• 제목/요약/키워드: Software reliability function

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소프트웨어 신뢰성 모델링 기반 소프트웨어 품질 측정 (The software quality measurement based on software reliability model)

  • 정혜정
    • 한국융합학회논문지
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    • 제10권4호
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    • pp.45-50
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    • 2019
  • 본 연구는 소프트웨어 신뢰성을 측정하기 위해 소프트웨어 신뢰도 측정 모형에 따라 소프트웨어 신뢰도를 측정하는 방법을 제시하려 한다. 본 연구에서 제시한 모형의 형태는 비동질적 포아송 과장의 분포를 이용하였으며, 제시된 모형의 소프트웨어 신뢰도를 측정하는 방안을 제시하였다. 제시된 모형에 따라서 적합한 소프트웨어 신뢰도 성장 모형을 선택하는 방법으로는 소프트웨어 고장 데이터에 따라서 신뢰도 함수의 추정 값에 따른 평균제곱오차를 계산하여 적합한 소프트웨어 신뢰도 함수를 제안하는 방법을 연구하였다. 본 연구에서는 소프트웨어 품질을 측정하기 위한 신뢰도 함수를 제안하기 위하여 모델을 제시하고 고장데이터를 적용하여 추정 값의 오차를 최소화하는 관점에서 소프트웨어 신뢰도 함수를 선택할 수 있는 방안을 제시한 연구로 판단된다.

Modelling the Failure Rate Function in Coverage and Software Reliability Growth

  • Park, Joong-Yang;Kim, Young-Soon;Park, Jae-Heung
    • International Journal of Quality Innovation
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    • 제5권1호
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    • pp.110-121
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    • 2004
  • There is a new trend of incorporating software coverage metrics into software reliability modelling. This paper proposes a coverage-based software reliability growth model. Firstly, the failure rate function in coverage is analytically derived. Then it is shown that the number of detected faults follows a Nonhomogeneous Poisson distribution of which intensity function is the failure rate function in coverage. Practical applicability of the proposed models is examined by illustrative numerical examples.

강도함수가 감소패턴을 따르는 NHPP 소프트웨어 신뢰모형에 관한 비교 연구 (A Comparative Study on Software Reliability Model for NHPP Intensity Function Following a Decreasing Pattern)

  • 김희철;김정범;문송철
    • 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.

로그형 평균값함수를 고려한 소프트웨어 신뢰성모형에 대한 비교연구 (A Comparative Study of Software Reliability Model Considering Log Type Mean Value Function)

  • 신현철;김희철
    • 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.

A software reliability model with a Burr Type III fault detection rate function

  • Song, Kwang Yoon;Chang, In Hong;Choi, Min Su
    • International Journal of Reliability and Applications
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    • 제17권2호
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    • pp.149-158
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    • 2016
  • We are enjoying a very comfortable life thanks to modern civilization, however, comfort is not guaranteed to us. Development of software system is a difficult and complex process. Therefore, the main focus of software development is on improving the reliability and stability of a software system. We have become aware of the importance of developing software reliability models and have begun to develop software reliability models. NHPP software reliability models have been developed through the fault intensity rate function and the mean value functions within a controlled testing environment to estimate reliability metrics such as the number of residual faults, failure rate, and reliability of the software. In this paper, we present a new NHPP software reliability model with Burr Type III fault detection rate, and present the goodness-of-fit of the fault detection rate software reliability model and other NHPP models based on two datasets of software testing data. The results show that the proposed model fits significantly better than other NHPP software reliability models.

TRUNCATED SOFTWARE RELIABILITY GROWTH MODEL

  • Prince Williams, D.R.;Vivekanandan, P.
    • Journal of applied mathematics & informatics
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    • 제9권2호
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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 .

로지스틱 테스트 노력함수를 이용한 소프트웨어의 최적인도시기 결정에 관한 연구 (A Study on the Optimal Release Time Decision of a Developed Software by using Logistic Testing Effort Function)

  • 최규식;김용경
    • Journal of Information Technology Applications and Management
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    • 제12권2호
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    • pp.1-13
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    • 2005
  • This paper proposes a software-reliability growth model incoporating the amount of testing effort expended during the software testing phase after developing it. The time-dependent behavior of testing effort expenditures is described by a Logistic curve. 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 curve 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.

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소프트웨어 신뢰도의 적정 파라미터 도출 기법에 관한 연구 (A Study on the Optimum Parameter Estimation of Software Reliability)

  • 최규식;문명호
    • Journal of Information Technology Applications and Management
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    • 제13권4호
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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.

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다기능레이더 소프트웨어 신뢰성시험 적용사례 및 결과 (A Case Study on Reliability Test of Embedded Software in the Multi-Function Radar)

  • 김종우
    • 전기전자학회논문지
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    • 제19권3호
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    • pp.431-439
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    • 2015
  • 최근 무기체계에서 소프트웨어가 담당하는 기능이 많아지고, 복잡해지면서 소프트웨어의 품질의 중요성에 대해서 대두가 되고 있다. 소프트웨어의 품질요소는 기능성, 사용성, 유지보수성, 신뢰성이 있으며, 이중 최근 들어 중요시되는 항목이 신뢰성 분야이다. 신뢰성 시험은 분석을 통한 정적 시험과 수행을 통한 동적 시험방법이 있으며, 실수행을 통해 검증하는 동적시험은 정적시험에 비해 많은 기간이 필요하며 복잡성이 높아질 경우 더욱 증가되는 경향을 보인다. 본 논문에서는 다기능 레이더 소프트웨어 개발시 수행한 신뢰성시험 절차 및 결과를 기술하고 이를 통해 효과적으로 시험기간을 줄일 수 있는 신뢰성시험 방법을 제안한다.

Parameter Estimation and Prediction for NHPP Software Reliability Model and Time Series Regression in Software Failure Data

  • Song, Kwang-Yoon;Chang, In-Hong
    • 통합자연과학논문집
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    • 제7권1호
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    • pp.67-73
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    • 2014
  • We consider the mean value function for NHPP software reliability model and time series regression model in software failure data. We estimate parameters for the proposed models from two data sets. The values of SSE and MSE is presented from two data sets. We compare the predicted number of faults with the actual two data sets using the mean value function and regression curve.