• 한국항공우주학회지
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• 제46권11호
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• pp.961-968
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• 2018

항공기 시현계통은 항공기 운영에 필요한 다양한 정보를 통합하여 조종사에게 시현한다. 시현계통에서 소프트웨어 결함이 발생되면 정확하지 않은 정보가 조종사에게 시현될 수 있기 때문에 항공기의 운영에 심각한 영향을 미칠 수 있다. 따라서 시현계통의 개발 중에 지상시험과 비행시험을 통해 발생 가능한 소프트웨어 결함을 식별하고 제거하려고 노력하고 있다. 본 연구는 비행시험 자료를 이용하여 시현계통의 소프트웨어 결함 분석을 지원하는 도구인 FDR(Flight Data Replay)을 제시한다. 이 도구는 항공기 임무컴퓨터와 연동되어 실시간으로 동작한다. 그리고 시현소프트웨어에 비행시험 자료를 적용하여 시현장치에 나타나는 기능적인 오류상황을 재현한다.

• 대한임베디드공학회논문지
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• 제7권3호
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• pp.135-142
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• 2012

The Quality of embedded system depends on the embedded software. As the complexity and the size of embedded software have been increasing, it is more likely that the software may include faults, and the reliability and stability issues are getting more important. In this paper, we propose a remote test tool for software based on VxWorks by using fault injection method. The test tool consists of test server and test client for testing on the cross development environment. The test server operates in the host system and user can not only test but also monitor the software by using it. The test client operates in the target system and it controls kernel objects and sends the input data into the software when receiving the control and data from the test server. We developed the prototype software and demonstrated the ability of testing software robustness by injecting faults.

• 한국정보처리학회논문지
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• 제5권5호
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• pp.1225-1233
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• 1998

소프트웨어 시스템을 언제까지 테스팅해서 사용자에게 양도할 것인가를 결정하는 소프트웨어 양도 정책은 개발자가 해결해야 하는 중요한 문제의 하나이다. 이 양도 정책 문제에 대한 일반적인 접근법은 주어진 신뢰성 요구사항을 만족하기 위해 필요한 고장 발견수나 테스팅 시간을 결정하는 것이다. 소프트웨어 신뢰성은 잔존 고장수 또는 수정된 고장수에 의존하며, 불완전 디버깅 환경에서는 발견된 고장이 모두 수정되는 것이 아니므로 불완전 디버깅 환경에서의 양도 정책을 구하는 새로운 방법이 필요하다. 본 논문에서는 불완전 디버깅 환경에서의 신뢰성 요구사항을 만족하였음을 원하는 신뢰수준으로 보증하는 양도 정책을 제안하고, 이를 구현하였다.

• 한국정보처리학회논문지
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• 제7권4호
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• pp.1103-1111
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• 2000

The hyper-geometric distribution software reliability growth model (HGDM) usually assumes that all the software faults detected are perfectly removed without introducing new faults. However, since new faults can be introduced during the test-and-debug phase, the perfect debugging assumption should be relaxed. In this context, Hou, Kuo and Chang [7] developed a modified HGDM for imperfect debugging environment, assuming tat the learning factor is constant. In this paper we extend the existing imperfect debugging HGDM for tow respects: introduction of random sensitivity factor and allowance of variable learning factor. Then the statistical characteristics of he suggested model are studied and its applications to two real data sets are demonstrated.

• 한국지능시스템학회논문지
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• 제13권4호
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• pp.486-490
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• 2003

Software qualify models can predict the risk of faults in the software early enough for cost-effective prevention of problems. This paper introduces a least squares support vector machine (LS-SVM) as a fuzzy regression method for predicting fault ranges in the software under development. This LS-SVM deals with the fuzzy data with crisp inputs and fuzzy output. Predicting the exact number of bugs in software is often not necessary. This LS-SVM can predict the interval that the number of faults of the program at each session falls into with a certain possibility. A case study on software reliability problem is used to illustrate the usefulness of this LS -SVM.

• Journal of Electrical Engineering and Technology
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• 제9권5호
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• pp.1739-1745
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• 2014

Prediction of fault-prone modules continues to attract researcher's interest due to its significant impact on software development cost. The most important goal of such techniques is to correctly identify the modules where faults are most likely to present in early phases of software development lifecycle. Various software metrics related to modules level fault data have been successfully used for prediction of fault-prone modules. Goal of this research is to predict the faulty modules at design phase using design metrics of modules and faults related to modules. We have analyzed the effect of pre-processing and different machine learning schemes on eleven projects from NASA Metrics Data Program which offers design metrics and its related faults. Using seven machine learning and four preprocessing techniques we confirmed that models built from design metrics are surprisingly good at fault proneness prediction. The result shows that we should choose Naïve Bayes or Voting feature intervals with discretization for different data sets as they outperformed out of 28 schemes. Naive Bayes and Voting feature intervals has performed AUC > 0.7 on average of eleven projects. Our proposed framework is effective and can predict an acceptable level of fault at design phases.

• 대한임베디드공학회논문지
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• 제13권6호
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• pp.305-312
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• 2018

Software has been used to develop many functions of the modern weapon systems which has a high mission criticality. Weapon system software must consider multi-threaded processing to satisfy growing performance requirement. However, developing multi-threaded programs are difficult because of concurrency faults, such as unintended data races. Especially, it is important to prepare analysis for debugging the data races, because the weapon system software may cause personal injury. In this paper, we present an efficient framework of analysis, called ConDeWS, which is designed to determine the scope of dynamic analysis through using the result of static analysis and fault analysis. As a result of applying the implemented framework to the target software, we have detected unintended data races that were not detected in the static analysis.

• ETRI Journal
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• 제21권3호
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• pp.6-15
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• 1999

Many studies in the software reliability have attempted to develop a model for predicting the faults of a software module because the application of good prediction models provides the optimal resource allocation during the development period. In this paper, we consider the change request data collected from the field test of the software module that incorporate a functional relation between the faults and some software metrics. To this end, we discuss the general aspect if regression method, the problem of multicollinearity and the measures of model evaluation. We consider four possible regression models including two stepwise regression models and two nonlinear models. Four developed models are evaluated with respect to the predictive quality.

• 대한전기학회논문지:전력기술부문A
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• 제54권2호
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• pp.73-78
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• 2005

The management of technological systems will become increasingly complex. Safe and reliable software operation is a significant requirement for many types of system. So, with software fault tolerance, we want to prevent failures by tolerating faults whose occurrences are known when errors are detected. This paper presents a fault location algorithm for single-phase-to-ground faults on the teed circuit of a parallel transmission line using software fault tolerance technique. To find the fault location of transmission line, we have to solve the 3rd order transmission line equation. A significant improvement in the identification of the fault location was accomplished using the N-Version Programming (NVP) design paradigm. The delivered new algorithm has been tested with the simulation data obtained from the versatile EMTP simulator.

• 제어로봇시스템학회논문지
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• 제14권4호
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• pp.399-405
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• 2008

Recently, robot technology is actively going on progress to the field of various services such as home care, medical care, entertainment, and etc. Because these service robots are in use nearby person, they need to be operated safely even though hardware and software faults occur. This paper proposes a Fault-Tolerant middleware for a robot system, which has following two characteristics: supporting of heterogeneous network interface and processing of software components and network faults. The Fault-Tolerant middleware consists of a Service Layer(SL), a Network Adaptation Layer(NAL), a Network Interface Layer(NIL), a Operating System ion Layer(OSAL), and a Fault-Tolerant Manager(FTM). Especially, the Fault-Tolerant Manager consists of 4 components: Monitor, Fault Detector, Fault Notifier, and Fault Recover to detect and recover the faults effectively. This paper implements and tests the proposed middleware. Some experiment results show that the proposed Fault-Tolerant middleware is working well.