• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.67-69
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• 2003

소프트웨어 시스템을 집적하는데 있어서 컴퍼넌트 중심의 소프트웨어 개발 접근 방법이 큰 경향이다. 집적 소프트웨어 시스템의 전체 신뢰도를 확보하기 위해 소프트웨어 컴퍼넌트의 테스트 및 자원의 유한성 내에서 소프트웨어가요하는 조건을 만족해야만 한다. 기지의 비용, 신뢰도, 테스트 노력, 시스템 컴퍼넌트의 기타 다른 공헌 인자를 가지고 순열조합의 최적화 문제로서 시스템 테스트의 최적화 문제 효율을 공식화할 수 있다. 본 연구에서는 그 각각이 사전에 명세화한 신뢰도 요건을 가진 단일 또는 다중 실용화 시스템에 대한“소프트웨어 컴퍼넌트 테스트 자원 할당”을 고려한다. 이것은 내고장(fault-tolerant) 시스템에도 확장해서 실용화할 수 있다. 테스트 자원 할당문제에 체계적으로 접근하는 절차를 논하고자 한다.

• Journal of applied mathematics & informatics
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• v.9 no.2
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• pp.761-769
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• 2002

Due to the large scale application of software systems, software reliability plays an important role in software developments. In this paper, a software reliability growth model (SRGM) is proposed. The testing time on the right is truncated in this model. The instantaneous failure rate, mean-value function, error detection rate, reliability of the software, estimation of parameters and the simple applications of this model are discussed .

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.192-196
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• 2007

그동안 소프트웨어의 신뢰도가 테스트중은 물론 운영중에도 고장을 검출 및 수벙함으로써 성장될 수 있다는 가정 하에 SRGM이 연구되어왔다. 한편, 어떤 논문에서는 운영중에 소프트웨어를 수정한다는 것이 특히 범용 소프트웨어인 경우 불가능에 가깝기 때문에 테스트노력이 일정한 것으로 가정하기도 하였다.. 저자는 소프트웨어의 신뢰도 현상에 접근할 수 있는 단순한 기법을 제안하여 기존신뢰도 모델을 수정하지 않고 고장률을 줄일 수 있도록 하는 방안을 제시한다.

• Journal of Applied Reliability
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• v.1 no.2
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• pp.175-181
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• 2001

Recently, the quality of software has become a major issue. The statistical models used in making predictions about the quality of software are termed software reliability growth models (SRGM). However, the existing SRGMs have not been satisfactory in predicting software reliability behavior (Keiller and Miller(1991), Keiller and Littlewood(1984), Musa(1987)). In this paper, we present a fuzzy-based interval estimation of software errors (failures).

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.5
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• pp.264-268
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• 2000

In discuss how the existing study results that decide optimum release time are rational and reasonable, considering the cost and reliability simultaneously in this paper. As a study method this paper examines the proposed results and their methodologies centering around the existing related papers for the general cost-reliability optimal release policies, especially their limitation for the derived results.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.1
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• pp.1-9
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• 2008

The Logistic cone is studied as a most desirable for the software testing effort. Assuming that the error detection rate to the amount of testing effort spent during the testing phase is proportional to the current error content, a software-reliability growth model is formulated by a nonhomogeneous Poisson process. Using this model the method of data analysis for software reliability measurement is developed. After defining a software reliability, This paper discusses the relations between testing time and reliability and between duration following failure fixing and reliability are studied SRGM in several literatures has used the exponential curve, Railleigh curve or Weibull cure as an amount of testing effort during software testing phase. However, it might not be appropriate to represent the consumption curve for testing effort by one of already proposed curves in some software development environments. Therefore, this paper shows that a logistic testing- effort function can be adequately expressed as a software development/testing effort curve and that it gives a good predictive capability based on real failure data.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.1109-1112
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• 2005

The software reliability is defined, and not only the relations between testing time and reliability, but also the relation between duration following failure fixing and reliability are studied in this paper. The release time making the testing cost to be minimum is determined through evaluating the cost for each condition. Also, the release time is determined depending on the conditions of the first reliability, considering the specified reliability. The optimum release time is determined by simultaneously studying two optimum release time issues that determine both the cost related time and the specified reliability related time. And, each condition and limitation are studied. The trend of the optimum time is also examined.

• Journal of Information Technology Applications and Management
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• v.11 no.2
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• pp.191-204
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• 2004

Many software reliability growth model(SRGM) have been proposed for past several decades. 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. We consider the methology to evaluate the SRGN using least square estimator(LSE) and maximum likelihood estimator(MLE) for those 4 functions, and then examine parameters applying actual data adopted from real field test of developing S/W.

• 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.