• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.125-132
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• 2010

Decision problem called an optimal release policies, after testing a software system in development phase and transfer it to the user, is studied. The applied model of release time exploited infinite non-homogeneous Poisson process. This infinite non-homogeneous Poisson process is a model which reflects the possibility of introducing new faults when correcting or modifying the software. The failure life-cycle distribution used exponential and non-exponential family which has various intensity. Thus, software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement becomes an optimal release policies. In a numerical example, after trend test applied and estimated the parameters using maximum likelihood estimation of inter-failure time data, estimated software optimal release time.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.319-326
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• 2013

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. 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). Statistical process control (SPC) can monitor the forecasting of software failure and thereby 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 logarithmic hazard learning effects property.

• 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.

• Communications for Statistical Applications and Methods
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• v.16 no.5
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• pp.803-812
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• 2009

The application of extreme value theory to financial data is a fairly recent innovation. The classical annual maximum method is to fit the generalized extreme value distribution to the annual maxima of a data series. An alterative modern method, the so-called threshold method, is to fit the generalized Pareto distribution to the excesses over a high threshold from the data series. A more substantial variant is to take the point-process viewpoint of high-level exceedances. That is, the exceedance times and excess values of a high threshold are viewed as a two-dimensional point process whose limiting form is a non-homogeneous Poisson process. In this paper, we apply the two-dimensional non-homogeneous Poisson process model to daily losses, daily negative log-returns, in the data series of KBW/USD exchange rate, collected from January 4th, 1982 until December 31 st, 2008. The main question is how to estimate extreme quantiles of losses such as the 10-year or 50-year return level.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.5
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• pp.345-353
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• 2015

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 parameter inference for software reliability models based on finite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision to market software, the conditional failure rate is an important variables. In this case, finite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outlier, 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 thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, proposed a control mechanism based on NHPP using mean value function of polynomial hazard function.

• International Journal of Reliability and Applications
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• v.3 no.2
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• pp.81-90
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• 2002

The importance of the reliability of software is growing more and more as more complicated digital computer systems are used for real-time control applications. To provide more reliable software, the testing period should be long enough, but not unnecessarily too long. In this study, we suggest a simple but effective stopping rule which can provide just proper amount of testing time. We take unique features of software into consideration and adopt non-homogeneous Poisson process model and Bayesian approach. A numerical example is given to demonstrate the validity of our stopping rule.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.497-506
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• 2007

Coverage-based NHPP SRGMs have been introduced in order to incorporate the coverage growth behavior into the NHPP SRGMs. The coverage growth function representing the coverage growth behavior during testing is thus an essential factor of the coverage-based NHPP SRGMs. This paper proposes a class of discrete time coverage growth functions and illustrates its application to real data sets.

• Proceedings of the Korean Reliability Society Conference
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• 2004.07a
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• pp.207-210
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• 2004

컴퓨터 소프트웨어는 이제 우리의 일상적인 삶에서 필수불가결한 요소이며 시스템의 운용에 중요한 요인이 되었다. 최근에 들어서는 소프트웨어 비용이 하드웨어 비용을 초과하게 되면서 소프트웨어를 개발하는데 필요한 비용과 더불어 소프트웨어 고장에 의한 비용의 중요성이 더 커지게 되었다. 본 논문에서는 Non-Homogeneous Poisson Process(NHPP)에 기초한 소프트웨어 비용 모형을 제안하려고 한다. 개발초기단계에서 출시 전까지의 소프트웨어 개발비용과 테스트비용, 출시이후의 보증기간동안의 제반비용, 소프트웨어 고장에 의한 위험비용 등을 포함하는 소프트웨어 비용 모형을 제안하고 소프트웨어의 최적 출시시기를 결정하는 효과적인 정책을 제시하려고 한다.

• Journal of Satellite, Information and Communications
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• v.10 no.3
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• pp.1-5
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• 2015

Recently, RF energy harvesting technology is a promising technology for small-size IoT(Internet of Things) devices such as sensor to resolve battery scarcity problem. When applied to existing cognitive radio networks, this technology can be expected to increase network throughput through the increase of cognitive user's operating time. This paper proposes a optimal channel-selection policy for RF energy harvesting CR networks model where cognitive users in harvesting zone harvest ambient RF energy from transmission by nearby active primary users and the others in non-harvesting zone choose the channel and communicate with their receiver. We consider that primary users and secondary users are distributed as Poisson point processes and contact with their intended receivers at fixed distances. Finally we can derive the optimal frame duration, transmission power and density of secondary user from the proposed model that can maximize the secondary users's throughput under the given several conditions and suggest future directions of research.

• Journal of Information Technology Applications and Management
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• v.28 no.4
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• pp.13-20
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• 2021

In this paper, I was applied the life distribution following linear failure rate distribution, Lindley distribution and Burr-Hatke exponential distribution extensively used in the arena of software reliability and were associated the reliability possessions of the software using the nonhomogeneous Poisson process with finite failure. Furthermore, the average value functions of the life distribution are non-increasing form. Case of the linear failure rate distribution (exponential distribution) than other models, the smaller the estimated value estimation error in comparison with the true value. In terms of accuracy, since Burr-Hatke exponential distribution and exponential distribution model in the linear failure rate distribution have small mean square error values, Burr-Hatke exponential distribution and exponential distribution models were stared as the well-organized model. Also, the linear failure rate distribution (exponential distribution) and Burr-Hatke exponential distribution model, which can be viewed as an effectual model in terms of goodness-of-fit because the larger assessed value of the coefficient of determination than other models. Through this study, software workers can use the design of mean square error, mean value function as a elementary recommendation for discovering software failures.