• Journal of Digital Convergence
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• v.12 no.12
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• pp.277-284
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• 2014

The NHPP software reliability models for failure analysis can have, in the literature, exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, finite failure NHPP models that assuming the expected value of the defect and infinite failures NHPP models that repairing software failure point in time reflects the situation, were presented for comparing property. Commonly used in the field of software reliability based on Rayleigh distribution software reliability model finite failures and infinite failures were presented for comparison problem. As a result, infinite fault model is effectively finite fault models, respectively. The parameters estimation using maximum likelihood estimation was conducted. In this research, can be able to help software developers for considering software failure property some extent.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.4
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• pp.351-358
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• 2016

Science and technology is developing rapidly as more powerful software with the rapid development of software testing and reliability assessment by the difficulty increases with the complexity of the software features of the larger increases NHPP software reliability models for failure analysis can have, in the literature, exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, finite failure NHPP models that assuming the expected value of the defect and infinite failures NHPP models that repairing software failure point in time reflects the situation, were presented for comparing property. Commonly used in the field of software reliability based on Erlang distribution software reliability model finite failures and infinite failures were presented for performance comparative evaluation problem. As a result, finite failure model is better than infinite failure model effectively. The parameters estimation using maximum likelihood estimation in the course of this study was conducted. As the results of this research, software developers to identify software failure property be able to help is concluded.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.3
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• pp.195-202
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• 2015

NHPP software reliability models for failure analysis can have, in the literature, exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, finite failure NHPP models that assuming the expected value of the defect and infinite failures NHPP models that repairing software failure point in time reflects the situation, were presented for comparing property. Commonly used in the field of software reliability based on exponential power distribution software reliability model finite failures and infinite failures were presented for comparison problem. As a result, finite fault model is effectively infinite fault models, respectively. The parameters estimation using maximum likelihood estimation was conducted. In this research, software developers to identify software failure property some extent be able to help is considered.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.361-364
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• 2005

본 논문에서는 순서 통계량을 이용한 유한 고장 NHPP 모형들이 제안되었다. 이 모형들은 결함당 고장발생률이 단조 증가하거나 단조 감소하는 패턴을 가진다. 그리고 수명 분포에서는 기존의 모형들과 비교하고 kappa(2) 분포를 이용한 소프트웨어 신뢰성 모형을 제안하여 이 모형의 특성과 효율성에 대하여 제시하였다. 고장 간격 시간 자료를 이용한 무한고장 NHPP 모형들에 대한 모수 추정은 최우 추정법을 사용하였고 적용 분포들의 적용을 용이하게 하기 위하여 특수한 형태를 제시하였다. 실제고장 자료를 이용한 자료분석에서는 편차자승합을 이용한 모형 선택과 적합도 및 치우침 검정을 실시하여 그 결과를 나열 하였다.

• Convergence Security Journal
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• v.12 no.6
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• pp.85-92
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• 2012

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do asymptotic likelihood inference for software reliability models based on infinite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The finite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outliers, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical Process Control (SPC) can monitor the forecasting of software failure and there by contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, we proposed a control mechanism based on NHPP using mean value function of log Poission, log-linear and Parto distribution.