• Journal of KIISE:Software and Applications
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• v.36 no.6
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• pp.451-461
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• 2009

The Adaptive Random Testing(ART) aims to improve the performance of traditional Random Testing(RT) by reducing the number of test cases to find the failure region which is located in the input domain. Such enhancement can be obtained by efficient selection algorithms of test cases. The ART through Iterative Partitioning(IP-ART) is one of ART techniques and it uses an iterative input domain partitioning method to improve the performance of early-versions of ART which have significant drawbacks in computation time. And the IP-ART with Enlarged Input Domain(EIP-ART), an improved version of IP-ART, is known to make additional performance improvement with scalability by expanding to virtual test space beyond real input domain of IP-ART. The EIP-ART algorithm, however, have the drawback of heavy cost of computation time to generate test cases mainly due to the virtual input domain enlargement. For this reason, two algorithms are proposed in this paper to mitigate the computation overhead of the EIP-ART. In the experiments by simulations, the tiling technique of input domain, one of two proposed algorithms, showed significant improvements in terms of computation time and testing performance.

• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.19-28
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• 2011

Adaptive Random Testing (ART) aims to enhance the performance of pure random testing by detecting failure region in a software. The ART algorithm generates effective test cases which requires less number of test cases than that of pure random testing. However, all ART algorithms currently proposed are designed for the tests of monolithic system or unit level. In case of integrated system tests, ART approaches do not achieve same performances as those of ARTs applied to the unit or monolithic system. In this paper, we propose an extended ART algorithm which can be applied to the integrated system testing environment without degradation of performance. The proposed approach investigates an input distribution of the unit under a test with limited number of seed input data and generates information to be used to resizing input domain partitions. The simulation results show that our approach in an integration environment could achieve similar level of performance as an ART is applied to a unit testing. Results also show resilient effectiveness for various failure rates.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.198-201
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• 2011

현재 안드로이드 시장에는 다양한 플랫폼을 기반으로 한 디바이스들이 혼재하고 있고, 안드로이드의 성장세로 봤을 때 앞으로 더욱더 많은 플랫폼 및 디바이스가 출시될 것이다. 따라서 여러 플랫폼 및 디바이스에 대한 상호 호환성을 만족시키기 위해 안드로이드 소프트웨어 개발 단계부터 테스트의 중요도가 높아지고 있고, 테스팅 시간을 줄이기 위한 테스트 자동화 문제가 대두되고 있다. 이러한 환경에서 상호 호환성을 만족시키기 위해서는 소프트웨어적인 요소뿐만 아니라 프로그램의 전반적인 요소까지 고려해야 하지만 기존의 테스트 자동화 도구인 JUnit은 안드로이드 소프트웨어의 특정 상태에 대한 정보만을 도출하기 때문에 전반적인 요소에 대한 통합관리가 불가능하다. 따라서 본 논문에서는 안드로이드 소프트웨어의 전반적인 요소들에 대한 정보를 도출하여 테스트 케이스를 자동으로 생성하는 방안을 제안한다. 사용자가 도출하고자 하는 정보를 선택함으로써 테스트 케이스 생성에 대한 유연성이 증가하고, 이를 자동화함으로써 테스팅 시간 감소를 통해 생산성 향상 및 높은 품질의 안드로이드 소프트웨어를 기대할 수 있다.

• Annual Conference of KIPS
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• 2001.04a
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• pp.197-200
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• 2001

이 논문은 웹기반 소프트웨어를 테스트하기 위한 오러클을 생성하는 방법을 제안하고 설명한다. 웹 페이지를 구성하는 응용 컴포넌트들의 구조를 파악하고 각 페이지를 구동시키는 액션들을 찾아내어 상태기반의 테스트 데이터를 찾아내는 방법이다. 테스트 스크립트를 작성하기 위하여 partial-W 방법을 도입하였으며 이를 이용하여 테스트 케이스의 값을 선택할 수 있다. 테스트 슈트는 언어 독립적이며 실행가능하다. 웹 응용의 특징인 동적인 인터렉션을 유한 상태기계(Finite State Machine)로 표현하고 각 상태를 변화시키는 웹 페이지의 사용자 입격을 결합하여 테스트 오러클을 생성한다.

• The KIPS Transactions:PartD
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• v.18D no.5
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• pp.343-356
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• 2011

When preparing test cases and running the test the existing GUI test tools require many tester's interventions. To cope with such problem this paper suggests a new method to build test cases for GUI test. This method identifies the potential control flows within the GUI and constructs the GUI map. The UIA library in .NET Framework is used to extract information about the GUI controls and the GUI map is constructed by the extracted information. Test scenarios are generated from the extracted information about the GUI controls using the grouping mechanism. Based on the grouping mechanism, various test scenarios which are test cases in GUI tests can be made by replacing a GUI control by another one in the same group. The existing GUI test tools do not support the concept of test coverage. Since, however, our method survey which part of the GUI map is executed or not during running the test, the test coverage can be measured by using the GUI map.

• Annual Conference of KIPS
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• 2024.05a
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• pp.290-293
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• 2024

최근 IoT (Internet of Things, IoT) 기기가 전 산업과 일상 생활에 활용되면서 취약점 탐지 기술이 중요해지고 있다. 그러나 리소스가 제약적인 IoT 기기에는 종래의 퍼징 기술을 적용하기 어렵다. 본 논문에서는 경량화 IoT 환경에서 퍼징 기술을 적용하기 위한 테스트케이스 선택 기법을 제안했다. 실험 결과에 따르면, 제안하는 방식은 무작위 입력을 생성하여 퍼징하는 종래 퍼저보다 평균 61.49% 빠르게 취약점을 탐지했다.

• Journal of Software Engineering Society
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• v.28 no.1
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• pp.23-28
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• 2019

Recently, in order to effectively test deep neural network model for image processing application, researches have actively conducted to automatically generate data in corner-case that is not correctly predicted by the model. This paper proposes test data generation method that selects arbitrary words from input of system and transforms them into synonyms in order to test the bug reporter automatic assignment system based on sentence classification deep neural network model. In addition, we compare and evaluate the case of using proposed test data generation and the case of using existing difference-inducing test data generations based on various neuron coverages.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.2
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• pp.86-99
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• 2007

Packet filtering is to filter out potentially malicious network packets. In order to test a packet filtering function we should verify whether security policies are performed correctly as intended. However there are few existing tools to test the function. Besides, they need user participation when generating test cases or deciding test results. Many security administrators have a burden to test systematically new security policies when they establish new policies or modify the existing ones. To mitigate the burdens we suggest a new test method with minimal user articipation. Our tool automates generation steps of the test cases and the test oracles, respectively. By using the test oracles generated automatically, deciding test results is possible without user intervention. Our method realizes an automatic testing in three phases; test preparation phase, test execution, and test evaluation. As a result it may enhance confidence of test activities more highly. This paper describes the design and implementation of our test method and tool.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.3
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• pp.64-76
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• 2009

Adaptive Random Testing through Iterative Partitioning(IP-ART) is one of Adaptive Random Testing(ART) techniques. IP-ART uses an iterative partitioning method for input domain to improve the performances of early-versions of ART that have significant drawbacks in computation time. Another version of IP-ART, named with EIP-ART(IP-ART with Enlarged Input Domain), uses virtually enlarged input domain to remove the unevenly distributed parts near the boundary of the domain. EIP-ART could mitigate non-uniform test case distribution of IP-ART and achieve relatively high performances in a variety of input domain environments. The EIP-ART algorithm, however, have the drawback of higher computation time to generate test cases mainly due to the additional workload from enlarged input domain. For this reason, a revised version of IP-ART without input domain enlargement needs to improve the distribution of test cases to remove the additional time cost. We explore three smoothing algorithms which influence the distribution of test cases, and analyze to check if any performance improvements take place by them. The simulation results show that the algorithm of a restriction area management achieves better performance than other ones.

• Annual Conference of KIPS
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• 2007.11a
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• pp.315-318
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• 2007

랜덤 테스트(RT)는 가능한 입력 도메인에서 임의의 입력 값을 선택하여 테스트 케이스를 생성하고 테스트를 수행하는 기본적인 블랙 박스 테스트 기법이다. 랜덤 테스트의 성능을 향상 시키기 위해서 오류 패턴을 고려한 다양한 Adaptive Random Testing (ART) 알고리즘들이 제안되어 왔다. 그 중 Distance-Based ART (D-ART), Restricted Random Testing (RRT)이 좋은 성능을 보이고 있지만, 수행시간이 너무 느리다는 단점이 있어, 이를 대체할 수 있는 여러 ART 방법들이 제안되고 있다. 그 중, Adaptive Random Testing through Iterative Partitioning (IP-ART)가 가장 좋은 성능과 빠른 수행시간을 보인다. 본 논문에서는 IP-ART 의 성능을 더욱 향상시킬 수 있는 방법을 제안하고, 시뮬레이션을 통하여 향상된 성능을 평가해 보았다.