• The KIPS Transactions:PartC
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• v.14C no.4
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• pp.313-320
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• 2007

In this paper, we propose a method to analyze security vulnerabilities of MS word-processor by checking the validation of its input files. That is, this study is to detect some vulnerabilities in the input file of the word processor by analyzing the header information of its input file. This validation test can not be conducted by the existing software fault injection tools including Holodeck and CANVAS. The proposed method can be also applied to identify the input file vulnerabilities of Hangul and Microsoft Excel which handle a data file with a header as an input. Moreover, our method can provide a means for assessing the fault tolerance and trustworthiness of the target software.

• ETRI Journal
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• v.27 no.2
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• pp.140-152
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• 2005

In this paper, we present design features, implementation, and validation of a satellite simulator subsystem for the Korea Multi-Purpose Satellite-2 (KOMPSAT-2). The satellite simulator subsystem is implemented on a personal computer to minimize costs and trouble on embedding onboard flight software into the simulator. An object-oriented design methodology is employed to maximize software reusability. Also, instead of a high-cost commercial database, XML is used for the manipulation of spacecraft characteristics data, telecommand, telemetry, and simulation data. The KOMPSAT-2 satellite simulator subsystem is validated by various simulations for autonomous onboard launch and early orbit phase operations, anomaly operation, and science fine mode operation. It is also officially verified by successfully passing various tests such as the satellite simulator subsystem test, mission control element system integration test, interface test, site installation test, and acceptance test.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.2
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• pp.209-214
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• 2009

The simulation software for predicting the performance of a wind turbine generator system (WTGS) is validated using the field measured data obtained from the idling test run of a dual rotor wind turbine recently developed and installed in Korea. Both steady-state and transient responses at low and high wind conditions are compared with the theoretically predicted ones from the simulation software WINSIM.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.197-206
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• 2015

Defect severity that is a measure of the impact caused by the defect plays an important role in software quality activities because not all software defects are equal. Earlier studies have concentrated on defining defect severity levels, but there have almost never been trials of measuring module severity. In this paper, first, we define a defect severity metric in the form of an exponential function using the characteristics that defect severity values increase much faster than severity levels. Then we define a new metrics set for software module severity using the number of defects in a module and their defect severity metric values. In order to show the applicability of the proposed metrics, we performed an analytical validation using Weyuker's properties and experimental validation using NASA open data sets. The results show that ms is very useful for measuring the module severity and msd can be used to compare different systems in terms of module severity.

• Aerospace Engineering and Technology
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• v.9 no.2
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• pp.51-56
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• 2010

There are two main software in COMS ground station at the normal mode operation - stationkeeping and wheel off-loading. In this paper, ground software validation test for wheel off-loading is summarized and described. The wheel off-loading was performed the design change from E3000 heritage and analyzed. The wheel off-loading of ground software has two part; one is wheel off-loading management for parameters change at the thruster set switching time and the other is wheel off-loading set-point being sent to satellite for the reference momentum.

• Journal of the Korea Society for Simulation
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• v.27 no.1
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• pp.25-32
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• 2018

This paper presents an efficient software reliability testing method for the model based auto-generated code and reify a dynamic test procedure. The benefits of executing the model-based each static/dynamic reliability test before the code-based static/dynamic reliability test are described. Also, The correlations of code/model based reliability test are demonstrated by using model testing tool, Model Advisor and Verification and Validation, and the code testing tool, PolySpace and LDRA. The result of reliability test is indicated in this paper.

• Journal of Digital Contents Society
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• v.18 no.3
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• pp.525-534
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• 2017

The open set recognition method should be used for the cases that the classes of test data are not known completely in the training phase. So it is required to include two processes of classification and the validation test. This kind of research is very necessary for commercialization of face recognition modules, but few domestic researches results about it have been published. In this paper, we propose an open set face recognition method that includes two sequential validation phases. In the first phase, with dummy classes we perform classification based on sparse representation. Here, when the test data is classified into a dummy class, we conclude that the data is invalid. If the data is classified into one of the regular training classes, for second validation test we extract four features and apply them for the proposed decision function. In experiments, we proposed a simulation method for open set recognition and showed that the proposed validation test outperform SCI of the well-known validation method

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.9
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• pp.880-886
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• 2014

Many railway signalling functions have increasingly depended on computer software with recent development in computing technology, leading to evolution into more flexible and intelligent railway signalling system. Meanwhile, software programs are likely to have many errors and the cost incurred by such errors has increased. Especially, if fatal software error occurs during railway operation, it may result in loss of lives. So the software verification and validation have become more important. It is needed for software functional safety tool to support these, but most commercial tools depend on direct access to the system's memory, resulting in many difficulties in application. Owing to such difficulties and complexity, they are rarely used in railway signalling system software validation. In this study, a new testing tool for software functional testing through an external interface that can be easily used in functional testing of software was developed. Such testing tool allows development and analysis of test cases for black-box testing through analysis of actually used interface protocols, leading to increased user convenience.

• Journal of Internet Computing and Services
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• v.10 no.4
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• pp.105-113
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• 2009

The feature models are widely used to model the commonalities and variabilities among the products in the domain engineering phase of software product line developments. The findings and corrections of the errors or consistencies in the feature models are essential to the successful software product line engineering. The aids of the automated tools are needed to perform the validation of the feature models effectively. This paper describes the approach based on JESS rule-base system to validate the feature models and proposes the feature model validation tool using this approach. The tool of this paper validates the feature models in real-time when modeling the feature models. Then it provides the information on existence of errors and the explanations on causes of those errors, which allows the feature modeler to create the error-free feature models. This attempt to validate the feature model using the rule-based system is supposed to be the first time in this research field.

• Nuclear Engineering and Technology
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• v.44 no.6
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• pp.663-672
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• 2012

As software based digital I&C (Instrumentation and Control) systems are used more prevalently in nuclear plants, enhancement of software dependability has become an important issue in the area of nuclear I&C systems. Critical attributes of software dependability are safety and reliability. These attributes are tightly related to software failures caused by faults. Software testing and V&V (Verification and Validation) activities are hence important for enhancing software dependability. If the risky modules of safety-critical software can be predicted, it will be possible to focus on testing and V&V activities more efficiently and effectively. It should also make it possible to better allocate resources for regulation activities. We propose a prediction technique to estimate risky software modules by adopting machine learning models based on software complexity metrics. An empirical study with various machine learning algorithms was executed for comparing the prediction performance. Experimental results show SVMs (Support Vector Machines) perform as well or better than the other methods.