• 디지털산업정보학회논문지
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• 제10권4호
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• pp.19-27
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• 2014

Software reliability in the software development process is an important issue. Software process improvement helps in finishing with reliable software product. Infinite 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 reliability model with log type mean value function (Musa-Okumoto and log power 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 log type mean value function was employed. This analysis of failure data compared with log type mean value function. In order to insurance for the reliability of data, Laplace trend test was employed. In this study, the log type model is also efficient in terms of reliability because it (the coefficient of determination is 70% or more) in the field of the conventional model can be used as an alternative could be confirmed. From this paper, software developers have to consider the growth model by prior knowledge of the software to identify failure modes which can be able to help.

• 산업공학
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• 제21권1호
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• pp.109-119
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• 2008

Reliability of embedded softwares, as one of factors which affect system reliability, is the probability of failure-free software operation for a specified period of time in a specified environment. and Embedded software is different from general package software because hardware and operating system are tightly coupled to each other. Reliability evaluation models for embedded softwares currently used do not separate estimation and prediction models clearly, and even a standard model has not been proposed yet. In this respect, we choose a reliability estimation model suitable for embedded softwares among software evaluation models being used, and modified the model so as to accomodate recent software environments. In addtion, based on the model, the web-based reliability prediction tool RPX is developed. Finally, an embedded software is analyzed using the tool.

• Journal of Information Technology Applications and Management
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• 제23권4호
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• pp.117-125
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• 2016

Software reliability in the software development process is an important issue. In infinite failure non-homogeneous Poisson process software reliability models, the failure occurrence rates per fault. can be presented constant, monotonic increasing or monotonic decreasing pattern. In this paper, the reliability software cost model considering decreasing intensity function was studied in the software product testing process. The decreasing intensity function that can be widely used in the field of reliability using power law process, log-linear processes and Musal-Okumoto process were studied and the parameter estimation method was used for maximum likelihood estimation. In this paper, from the software model analysis, we was compared by applying a software failure interval failure data considering the decreasing intensity function The decreasing intensity function model is also efficient in terms of reliability in the arena of the conservative model can be used as an alternating model can be established. From this paper, the software developers have to consider life distribution by preceding information of the software to classify failure modes which can be gifted to support.

• Journal of Information Technology Applications and Management
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• 제24권2호
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• pp.71-80
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• 2017

Software reliability is one of the most elementary and important problems in software development In order to find the software failure occurrence, the instantaneous failure rate function in the Poisson process can have a constant, incremental or decreasing tendency independently of the failure time. In this study, we compared the reliability performance of the software reliability model using the parameters of Pareto life distribution with the intensity decreasing pattern and the shape parameter of Erlang life distribution with the intensity increasing and decreasing pattern in the software product testing. In order to identify the software failure environment, the parametric estimation was applied to the maximum likelihood estimation method. Therefore, in this paper, we compare and evaluate software reliability by applying software failure time data. The reliability of the Erlang and Pareto life models is shown to be higher than that of the Pareto lifetime distribution model when the shape parameter is higher and the Erlang model is more reliable when the shape parameter is higher. Through this study, the software design department will be able to help the software design by applying various life distribution and shape parameters, and providing basic knowledge using software failure analysis.

• 한국신뢰성학회지:신뢰성응용연구
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• 제17권4호
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• pp.296-304
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• 2017

Purpose: Recent weapon systems in defense have increased the complexity and importance of software when developing multifunctional equipment. In this study, we analyze the accuracy of the proposed software reliability model when applied to weapon systems. Methods: Determine the similarity between software reliability analysis results (prediction/estimation) utilizing data from developing weapon systems and system failures data during operation of weapon systems. Results: In case of a software reliability prediction model, the predicted failure rate was higher than the actual failure rate, and the estimation model was consistent with actual failure history data. Conclusion: The software prediction model needs to adjust the variables that are appropriate for the domestic weapon system environment. As the reliability of software is increasingly important in the defense industry, continuous efforts are needed to ensure accurate reliability analysis in the development of weapon systems.

• 한국정보처리학회논문지
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• 제7권7호
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• pp.2076-2085
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• 2000

Almost all existing software reliability models are based on the assumptions of he software usage and software failure process. There, therefore, is no universally applicable software reliability model. To develop a universal software reliability model this paper suggests the predictive filter as a general software reliability prediction model for time domain failure data. Its usefulness is empirically verified by analyzing the failure datasets obtained from 14 different software projects. Based on the average relative prediction error, the suggested predictive filter is compared with other well-known neural network models and statistical software reliability growth models. Experimental results show that the predictive filter generally results in a simple model and adapts well across different software projects.

• 품질경영학회지
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• 제29권4호
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• pp.92-102
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• 2001

Software testing during development and operation should exercise to obtain the desired software quality and leave failure data set. So far, many software reliability models are classified and can be used to measure a software reliability only based on its failure history But, in practice, developers or testers of software systems must decide which existing software reliability model can be fitted. In this paper, we will show that an appropriate reliability model can be selected by considering relations between characteristics of each testing environment and models' assumptions. Several methods of software testing are presented and discussed. Also, unit test, integrated test, function test and system test that are sequentially exercised during development will be introduced.

• 정보교육학회논문지
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• 제2권1호
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• pp.35-51
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• 1998

Software reliability growth model is one of the evaluation methods, software quality which quantitatively calculates the software reliability based on the number of errors detected. For correct and precise evaluation of reliability of certain software, the reliability model, which is considered to fit dose to real data should be selected as well. In this paper, the optimal model for specific test data was selected one of among five software reliability growth models based on NHPP(Non Homogeneous Poission Process), and in result reliability estimating scales(total expected number of errors, error detection rate, expected number of errors remaining in the software, reliability etc) could obtained. According to reliability estimating scales obtained, Software development and predicting optimal release point and finally in conducting systematic project management.

• 한국통신학회논문지
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• 제23권8호
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• pp.1915-1925
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• 1998

교환 시스템이 고장과 장애를 일으키면 서비스에 치명적인 영향을 미치게 된다. 다시 말해서 시스템을 제어하는 교환 소프트웨어의 역할은 매우 중요하다. 그렇기 때문에 정량적인 소프트웨어의 품질 평가 방법은 더욱 중요하다. 본 논문에서는 기능 블록으로 구성된 교환 소프트웨어를 시험하여 얻어진 각종 고장 데이터를 수집, 분석하고 이를 이용하여 각 버전별, 개발 전과정에 대한 소프트웨어 신뢰도를 평가해보고, 기타 고려할 사항에 대해 논한다. 대표적인 2개의 신뢰도 모형(G-O model, S-Shaped model)을 선택하여 소프트웨어 신뢰도를 비교해 보고 품질 향상을 위한 제반 활동과 소프트웨어 개발 프로젝트에 맞는 소프트웨어 신뢰도 모형을 제시하였다.

• 한국정보과학회논문지:소프트웨어및응용
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• 제37권7호
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• pp.536-547
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• 2010

최근 소프트웨어는 고성능의 많은 기능을 제공해야 하기 때문에 그 중요성이 증가할 뿐만 아니라 복잡도 또한 증가하고 있다. 그러므로 신뢰할 만한 소프트웨어를 개발하는 것이 중요한 이슈가 되고 있다. 신뢰할 만한 소프트웨어를 개발하기 위해서는 신뢰성을 초기단계에서부터 관리해야 할 필요성이 있지만 대부분 신뢰성 추정 모델의 경우 시스템 또는 운영 테스트 단계에서 주로 사용되고 있다. 신뢰성 높은 소프트웨어를 개발하기 위해서는 초기 테스트 단계에서부터 개별 유닛의 신뢰성을 관리할 필요성이 있기에 이 단계에서의 특징을 반영해야 한다. 그러나 초기 테스트 단계에서는 개발자와 테스터가 분리되는 것이 아니라 개발자가 테스트뿐만 아니라 디버그까지 함께 수행을 하게 된다. 그렇기 때문에 테스트 시간과 디버그 시간을 모두 고려하는 신뢰성 추정 모델이 필요하다. 본 논문에서는 초기 테스트 단계에서부터 개별 유닛의 신뢰성 관리를 지원하고자 새로운 신뢰성 모델을 제안하였다. 그리고 실제 산업에서 수집된 데이터를 이용하여 제안한 모델이 실제 데이터와 얼마나 일치하는지 그리고 기존 모델과 어떤 차이를 보이는지를 확인하기 위한 실험을 수행하였다.