• Journal of KIISE
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• v.44 no.2
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• pp.171-178
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• 2017

In this study, we propose an automated unit test generation technique for detecting vulnerabilities of Android kernel modules. The technique automatically generates unit test drivers/stubs and unit test inputs for each function of Android kernel modules by utilizing dynamic symbolic execution. To reduce false alarms caused by function pointers and missing pre-conditions of automated unit test generation technique, we develop false alarm reduction techniques that match function pointers by utilizing static analysis and generate pre-conditions by utilizing def-use analysis. We showed that the proposed technique could detect all existing vulnerabilities in the three modules of Android kernel 3.4. Also, the false alarm reduction techniques removed 44.9% of false alarms on average.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.556-559
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• 2008

In this study, an automated ultrasonic testing system and post signal and image processing techniques are developed in order to construct ultrasonic flaw images in weldments. The automated ultrasonic testing system developed in the present study adopted an 8 channel pulser/receiver-ADC unit and a 2 axis motion driving unit and the post signal and image processing algorithms are built into the system program of the automated ultrasonic testing system.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.11
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• pp.1061-1065
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• 2010

AUTOSAR, a standard software platform for automotive, has been developed to manage software complexity and improve software reuseability. However Automated and standardized testing is needed to improve reliability and reduce time and effort on testing. Fundamental functionality of AUTOSAR RTE and basic software modules is guaranteed by using an AUTOSAR tool, but application software components have to be tested thoroughly. In this paper, we suggest a test system for the AUTOSAR software component using TTCN-3, a standardized testing language. Test execution system and test cases for the software component are generated automatically from AUTOSAR XML containing software design information. With the proposed testing techniques we can reduce time and effort to build the testing system.

• Journal of KIISE:Software and Applications
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• v.36 no.1
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• pp.10-20
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• 2009

As unit testing should be performed repeatedly and continuously, it is a high-cost software development activity. Although there are many studies on unit test automation, there are less studies on automated test case generation which are worthy of note. In this paper, we discuss a study on automated test data generation from source codes and indicate algorithms for each stage. We also show some issues of test data generation and introduce an automated test data generating tool: CUTIG. As CUTIG generates test data not from require specifications but from source codes, software developers could generate test data when specifications are insufficient or discord with real implementation. Moreover we hope that the tool could help software developers to reduce cost for test data preparation.

• The KIPS Transactions:PartD
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• v.16D no.6
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• pp.911-920
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• 2009

Airbone software must comply the DO-178B standard in order to be certified by the FAA. The standard requires the unit testing of safety-critical software to meet the coverage criterion called MC/DC(Modified Condition/Decision Coverage). Although MC/DC is known to be effective in finding errors related to safety, it is also true that generating test cases which satisfy the MC/DC criterion is not easy. This paper presents a tool named MD-SAT which generates MC/DC test cases with SAT(SATisfiability) technology. It can be employed for generating diverse test cases in tools implementing various testing techniques including decision table based test, cause-effect graphing, and state-based test.

• Proceedings of the Safety Management and Science Conference
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• 2006.04a
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• pp.1-8
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• 2006

By the effect of globalism and information the workplace environment is complicated and diversified little by little. The job stress due to the life style, the idea and culture, and the automated facility system etc. is to a tendency which compared to increase more. It will not be able to prevent a industrial accident basically because the oriental and western life style is different. Therefore this paper presents the Korean life change unit model through statistical testing in order to minimize industrial accident with the proposed life change unit factors on the workers living In the middle area. Finally, the analytical result of this paper can be easily used in order to minimize the industrial accidents by the job stress with the worker and the occupational safety & health manager in real fields.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.443-452
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• 2020

Worker's awkward postures and unreasonable physical load can be corrected by monitoring construction activities, thereby increasing the safety and productivity of construction workers and projects. However, manual identification is time-consuming and contains high human variance. In this regard, an automated activity recognition system based on inertial measurement unit can help in rapidly and precisely collecting motion data. With the acceleration data, the machine learning algorithm will be used to train classifiers for automatically categorizing activities. However, input acceleration data are extracted either from designed experiments or simple construction work in previous studies. Thus, collected data series are discontinuous and activity categories are insufficient for real construction circumstances. This study aims to collect acceleration data during long-term continuous work in a construction project and validate the feasibility of activity recognition algorithm with the continuous motion data. The data collection covers two different workers performing formwork at the same site. An accelerator, as well as portable camera, is attached to the worker during the entire working session for simultaneously recording motion data and working activity. The supervised machine learning-based models are trained to classify activity in hierarchical levels, which reaches a 96.9% testing accuracy of recognizing rest and work and 85.6% testing accuracy of identifying stationary, traveling, and rebar installation actions.

• Journal of Microbiology and Biotechnology
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• v.15 no.3
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• pp.595-602
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• 2005

A one-step real-time quantitative RT-PCR assay in combination with automated RNA extraction was evaluated for routine testing of HCV RNA in the laboratory. Specific primers and probes were developed to detect 302 bp on 5'-UTR of HCV RNA. The assay was able to quantitate a dynamic linear range of $10^7-10^1$ HCV RNA copies/reaction ($R^2=0.997$). The synthetic HCV RNA standard of $1.84{\pm}0.1\;(mean{\pm}SD)$ copies developed in this study corresponded to 1 international unit (IU) of WHO International Standard for HCV RNA (96/790 I). The detection limit of the assay was 3 RNA copies/reaction (81 IU/ml) in plasma samples. The assay was comparable to the Amplicor HCV Monitor (Monitor) assay with correlation coefficient r=0.985, but was more sensitive than the Monitor assay. The assay could be completed within 3 h from RNA extraction to detection and data analysis for up to 32 samples. It allowed rapid RNA extraction, detection, and quantitation of HCV RNA in plasma samples. The method provided sufficient sensitivity and reproducibility and proved to be fast and labor-saving, so that it was suitable for high throughput HCV RNA test.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.8
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• pp.229-234
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• 2020

This paper presents the design and the implementation of CRESTIVE-DX, a concolic testing tool that distribute the concolic testing process over the embedded target system and the host system for efficient test generation of a target embedded program. CRESTIVE-DX conducts the execution of a target program on the target embedded system to consider possible machine-dependent behaviors of a target program execution, and conducts machine-independent parts, such as search-strategy heuristics, constraint solving, on host systems with high-speed computation unit, and coordinates their concurrent executions. CRESTIVE-DX is implemented by extending an existing concolic testing tool for C programs CREST. We conducted experiments with a test bed that consists of an embedded target system in the Arm Cortex A54 architecture and host systems in the x86-64 architecture. The results of experiments with Unix utility programs Grep, Busybox Awk, and Busybox Ed show that test input generation of CRESTIVE-DX is 1.59 to 2.64 times faster than that of CREST.

• Convergence Security Journal
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• v.22 no.1
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• pp.3-9
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• 2022

The role of the integrated development environment is very important in software development of a development project. After many developers develop different modules, software product is completed through compile, debugging, integration, testing, and distribution. However, bugs and various issues in the development process cause problems such as quality deterioration of software product and dissatisfaction with requirements. So the need for automated testing to avoid these problems and improve quality has increased. In this study, we propose test automation modules of four perspectives to improve quality throughout the test automation in an integrated development environment. Each automation module operates through the tool chain of an integrated build framework implemented on the devops.