• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.4
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• pp.551-560
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• 2010

In this paper, we suggest a localization method of factors affecting the accuracy of Air-to-Ground weapon delivery. The proposed method, called FBEL(Factor-Based Error Localization), is based on the fault localization technique widely utilized in the realm of software engineering field. FBEL localizes the major factors affecting the performance of weapon delivery. To analyze the effectiveness and the applicability of FBEL, we applied FBEL to real firing data and got the major factors caused the errors. We expect that the method could contribute to improve the quality of weapon delivery system. We also expect that it may aid improvement of pilot capability greatly, if it is applied to pilot firing training.

• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.59-67
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• 2011

This paper proposes a model to analyze the fault factors of air-to-ground weapon delivery utilizing software fault localization methods. In the previous study, to figure out the factors to affect the accuracy of air-to-ground weapon delivery, the FBEL (Factor-based Error Localization) method had been proposed and the fault factors were analyzed based on the method. But in the study, the correlation between weapon delivery accuracy and the fault factors could not be revealed because the firing accuracy among several factors was fixed. In this paper we propose a more precise fault analysis model driven through a study of the correlation among the fault factors of weapon delivery, and a method to estimate the possibility of faults with the limited number of test cases utilizing the model. The effectiveness of proposed method is verified through the simulation utilizing real delivery data. and weapons delivery testing in the evaluation of which element affecting the accuracy of analysis that was available to be used successfully.

• Journal of KIISE
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• v.43 no.9
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• pp.998-1007
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• 2016

In recent years, the cost of automotive ECU (Electronic Control Unit) has accounted for more than 30% of total car production cost. However, the complexity of testing and debugging an automotive ECU is increasing because automobile manufacturers outsource automotive ECU production. Therefore, a large amount of cost and time are spent to localize faults during testing an automotive ECU. In order to solve these problems, we propose a fault localization method in memory for developers who run the integration testing of automotive ECU. In this method, memory is partitioned by utilizing memory map, and fault-suspiciousness for each partition is calculated by utilizing memory update information. Then, the fault-suspicious region for partitions is decided based on calculated fault-suspiciousness. The preliminary result indicated that the proposed method reduced the fault-suspicious region to 15.01(%) of memory size.