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

• Journal of KIISE
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• v.42 no.12
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• pp.1551-1560
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• 2015

Software Reliability Growth Models (SRGMs) are used to quantitatively evaluate software reliability and to determine the software release date or additional testing efforts using software failure data. Because a single SRGM is not universally applicable to all kinds of software, the selection of an optimal SRGM suitable to a specific case has been an important issue. The existing methods for SRGM selection assess the goodness-of-fit of the SRGM in terms of the collected failure data but do not consider the accuracy of future failure predictions. In this paper, we propose a method for selecting SRGMs using the trend of failure data and failure prediction ability. To justify our approach, we identify problems associated with the existing SRGM selection methods through experiments and show that our method for selecting SRGMs is superior to the existing methods with respect to the accuracy of future failure prediction.

• The Transactions of the Korea Information Processing Society
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• v.7 no.11
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• pp.3384-3393
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• 2000

소프트웨어를 테스팅하는 동안 얻어지는 고장 데이터를 분석하여 소프트웨어의 신뢰성이 성장하는 과정을 평가하기 위해 여러 가지 소프트웨어 신뢰성 성장 모델들이 개발되었다. 그러나 이들 신뢰성 성장 모델들은 소프트웨어 개발과 사용환경에 관한 여러 가지 가정에 기반하고 있기 때문에, 이 가정이 적합하지 않은 상황이나 결함이 드물게 발생되는 소프트웨어에 대해서는 적절하지 않다. 입력영역에 기초한 소프트웨어 신뢰성 모델은 일반적으로 이러한 가정을 요구하지 않는데 디버깅 전의 소프트웨어와 디버깅 후의 소프트웨어를 별개의 것으로 다루어 많은 테스트 입력을 요하는 단점이 있다. 본 논문에서는 이러한 가정이 요구되지 않고 디버깅 전과 후의 소프트웨어를 동시에 테스트하는 방법에 기반을 둔 입력 영역 기반 소프트웨어 성장모델을 제안하고 그 통계적 특성을 조사한다. 이 모델은 모든 데이터를 다 활용하기 때문에 기존 입력영역 소프트웨어 신뢰성 모델에 비해 적은 테스트 입력을 필요로 할 것으로 기대된다. 그리고 소프트웨어의 유지보수 단계에 적용하기 위해 개발된 유사한 방법들과 비교한다.

• Korean Journal of Materials Research
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• v.9 no.9
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• pp.932-936
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• 1999

4NH(sub)3+$3O_2$$\longrightarrow$$2N_2$+$6H_2$O 의 화학반응식을 가지며$ O_2$ 및 $H_2$O를 산화제로 하는 $NH_3$/$O_2$산화의 성장모델을 세웠으며, 그 결과 Fick의 제 1 법칙을 기초로 하는 건식 및 습식 산화메카니즘으로 이해되는 Deal-Grove의 산화막 성장모델과 유사한 결과가 도출되었다. 이 성장모델에 의하면 산화제$ O_2$ 및 $H_2$O가 상호보완적으로 산화에 영향을 미치므로 산화온도 뿐 아니라 $NH_3$/O$_2$의 유량비도 산화율을 결정한다. rapid thermal processing(RTP)에 의한 산화막 성장실험으로 본 연구에서 제안하는 성장모델을 확인하였으며, NH$_3$분자의 분해에 의해 발생하는 N 원자의 산화막 내부확산을 secondary ion mass spectroscopy(SIMS)로 확인하였으며, Auger electron spectroscopy (AES) 측정결과 N 원자의 존재는 무시할만한 수준이었다.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.349-352
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• 2011

본 논문에서는 변동하중 하에서의 균열 성장 예측을 위하여 손상 모델과 주어진 데이터에 기반하여 균열 성장 모델의 변수를 확률분포로 추정한다. 이를 위해 베이지안 접근법을 활용하여 불확실 변수 결합 확률 분포식을 구축하고, Markov Chain Monte Carlo(MCMC)을 통해서 균열 성장 모델의 변수 샘플을 추출하였다. 여기서 추출된 샘플들을 균열 성장 모델에 적용, 균열 성장의 결과를 확률적인 분포로 예측하였다. 위와 같은 추정은 재료의 물성과 같은 변동성이 있는 변수를 모델에 적용하여, 결과값을 확률적인 분포로 예측하였다. 이것은 기존의 안전계수 개념보다 더욱 적절한 안전 기준을 제시 할 수 있다.

• 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 the Korean Society for Aeronautical & Space Sciences
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• v.31 no.3
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• pp.15-22
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• 2003

The fatigue crack growth model is derived and the retardation model is proposed. The fatigue crack growth model considers the residual plastic stretch on the crack surface which results from the plastic deformation at the tip of fatigue crack. The fatigue crack growth rate is calculated by using the cumulative fatigue damage and plastic strain energy in the material elements at the crack tip. This model gives the crack growth rate in reasonable agreement with test data for aluminum alloy AL6061-T651 and 17-4PH casting steel. The fatigue crack growth retardation model is based on the residual plastic stretch produced from a tensile overload which reduced the plastic strain range of the following load cycles. A strip-yield model of a crack tip plasticity is used for the calculation of a plastic zone size. The proposed retardation model characterized the observed features and delayed retardation of the fatigue crack growth under tensile overload.

• Korean Journal of Environmental Biology
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• v.20 no.4
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• pp.378-385
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• 2002

Growth of Pacific oystey, Crassostrea gigas, in Kamak Bay, Korea was modeled using Von Bertalanffy growth function, seasonal Von Bertalanffy growth function and generalized growth equation of Schnute and Richards' growth model, based on shell length and wet weight frequency data of 9208 oysters. Carrying capacity in the oyster culture ground was also estimated using Schaefer's and Fox's surplus production model. The present results suggest that the generalized growth equation of Schnute and Richards' model is fitter to describe the length growth pattern of C. gigas than Von Bertalanffy growth functions. This results also suggest that the current number of culture facility per unit area in 2000 is similar to the number of facility that produces the maximum production of oyster per unit area.

• Journal of Korea Game Society
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• v.13 no.2
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• pp.49-58
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• 2013

In this study, a tree growth model is designed to represent a variety of trees consisting of a outdoor terrain of game efficiently and naturally. The proposed tree growth model is an integrated tree growth model, and is configured using the following approaches: (1) the tree modeling method based on growth volume and the convolution sums of divisor functions, which is used to model a variety kind of trees more intuitively and naturally; (2) a rendering method using a level of detail of branch based on instancing for real-time processing of numerous trees with complicated structures; and (3) a combination of the above methods to efficiently implement a game landscape. The natural and diverse growths of trees that emerged using the proposed tree growth model is evaluated through experimentation, along with the possibility of implementing the natural game landscape and the efficiency of real-time processing.

• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.597-604
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• 2004

Accurate software cost estimation is essential to both developers and customers. Most of the cost estimating models based on the size measure methods, such as LOC and FP, are obtained through size estimation. The accuracy of size estimation directly influences the accuracy of cost estimation. As a result, the overall structure of regression-based cost models applies the power function based on software size. Many growth phenomenon in nature such as the growth in living organism, performance of technology, and learning capability of human show an S-shaped curve. This paper proposes a model which estimates the developing effort by using the growth curve. The presented model assumes that the relation cost and size follows the growth curve. The appropriateness of the growth curve model based on Function Point, Full-Function Point and Use-Case Point, which are the general methods in estimating the software size have been confirmed. The proposed growth curve model shows similar performance with power function model. In conclusion, the growth curve model can be applied in the estimation of the software cost.