• Journal of KIISE:Software and Applications
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• v.36 no.9
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• pp.697-705
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• 2009

A GUI automated test can be divided into two areas. The first one is a regression test automation and the second one is an automated test. The former includes generating test cases manually and executing them automatically but the latter includes both generating test cases and executing them automatically. Costs of a software test are increasing more and more. Many companies are searching for a test automation method but most used things are limited to regression test automation. So, when testing at first, there should be test cases which are drawn up by a human. This paper explains to make test cases based on a source code and execute them automatically. In this paper, the study proceeds with a digital television set-top box application and explains to test without any effort of human. Of course, this study is far from a realization to industries. But this paper has a contribution at reducing more human efforts than the previous regression test automation and showing that later, fully automated test can be possible.

• Journal of the Korea Convergence Society
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• v.7 no.6
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• pp.35-41
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• 2016

As software is very important, modern men are interesting software quality testing. In this paper, we analyze the Internation standard and Test data, so, we propose the testing method by analysing testing data. We compare ISO/IEC 9126-2 testing model with ISO/IEC 25023 testing model. On the basis of ISO/IEC 25023, we classify the test data and we analyze the difference of International Standard to functionality, reliability, usability, efficiency, maintainability, portability, compatability, and security. By reality 331 testing data, we classify test data, and analyze difference according to sex. We find regression model by functionality, usability and testing date and we prove difference of testing date and the number of error by tester. Also, we prove difference of the number of error in software type.

• Journal of Korean Society for Quality Management
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• v.49 no.2
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• pp.201-211
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• 2021

Purpose: This paper proposes a density adaptive grid algorithm for the k-NN regression model to reduce the computation time for large datasets without significant prediction accuracy loss. Methods: The proposed method utilizes the concept of the grid with centroid to reduce the number of reference data points so that the required computation time is much reduced. Since the grid generation process in this paper is based on quantiles of original variables, the proposed method can fully reflect the density information of the original reference data set. Results: Using five real-life datasets, the proposed k-NN regression model is compared with the original k-NN regression model. The results show that the proposed density adaptive grid-based k-NN regression model is superior to the original k-NN regression in terms of data reduction ratio and time efficiency ratio, and provides a similar prediction error if the appropriate number of grids is selected. Conclusion: The proposed density adaptive grid algorithm for the k-NN regression model is a simple and effective model which can help avoid a large loss of prediction accuracy with faster execution speed and fewer memory requirements during the testing phase.

• Journal of the Korean Statistical Society
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• v.28 no.4
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• pp.489-501
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• 1999

In this paper, we consider the panel data regression model in which the disturbances have nested error component. We derive a Lagrange Multiplier(LM) test which is jointly testing for the presence of random individual effects and nested effects under the normality assumption of the disturbances. This test extends the earlier work of Breusch and Pagan(1980) and Baltagi and Li(1991). Further, it is shown that this LM test has the same asymptotic distribution without normality assumption of the disturbances.

• Journal of the Korean Statistical Society
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• v.18 no.1
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• pp.46-61
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• 1989

This paper is concerned with the development of a nonparametric procedure for the statistical inference about the nonlinear regression parameters. A confidence region and a hypothesis testing procedure based on a class of signed linear rank statistics are proposed and the asymptotic distributions of the test statistic both under the null hypothesis and under a sequence of local alternatives are investigated. Some desirable asymptotic properties including the asymptotic relative efficiency are discussed for various score functions.

• Communications for Statistical Applications and Methods
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• v.4 no.2
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• pp.565-579
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• 1997

A robust test is proposed for the problem of testing the parallelism of several regression lines against ordered alternatives. The proposed test statistic is based on a linear combination of one-step pairwise GM-estimators. We compare the performance of the proposed test with that of the other tests through a Monte Carlo simulation. The results of the simulation study show that the proposed test has stable levels, good empirical powers in various circumstances, and particularly higher empirical powers under the presence of extreme outliers or leverage points.

• Journal of the Korean Statistical Society
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• v.8 no.2
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• pp.107-109
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• 1979

Consider a linear model with n observations and k explanatory variables: (1)b $y=X\beta+u, u\simN(0,\sigma^2I_n)$. We assume that the model satisfies the ideal conditions. Consider the general linear constraints on regression coefficient vector: (2) $R\beta=r$, where R and r are known matrices of orders $q\timesk$ and q\times1$ respectively, and the rank of R is $qk+q$.

• The Korean Journal of Applied Statistics
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• v.5 no.1
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• pp.29-39
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• 1992

A testing and estimation procedure is considered for changes at unknown time point in simple linear regression model. A test statistic of quadratic form is suggested. We also discuss the asymptotic distribution and its level control. The proposed method is compared with the likelihood ratio test through a example.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.655-665
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• 2000

Several information criterions, Schwarz information criterion (SIC), Akaike information criterion (AIC), and the modified Akaike information criterion ($AIC_c$), are proposed to locate a change point in the multiple linear regression model. These methods are applied to a stock Exchange data set and compared to the results.

• Journal of the Korean Statistical Society
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• v.7 no.1
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• pp.17-26
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• 1978

For testing $\beta_i=\beta, i=1,...,k$, in the regression model $Y_{ij} = \alpha_i + \beta_ix_{ij} + e_{ij}, j=1,...,n_i$, a simple and robust test based on Kendall's tau is proposed. Its asymptotic distribution is proved to be chi-square under the null hypthesis and noncentral chi-square under an appropriate sequence of alternatives. For the optimal designs, the asymptotic relative efficiency of the proposed procedure with respect to the least squares procedure is the same as that of the Wilcoxon test with respect to the t-test.