• 한국항공우주학회지
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• 제44권3호
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• pp.256-265
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• 2016

소프트웨어 기반의 고장허용이란 장비의 일부분에 소프트웨어 고장이 발생하더라도 허용할 수 있도록 장비를 설계하는 것을 의미힌다. 고장허용을 위한 설계 방법은 크게 하드웨어 기반 고장허용 설계 방법과 소프트웨어 기반 고장허용 설계 방법이 있으며, 시스템의 특징에 따라 적절한 방법의 고장허용 설계 방법 선택이 필요하다. 본 논문에서는 하드웨어적으로 이중화로 구성된 비행조종컴퓨터의 소프트웨어 기반 고장허용 설계 기법에 대하여 기술하였다. 소프트웨어 기반의 고장허용 설계를 위하여 소프트웨어 고장을 분류하고, 고장에 대한 검출 방법을 설계한 후, 고장발생시 복구 방법을 설계하였다. 설계된 방법의 유효성을 확인하기 위하여 전용 소프트웨어 시험 환경을 통해 설계된 소프트웨어 기반 고장허용 설계의 타당성을 검증하였다.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권6호
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• pp.396-402
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• 2005

The software reliability growth model(SRGM) has been developed in order to evaluate such measures as remaining fault number, fault rate, and reliability for the developing stage software. Most of the study literatures assumed that this detecting efficiency was perfect. However the actual fault detecting is generally imperfect, and widely known to many persons. It is not easy to develop and remove the fault existing in the software because the fault finding is difficult, and the exact solving method also not easy, and new fault may be introduced depending on the tester's capability. There, the fault removing efficiency influences the software reliability growth or developing cost of software. It is a very useful measure throughout the developing stage, much helpful for the developer to evaluate the debugging efficiency, and evaluate additional workload. Hence, the study for the imperfect debugging is important in point of software reliability and cost. This paper proposes that the fault debugging is imperfect and new fault may be introduced for the developing software during the developing stage.

• 한국신뢰성학회지:신뢰성응용연구
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• 제16권1호
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• pp.48-55
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• 2016

Purpose: The purpose of this study is to identify the object-oriented metrics which have strong impact on the reliability and fault-proneness of software products. The reliability and fault-proneness of software product is closely related to the design properties of class diagrams such as coupling between objects and depth of inheritance tree. Methods: This study has empirically validated the object-oriented metrics to determine which metrics are the best to predict fault-proneness. We have tested the metrics using logistic regressions and artificial neural networks. The results are then compared and validated by ROC curves. Results: The artificial neural network models show better results in sensitivity, specificity and correctness than logistic regression models. Among object-oriented metrics, several metrics can estimate the fault-proneness better. The metrics are CBO (coupling between objects), DIT (depth of inheritance), LCOM (lack of cohesive methods), RFC (response for class). In addition to the object-oriented metrics, LOC (lines of code) metric has also proven to be a good factor for determining fault-proneness of software products. Conclusion: In order to develop fault-free and reliable software products on time and within budget, assuring quality of initial phases of software development processes is crucial. Since object-oriented metrics can be measured in the early phases, it is important to make sure the key metrics of software design as good as possible.

• 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.

• International Journal of Reliability and Applications
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• 제17권2호
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• pp.149-158
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• 2016

We are enjoying a very comfortable life thanks to modern civilization, however, comfort is not guaranteed to us. Development of software system is a difficult and complex process. Therefore, the main focus of software development is on improving the reliability and stability of a software system. We have become aware of the importance of developing software reliability models and have begun to develop software reliability models. NHPP software reliability models have been developed through the fault intensity rate function and the mean value functions within a controlled testing environment to estimate reliability metrics such as the number of residual faults, failure rate, and reliability of the software. In this paper, we present a new NHPP software reliability model with Burr Type III fault detection rate, and present the goodness-of-fit of the fault detection rate software reliability model and other NHPP models based on two datasets of software testing data. The results show that the proposed model fits significantly better than other NHPP software reliability models.

• International journal of advanced smart convergence
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• 제1권1호
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• pp.57-60
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• 2012

In this paper, we have performed a safety analysis on an automotive evaporator inspection system. We performed the bi-directional analysis on the manufacturing line. Software Fault Tree Analysis (SFTA) as backward analysis and Software Failure Modes, Effects, & Criticality Analysis (SFMECA) as forward analysis are performed alternately to detect potential cause-to-effect relations. The analysis results indicate the possibility of searching and summarizing fault patterns for future reusability.

• International Journal of Computer Science & Network Security
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• 제22권5호
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• pp.348-358
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• 2022

Software fault prediction is a method to compute fault in the software sections using software properties which helps to evaluate the quality of software in terms of cost and effort. Recently, several software fault detection techniques have been proposed to classifying faulty or non-faulty. However, for such a person, and most studies have shown the power of predictive errors in their own databases, the performance of the software is not consistent. In this paper, we propose a hybrid soft computing technique for SFP based on optimal feature extraction and classification (HST-SFP). First, we introduce the bat induced butterfly optimization (BBO) algorithm for optimal feature selection among multiple features which compute the most optimal features and remove unnecessary features. Second, we develop a layered recurrent neural network (L-RNN) based classifier for predict the software faults based on their features which enhance the detection accuracy. Finally, the proposed HST-SFP technique has the more effectiveness in some sophisticated technical terms that outperform databases of probability of detection, accuracy, probability of false alarms, precision, ROC, F measure and AUC.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2008년도 춘계학술대회 논문집
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• pp.952-963
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• 2008

The collection of KTX trainset fault code is made by DEP software. We can improve software function and update data after understanding DEP software function and software structure. For the improvement of trainset function and its performance, the same improvement of performance and structure change as DEP software, which collects and analyzes train's fault information, are required. Accordingly, we made a research for functional strucfure of KTX fault code collection software, STR3F, variable declaration through Script.rxr file and code analysis method and proceeded research for realizing more improved user environment of DEL software and fault analysis method.

• Nuclear Engineering and Technology
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• 제40권5호
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• pp.397-408
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• 2008

This paper describes the application of a software fault tree analysis (FTA) as one of the analysis techniques for a software safety analysis (SSA) at the design phase and its analysis results for the safety-critical software of a digital reactor protection system, which is called the KNICS RPS, being developed in the KNICS (Korea Nuclear Instrumentation & Control Systems) project. The software modules in the design description were represented by function blocks (FBs), and the software FTA was performed based on the well-defined fault tree templates for the FBs. The SSA, which is part of the verification and validation (V&V) activities, was activated at each phase of the software lifecycle for the KNICS RPS. At the design phase, the software HAZOP (Hazard and Operability) and the software FTA were employed in the SSA in such a way that the software HAZOP was performed first and then the software FTA was applied. The software FTA was applied to some critical modules selected from the software HAZOP analysis.

• 융합보안논문지
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• 제13권1호
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• pp.3-10
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• 2013

본 연구에서는 소프트웨어 제품 테스팅 과정에서 관측고장시간에 근거한 결함 발생률을 고려한 소프트웨어 신뢰성 모형에 대하여 연구 하였다. 신뢰성 분야에서 많이 사용되는 S-분포모형을 이용한 새로운 결함 확률을 추가한 문제를 제시하였다. 수명분포는 유한고장 비동질적인 포아송과정을 이용하였다 본 논문의 결함 발생률을 고려한 소프트웨어 고장 자료 분석에서는 고장 시간 자료를 적용하였으며 모수추정 방법은 최우추정법을 이용하여 결함 발생 확률에 대한 관계와 신뢰도를 추정 하였다.