Hee-Cheul Kim

The Comparative Software Cost Model of Considering Logarithmic Fault Detection Rate Based on Failure Observation Time

Abstract 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. Key Words : Logarithmic Fault Detection Rate, Software Release Policy, NHPP, Cost Model, Goel-Okumoto Model Received 2 September 2013, Revised 25 September 2013Accepted 20 November 2013Corresponding Author: Hee-Cheul Kim(Namseoul University) Email: kim1458@nsu.ac.krⒸ The Society of Digital Policy & Management. All rights reserved. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License(http://creativecommons.otg/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is ISSN: 1738-1916 properly cited.

Truncated Log Shaped Type Software Reliability Growth Model

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 intensity function, mean-value function, reliability of the software, estimation of parameters and the special applications of this model are discussed using real data.

The Comparative Study for ENHPP Software Reliability Growth Model Based on Mixture Coverage Function

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 Poisson process (ENHPP). In this paper, exponential coverage and S-shaped (Yamada-Ohba-Osaki) model was reviewed, proposes modified 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.

Failure Time Prediction Capability Comparative Analysis of Software NHPP Reliability Model

This study aims to analyze the predict capability of some of the popular software NHPP reliability models(Goel-Okumo model, delayed S-shaped reliability model and Rayleigh distribution model). The predict capability analysis will be on two key factors, one pertaining to the degree of fitment on available failure data and the other for its prediction capability. Estimation of parameters for each model was used maximum likelihood estimation using first 80% of the failure data. Comparison of predict capability of models selected by validating against the last 20% of the available failure data. Through this study, findings can be used as priori information for the administrator to analyze the failure of software.

The Comparative Study for Software Reliability Model Based on Finite and Infinite Failure Property using Rayleigh Distribution

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 Comparative Software Reliability Cost Model of Considering Shape Parameter

Abstract 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. Key Words : Shape Parameter, NHPP, Cost Model, Erlang Distribution, Log-logistic Distributionl

Study for Predict of the Future Software Failure Time Using Nonlinear Regression

Software failure time have been proposed in the literature exhibit either constant, monotonic increasing or monotonic decreasing. For data analysis of software reliability model trend analysis was developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offers information of outline content. In this paper, we discuss failure time case of failure time censoring, and predict the future failure time using nonlinear regression models (growth, Logistic and weighted type) which error terms for each other are different. The proposed prediction method used the failure time for the prediction using nonlinear regression model. Model selection, using the coefficient of determination and the mean square error, were presented for effective comparison.

The Assessing Comparative Study for Statistical Process Control of Software Reliability Model Based on Logarithmic Learning Effects

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.

The Comparative Study of Software Optimal Release Time Based on Intensity Function property

Abstract In this paper, we were researched decision problem called an optimal release policies after testing a software system in development phase and transferring it to the user. The applied model of release time exploited infinite failure non-homogeneous Poisson process This infinite failure non-homogeneous Poisson process is a model which reflects the possibility of introducing new faults when correcting or modifying the software. The intensity function used Gompertz, Preto and Log-logstic pattern which has the efficient various property. Thus, optimal 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. Key Words : Software Release Policies, Infinite Non-Homogeneous Poisson Process, Intensity Function Property

The Comparative Study of Software Optimal Release Time Based on Weibull Distribution Property

Abstract In this paper, we were researched decision problem called an optimal release policies after testing a software system in development phase and transferring it to the user. The applied model of release time exploited infinite failure non-homogeneous Poisson process This infinite failure 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 the Weibull distribution which has the efficient various property which has the place efficient quality. Thus, optimal 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. Key Words :