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

• Journal of Industrial Convergence
• /
• v.18 no.3
• /
• pp.19-25
• /
• 2020

In the software development process, software reliability evaluation is a very important issue. In particular, finding the optimal development model that satisfies high reliability is the more important task for software developers. For this, in this study, Pareto and Erlang life distributions were applied to the finite failure NHPP model to evaluate the reliability attributes. For this purpose, parametric estimation is applied to the maximum likelihood estimation method, and nonlinear equations are calculated using the bisection method. As a result, the Erlang model showed better performance than the Pareto model in the evaluation of the strength function and the mean value function. Also, as a result of inputting future mission time and evaluating reliability, the Erlang model showed an effectively high trend together with the Pareto model, while the Goel-Okumoto basic model showed a decreasing trend. In conclusion, the Erlang model is the best model among the proposed models. Through this study, it is expected that software developers will be able to use it as a basic guideline for exploring and evaluating the optimal software reliability model.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.5 s.43
• /
• pp.9-18
• /
• 2006

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the exponentiated exponential distribution reliability model, which maked out efficiency substituted for gamma and Weibull model(2 parameter shape illustrated by Gupta and Kundu(2001) Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE, AIC statistics and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using NTDS data set for the sake of proposing shape parameter of the exponentiated exponential distribution was employed. This analysis of failure data compared with the exponentiated exponential distribution model and the existing model (using arithmetic and Laplace trend tests, bias tests) is presented.

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

• Convergence Security Journal
• /
• v.12 no.6
• /
• pp.3-10
• /
• 2012

In this paper, make a study decision problem called an optimal release policies after testing a software system in development phase and transfer it to the user. When correcting or modifying the software, finite failure non-homogeneous Poisson process model, considering learning factor, presented and propose release policies of the life distribution, log linear type model which used to an area of reliability because of various shape and scale parameter. In this paper, discuss optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement. In a numerical example, the parameters estimation using maximum likelihood estimation of failure time data, make out estimating software optimal release time.

• Journal of the Korea Society of Computer and Information
• /
• v.12 no.6
• /
• pp.89-96
• /
• 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 quality 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-type model was reviewed, proposes modified(the superosition and mixture) 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 for the sake of efficient model, was employed.

• Convergence Security Journal
• /
• v.7 no.3
• /
• pp.7-13
• /
• 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.

• Journal of IKEEE
• /
• v.9 no.2 s.17
• /
• pp.143-151
• /
• 2005

Finite failure NHPP models proposed in the literature exhibit is either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. For the sake of proposing shape parameter of the Gamma family distribution, used the special pattern. Data set, where the underlying failure process could not be adequately described by the knowing models, which motivated the development of the Gamma or Weibull model and Gompertz model. Analysis of failure data set that led us to the Gamma or Weibull model and Gompertz model using arithmetic and Laplace trend tests, bias tests was presented in this Paper.

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

• Convergence Security Journal
• /
• v.7 no.2
• /
• pp.1-8
• /
• 2007

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault (intensity function). In this paper, intensity function of Goel-Okumoto model was reviewed, proposes Kappa (2) and the Burr distribution, which maked out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method. For model determination and selection, explored goodness of fit (the error sum of squares) The methodology developed in this paper is exemplified with a software reliability real data set introduced by NTDS (Naval Tactical Data System)