• Title/Summary/Keyword: Finite Failure NHPP

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The Study for ENHPP Software Reliability Growth Model based on Superposition Coverage Function (중첩커버리지 함수를 고려한 ENHPP 소프트웨어 신뢰성장 모형에 관한 연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul
    • Convergence Security Journal
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    • v.7 no.3
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    • pp.7-13
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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-shaped model was reviewed, proposes the superposition model, which maked out efficiency application for software reliability. 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.

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The Comparative Software Cost Model of Considering Logarithmic Fault Detection Rate Based on Failure Observation Time (로그형 관측고장시간에 근거한 결함 발생률을 고려한 소프트웨어 비용 모형에 관한 비교 연구)

  • Kim, Kyung-Soo;Kim, Hee-Cheul
    • Journal of Digital Convergence
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    • v.11 no.11
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    • pp.335-342
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    • 2013
  • In this study, reliability software cost model considering logarithmic fault detection rate based on observations from the process of software product testing was studied. Adding new fault probability using the Goel-Okumoto model that is widely used in the field of reliability problems presented. When correcting or modifying the software, finite failure non-homogeneous Poisson process model. For analysis of software cost model considering the time-dependent fault detection rate, the parameters estimation using maximum likelihood estimation of inter-failure time data was made. In this research, Software developers to identify the best time to release some extent be able to help is considered.

The Study for ENHPP Software Reliability Growth Model Based on Kappa(2) Coverage Function (Kappa(2) 커버리지 함수를 이용한 ENHPP 소프트웨어 신뢰성장모형에 관한 연구)

  • Kim, Hee-Cheul
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.12
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    • pp.2311-2318
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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 Release times 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-shaped model was reviewed, proposes the Kappa coverage model, which make out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE statistics and Kolmogorov distance, for the sake of efficient model, was employed. Numerical examples using real data set for the sake of proposing Kappa coverage model was employed. This analysis of failure data compared with the Kappaa coverage model and the existing model(using arithmetic and Laplace trend tests, bias tests) is presented.

Comparative Evaluation on the Cost Analysis of Software Development Model Based on Weibull Lifetime Distribution (와이블 수명분포에 근거한 소프트웨어 개발모형의 비용 분석에 관한 비교 평가)

  • Bae, Hyo-Jeong
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.3
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    • pp.193-200
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    • 2022
  • In this study, the finite-failure NHPP software reliability model was applied to the software development model based on the Weibull lifetime distribution (Goel-Okumoto, Rayleigh, Type-2 Gumbe), which is widely used in the software reliability field, and then the cost attributes were compared and evaluated. For this study, failure time data detected during normal operation of the software system were collected and used, the most-likelihood estimation (MLE) method was applied to the parameter estimation of the proposed model, and the calculation of the nonlinear equation was solved using the binary method. As a result, first, in the software development model, when the cost of testing per unit time and the cost of removing a single defect increased, the cost increased but the release time did not change, and when the cost of repairing failures detected during normal system operation increased, the cost increased and the release time was also delayed. Second, as a result of comprehensive comparative analysis of the proposed models, it was found that the Type-2 Gumble model was the most efficient model because the development cost was lower and the release time point was relatively faster than the Rayleigh model and the Goel-Okumoto basic model. Third, through this study, the development cost properties of the Weibull distribution model were newly evaluated, and the analyzed data is expected to be utilized as design data that enables software developers to explore the attributes of development cost and release time.

The Comparative Software Reliability Cost Model of Considering Shape Parameter (형상모수를 고려한 소프트웨어 신뢰성 비용 모형에 관한 비교 연구)

  • Kim, Kyung-Soo;Kim, Hee-Cheul
    • Journal of Digital Convergence
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    • v.12 no.3
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    • pp.219-226
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    • 2014
  • In this study, reliability software cost model considering shape parameter based on life distribution from the process of software product testing was studied. The shape parameter using the Erlang and Log-logistic model that is widely used in the field of reliability problems presented. The software failure model was used finite failure non-homogeneous Poisson process model, the parameters estimation using maximum likelihood estimation was conducted. In comparison result of software cost model based on the Erlang distribution and the log-logistic distribution software cost model, because Erlang model is to predict the optimal release time can be software, but the log-logistic model to predict to optimal release time can not be, Erlang distribution than the log-logistic distribution appears to be effective. In this research, software developers to identify software development cost some extent be able to help is considered.