of the CY&P models appear to have good fits and validated results for some cases, these models also seem to be quite sensitive to parameters which means a more stable model should be developed and data should carefully be handled. In particular biological and technical interactions such as multispecies, predator prey relationship, age structure and mortality should be taken into account. In addition, economic factors and fishing efforts such as price, cost, technical change and a reasonable function of fishing input should simultaneously be considered.

• International Journal of Reliability and Applications
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• v.2 no.3
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• pp.147-160
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• 2001

The reliability of computer software is of prime importance for all developers of software. The complicated nature of detecting and removing faults from software has led to a plethora of models for reliability growth. One of the most basic of these is the Jelinski Moranda model, where it is assumed that there are N faults in the software, and that in testing, bugs (or faults) are encountered (and removed when defected) according to a stochastic process at a rate which at a given point in time is proportional to the number of bugs remaining in the system. In this research, we consider the possibility that imperfect repair may occur in any attempt to remove a detected bug in the Jelinski Moranda model. We let p represent the probability that a fault which is discovered or detected is actually perfectly repaired. The possibility that the probability p may differ before and after release of the software is also considered. The distribution of both the number of bugs detected and perfectly repaired in a given time period is studied. Cost models for the development and release of software are investigated, and the impact of the parameter p on the optimal release time minimizing expected costs is assessed.

• Journal of Information Technology Applications and Management
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• v.13 no.4
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• pp.1-12
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• 2006

Many software reliability growth models(SRGM) have been proposed since the software reliability issue was raised in 1972. The technology to estimate and grow the reliability of developing S/W to target value during testing phase were developed using them. Most of these propositions assumed the S/W debugging testing efforts be constant or even did not consider them. A few papers were presented as the software reliability evaluation considering the testing effort was important afterwards. The testing effort forms which have been presented by this kind of papers were exponential, Rayleigh, Weibull, or logistic functions, and one of these 4 types was used as a testing effort function depending on the S/W developing circumstances. I propose the methology to evaluate the SRGM using least square estimator and maximum likelihood estimator for those 4 functions, and then examine parameters applying actual data adopted from real field test of developing S/W.

• The Korean Journal of Applied Statistics
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• v.21 no.5
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• pp.813-823
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• 2008

The non-homogeneous Poisson process(NHPP) based software reliability growth models are proved quite successful in practical software reliability engineering. The fault detection rate is usually assumed to be the continuous and monotonic function. However, the fault detection rate can be affected by many factors such as the testing strategy, running environment and resource allocation. This paper describes a parameter estimation of software reliability growth model with change-point problem. We obtain the maximum likelihood estimate(MLE) and least square estimate(LSE), and compare goodness-of-fit.

• International Journal of Reliability and Applications
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• v.2 no.4
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• pp.269-280
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• 2001

The objective of this paper is to provide a model for effective implementation of costing RAM management in the design and procurement of production facility considering the system cost-performance trade-off. This research proposes a two-step approach of costing RAM design and test of system RAM for production facility. In Step 1, a static model is proposed to find an initial system configuration to meet the required performance based on system RAM and LCC and analyzes the trade-off relationships between various factors of RAM and LCC. In the second Step, we developed time and failure truncated models for system reliability test and analysis. For the computational purpose, we developed computer programs and have shown the sample results. By the sample test run, the proposed model has shown the possibilities to provide a good method to analyze system performance evaluation for both design and operational phase, This model can be applied to a wide variety of systems not only for costing RAM of the production facilities but also for the other kinds of equipment.

• Structural Engineering and Mechanics
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• v.17 no.1
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• pp.29-50
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• 2004

A total life model was developed to assess the service life of aging aircraft. The primary focus of this paper is the development of crack growth life projection using the response surface method. Crack growth life projection is a necessary component of the total life model. The study showed that the number of load cycles N needed for a crack to propagate to a specified size can be linearly related to the geometric parameter, material, and stress level of the component considered when all the variables are transformed to logarithmic values. By the Central Limit theorem, the ln N was approximated by Gaussian distribution. This Gaussian model compared well with the histograms of the number of load cycles generated from simulated crack growth curves. The outcome of this study will aid engineers in designing their crack growth experiments to develop the stochastic crack growth models for service life assessments.