• 한국통신학회논문지
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• 제29권4A호
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• pp.399-414
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• 2004

In this paper, an evolution of software reliability engineering in a large-scale software project is summarized. The considered software consists of many components, called functional blocks in software of switching system. These functional blocks are served as the unit of coding and test, and the software is continuously updated by adding new functional blocks. We are mainly concerned with the analysis of the effects of these software components in software reliability and reliability evolution. We analyze the static characteristics of the software related to software reliability using collected failure data during system test. We also discussed a pattern which represents a local and global growth of the software reliability as version evolves. To find the pattern of system software, we apply the S-shaped model to a collection of failure data sets of each evolutionary version and the Goel-Okumoto(G-O) model to a grouped overall failure data set. We expect this pattern analysis will be helpful to plan and manage necessary human/resources fur a new similar software project which is developed under the same developing circumstances by estimating the total software failures with respect to its size and time.

• 디지털산업정보학회논문지
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• 제10권2호
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• pp.29-36
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• 2014

Finite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, proposes the Gompertz distribution reliability model, which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on mean square error (MSE) and coefficient of determination$(R^2)$, for the sake of efficient model, was employed. Analysis of failure using real data set for the sake of proposing fixed shape parameter of the Gompertz distribution was employed. This analysis of failure data compared with the Gompertz distribution model of shape parameter. In order to insurance for the reliability of data, Laplace trend test was employed. In this study, the proposed Gompertz model is more efficient in terms of reliability in this area. Thus, Gompertz model can also be used as an alternative model. From this paper, software developers have to consider the growth model by prior knowledge of the software to identify failure modes which can was helped.

• 한국정보처리학회논문지
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• 제3권2호
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• pp.231-241
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• 1996

지금까지 많은 소프트웨어 신뢰도 성장 모델들의 제안되어 왔으나 현상을 완전히 고려한 소프트웨어 신뢰도 모델은 아직 개발되어 있지 못한 실정이다. 따라서 다양한 소프트웨어 신뢰도 모델이 계속 개발되어 모든 현상을 고려할 수 있는 모델의 개발이 필요하다고 볼 수 있다. 이와 같은 목적하에 본 논문에서는 발견되는 오류를 오류의 특성에 따라 3종류로 분류하였고, 또한 각 오류의 분류된 오류의 발견 시점 등을 고려 하여 소프트웨어의 신뢰도를 측정할 수 있는 신뢰도 모델을 제안하였다. 그리고모델의 파라메타의 추정 및 신뢰성 평가를 위해실측 데이타를 이용하여 고찰하였으며, 본 논문의 적합성을 검증하기 위해 기존의 모델과 비교 분석 하였다.

• 정보학연구
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• 제10권2호
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• pp.47-64
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• 2007

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. Accurate predictions of software release times, and estimation of the reliability and availability of a software product require quantification of a critical element of the software testing process : test coverage. This model called enhanced non-homogeneous poission process(ENHPP). In this paper, exponential coverage and S-coverage model was reviewed, proposes the exponentiated exponential coverage reliability model, which maked out efficiency substituted for gamma and Weibull model(2 parameter shape illustrated by Gupta and Kundu(2001). In this analysis of software failure data, algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE statistics for the sake of efficient model, was employed.

• 전자통신동향분석
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• 제14권4호통권58호
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• pp.1-9
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• 1999

In this paper, we summarize the lessons learned from the applications of the software reliability engineering to a large-scale software project. The considered software is the software system of the TDX-10 ISDN switching system. The considered software consists of many components, called functional blocks. These functional blocks serve as the unit of coding and test. The software is continuing to be developed by adding new functional blocks. We are mainly concerned with the analysis of the effects of these software components to software reliability and with the analysis of the reliability evolution. We analyze the static characteristics of the software related to software reliability using failure data collected during system test. We also discussed a pattern which represents a local and global growth of the software reliability as version evolves. To find the pattern of software of the TDX-10 ISDN system, we apply the S-shaped model to a collection of failure data sets of each evolutionary version and the Goel-Okumoto (G-O) model to a grouped overall failure data set. We expect this pattern analysis will be helpful to plan and manage necessary human/resources for a new similar software project which is developed under the same developing circumstances by estimating the total software failures with respect to its size and time.

• 응용통계연구
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• 제21권5호
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• pp.813-823
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• 2008

비동질적 포아송과정(NHPP) 모형은 신뢰성 공학에서 소프트웨어 내에 남아있는 결함발견현상을 설명하는데 자주 사용된다. 이때 결함발견율은 연속적이며 단조함수를 가정하였으나 현실적으로 소프트웨어 시험환경, 전략 및 자원할당 등으로 인해 결함발견율이 변하는 경우가 있다. 본 논문은 결함발견율이 변화하는 변화점 문제를 고려한 소프트웨어 신뢰도 성장모형(SRGM)을 고려하여 모수를 추정하는데 목적이 있다. 이를 위해 자료를 모의 생성한 후 평균값 함수의 각 모수를 최우추정법과 최소제곱법을 이용하여 추정하며, 결함발견구간이 일정하게 증가하는 경우와 일정하게 증가하지 않는 경우를 각각 고려한다. 이때 각 모수의 적합도 비교 평가를 통하여 변화점을 고려한 SRGM에서의 최적 추정법을 수치적 방법으로 판단한다.

• 정보처리학회논문지D
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• 제9D권3호
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• pp.389-398
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• 2002

본 논문에서는 비동질 포아송 과정에 기초한 소프트웨어 오류 현상에 대한 신뢰도 모형을 고려하고 사전정보를 이용한 베이지안 추론을 시행하였다. 고장 패턴은 NHPP에 대한 강도함수와 평균값 함수로서 나타낼 수 있다. 따라서 본 논문에서는 기존의 모형인 Goel이 제시한 모형과 신뢰성 분포로 많이 사용되는 와이블 분포의 특수형태인 레일리분포와 라플라스 분포를 이용한 모형을 제시하여 베이지안 추론을 시행하고 또, 효율적 모형을 위한 모형선택으로서 편차자승합을 이용하여 비교하였다. 모수의 추정을 위해서 마코브체인 몬테카를로 기법중에 하나인 깁스샘플링을 이용한 근사추정 기법이 사용되었다. 수치적인 예에서는 실측자료인 NTDS 자료를 이용하여 모수 및 신뢰도를 추정하였고 편차자승합을 이용한 모형비교의 결과를 나열하였다.

• 산업경영시스템학회지
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• 제18권33호
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• pp.119-122
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• 1995

Application of the PWFRM and SRGM for software reliability Prediction offers not only the judging base of model but also themselves with good applicabilty as easy-to-use tool.

• 대한산업공학회지
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• 제33권4호
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• pp.487-493
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• 2007

In this paper, we deal with an optimal software-release problem of determining the time to stop testing and release the software system to the user. The optimal release time problem is considered from maintenance like the periodic distribution of service packs and the unpredictable distribution of patches after the release. Moreover, the environment of software error-detection during operation differs from the environment during testing. This paper proposes the software reliability growth model which incorporates periodic service packs, unpredictable patches and operational environment. Based on the proposed model, we derive optimal release time to minimize total cost composed of fixing an error, testing and maintenance. Using numerical examples, optimal release time is determined and illustrated.

• 한국신뢰성학회지:신뢰성응용연구
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• 제14권4호
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• pp.225-229
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• 2014

A one-shot device is defined as a product, system, weapon, or equipment that can be used only once. After use, the device is destroyed or must undergo extensive rebuild. Determining the reliability of a one-shot device poses a unique challenge to the manufacturers and users due to the destructive nature and costs of the testing. This paper presents a reliability growth prediction for a one-shot system. It is assumed that 1) test duration is discrete(i.e. trials or rounds); 2) trials are statistically independent; 3) the number of failures for a given system configuration is distributed according to a binomial distribution; and 4) the cumulative expected number of failures through any sequence of configurations is given by AMSAA model. When the system development is represented by three configurations and the number of trials and failures during configurations are given, the AMSAA model parameters and reliability at configuration 3 are estimated by using a reliability growth analysis software. Further, if the reliability growth predictions do not meet the target reliability, the sample size of an additional test is determined for achieving the target reliability.