• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.8 no.6
• /
• pp.445-452
• /
• 2015

Software reliability in the software development process is an important issue. Software process improvement helps in finishing with reliable software product. Infinite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, proposes the reliability model with log and power intensity function (log linear, log power and exponential power), which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on mean square error (MSE) and coefficient of determination($R^2$), for the sake of efficient model, was employed. Analysis of failure, using real data set for the sake of proposing log and power intensity function, was employed. This analysis of failure data compared with log and power intensity function. In order to insurance for the reliability of data, Laplace trend test was employed. In this study, the log type model is also efficient in terms of reliability because it (the coefficient of determination is 70% or more) in the field of the conventional model can be used as an alternative could be confirmed. From this paper, software developers have to consider the growth model by prior knowledge of the software to identify failure modes which can be able to help.

• Journal of Convergence for Information Technology
• /
• v.11 no.3
• /
• pp.125-131
• /
• 2021

The problem of determining the maintenance point which minimizes the process-related total cost is called the 'process mean shift problem'. By expanding and integrating the existing maintenance models that have been partially progressed, we present a expanded and integrated maintenance model which reflects the production site where various situations occur. To implement this, we set both the upper and lower limits of the product specification, and adopted the quality loss function for conforming items. Also, we set the process variance of the wear level as a function rather than a constant. In this study, we developed two general functions to the wear level. One is about the production volume and the other is maintenance cost. As a result, this study is expected to be a maintenance model that can be applied to various processes. In the future, this study can be developed as a profit maximization model by adding profit items from product sales, and expansion to a maintenance model that introduces failure to the model of this study can be considered.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.14 no.10
• /
• pp.5156-5161
• /
• 2013

In distributed spatial data stream processing, processed tuples of downstream nodes are replicated to the upstream node in order to increase the utilization of distributed nodes and to recover the whole system for the case of system failure. However, while the data input rate increases and multiple downstream nodes share the operation result of the upstream node, the data which stores to output queues as a backup can be lost since the deletion operation delay may be occurred by the delay of the tuple processing of upstream node. In this paper, the adaptive upstream backup scheme based on operation throughput in distributed spatial data stream system is proposed. This method can cut down the average load rate of nodes by efficient spatial operation migration as it processes spatial temporal data stream, and it can minimize the data loss by fluid change of backup mode. The experiments show the proposed approach can prevent data loss and can decrease, on average, 20% of CPU utilization by node monitoring.

• The Korean Journal of Applied Statistics
• /
• v.30 no.5
• /
• pp.647-663
• /
• 2017

Weibull distribution is a popular distribution for modeling lifetimes because it reflects the characteristics of failure adequately and it models either increasing or decreasing failure rates simply. It is a standard method of the lifetimes test to wait until all samples failed; however, censoring can occur due to some realistic limitations. In this paper, we propose a generalized likelihood ratio (GLR) chart to monitor changes in the scale parameter for type I right-censored Weibull lifetime data. We also compare the performance of the proposed GLR chart with two CUSUM charts proposed earlier using average run length (ARL). Simulation results show that the Weibull GLR chart is effective to detect a wide range of shift sizes when the shape parameter and sample size are large and the censoring rate is not too high.