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A Study on Development Cost Attributes Analysis of NHPP Software Reliability Model Based on Rayleigh Distribution and Inverse Rayleigh Distribution (레일리 분포와 역-레일리 분포에 근거한 NHPP 소프트웨어 신뢰성 모형의 개발비용 속성 분석에 관한 연구)

  • Yang, Tae-Jin
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.12 no.6
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    • pp.554-560
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    • 2019
  • In this study, after applying the finite failure NHPP Rayleigh distribution model and NHPP Inverse Rayleigh distribution model which are widely used in the field of software reliability to the software development cost model, the attributes of development cost and optimal release time were compared and analyzed. To analyze the attributes of software development cost, software failure time data was used, parametric estimation was applied to the maximum likelihood estimation method, and nonlinear equations were calculated using the bisection method. As a result, it was confirmed that Rayleigh model is relatively superior to Inverse Rayleigh model because software development cost is relatively low and software release time is also fast. Through this study, the development cost attributes of the Rayleigh model and the Inverse Rayleigh model without the existing research examples were newly analyzed. In addition, we expect that software developers will be able to use this study as a basic guideline for exploring software reliability improvement method and development cost attributes.

A SOFTWARE RELIABILITY ESTIMATION METHOD TO NUCLEAR SAFETY SOFTWARE

  • Park, Gee-Yong;Jang, Seung Cheol
    • Nuclear Engineering and Technology
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    • v.46 no.1
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    • pp.55-62
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    • 2014
  • A method for estimating software reliability for nuclear safety software is proposed in this paper. This method is based on the software reliability growth model (SRGM), where the behavior of software failure is assumed to follow a non-homogeneous Poisson process. Two types of modeling schemes based on a particular underlying method are proposed in order to more precisely estimate and predict the number of software defects based on very rare software failure data. The Bayesian statistical inference is employed to estimate the model parameters by incorporating software test cases as a covariate into the model. It was identified that these models are capable of reasonably estimating the remaining number of software defects which directly affects the reactor trip functions. The software reliability might be estimated from these modeling equations, and one approach of obtaining software reliability value is proposed in this paper.

A Performance Comparative Evaluation for Finite and Infinite Failure Software Reliability Model using the Erlang Distribution (어랑분포를 적용한 유한 및 무한 고장 소프트웨어 신뢰모형에 관한 성능 비교 평가에 관한 연구)

  • Yang, Tae-Jin
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.9 no.4
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    • pp.351-358
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    • 2016
  • Science and technology is developing rapidly as more powerful software with the rapid development of software testing and reliability assessment by the difficulty increases with the complexity of the software features of the larger increases NHPP software reliability models for failure analysis can have, in the literature, exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, finite failure NHPP models that assuming the expected value of the defect and infinite failures NHPP models that repairing software failure point in time reflects the situation, were presented for comparing property. Commonly used in the field of software reliability based on Erlang distribution software reliability model finite failures and infinite failures were presented for performance comparative evaluation problem. As a result, finite failure model is better than infinite failure model effectively. The parameters estimation using maximum likelihood estimation in the course of this study was conducted. As the results of this research, software developers to identify software failure property be able to help is concluded.

Using Artificial Neural Network for Software Development Efforts Estimation on (인공신경망을 이용한 소프트웨어 개발공수 예측모델에 관한 연구)

  • Jeon, Eung-Seop
    • The Transactions of the Korea Information Processing Society
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    • v.3 no.1
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    • pp.211-224
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    • 1996
  • In the research area of estimation of the software development efforts, a number of researches have been accomplished in order to control the costs and to make software more competitive. However, most of them were restricted to the functional algorithm models or the statistic models. Moreover, since they are dealing with the cases of foreign countries, the results are hard to apply directly to the domestic environment for the efficient project management because of lack of accuracy, fitness, flexibility and portability. Therefore, it is appropriate to suggest and propose a new approach supported by artificial neural network which is composed of back propagation and feel-forward algorithms to improve the exactness of the efforts estimation and to advance practical uses. In this study, the artificial neural network approach is used to model the software cost estimation and the results are compared with the revised COCOMO and the multiregression model in order to validate the superiority of the model.

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The Comparison of Parameter Estimation for Nonhomogeneous Poisson Process Software Reliability Model (NHPP 소프트웨어 신뢰도 모형에 대한 모수 추정 비교)

  • Kim, Hee-Cheul;Lee, Sang-Sik;Song, Young-Jae
    • The KIPS Transactions:PartD
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    • v.11D no.6
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    • pp.1269-1276
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    • 2004
  • The Parameter Estimation for software existing reliability models, Goel-Okumoto, Yamada-Ohba-Osaki model was reviewed and Rayleigh model based on Rayleigh distribution was studied. In this paper, we discusses comparison of parameter estimation using maximum likelihood estimator and Bayesian estimation based on Gibbs sampling to analysis of the estimator' pattern. Model selection based on sum of the squared errors and Braun statistic, for the sake of efficient model, was employed. A numerical example was illustrated using real data. The current areas and models of Superposition, mixture for future development are also employed.

An Estimating Method for Software Testing Manpower (소프트웨어 시험 인력의 추정 방법)

  • Park Ju-Seok
    • The KIPS Transactions:PartD
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    • v.11D no.7 s.96
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    • pp.1491-1498
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    • 2004
  • Successful project planning relics on a good estimation of the manpower required to complete a project, together with the schedule options that may be available. Despite the extensive research done developing new and better models, existing software manpower estimation models are present only the total manpower or instantaneous manpower distribution according to the testing time for the software life-cycle. This paper suggests the manpower estimating models for software testing phase as well as testing process and debugging process in accordance with de-tected faults. This paper presents the polynomial model for effort based on testing and debugging faults. These models are verified by 5 different software project data sets with coefficient of determination and mean magnitude of relative error for adaptability of model.

Software Maintenance Cost Estimation using RBF Network (RBF망을 이용한 소프트웨어 유지보수 비용 추정)

  • 박주석;정기원
    • Journal of KIISE:Software and Applications
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    • v.31 no.5
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    • pp.555-562
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    • 2004
  • Software industry has put more emphasis on maintenance and enhancement work than on the new development. The existing effort estimation models can still be applied to maintenance projects, though modifications are needed. This paper suggests a way to estimate the size of a maintenance project from the regression analysis of ISBSG's benchmarking data. First of all, among the 3 elements(addition, modification and deletion of the program) which influences the software cost, we selected and classified 4 groups from a total of 8 which shows actual maintenance cost from ISBSG's data. Moreover, we developed statistical model and a model which uses RBF(Radial Basis Function) Network and after evaluating each functions we concluded that the RBF Network is superior to the statistical model.

Sensitivity Analysis of HAZUS Results Attenuation (지진파 감쇄식에 대한 민감도 분석 연구 (HAZUS))

  • Oh, Tae-Seok;Kim, Jun-Kyoung;Kang, Ik-Bum;Yoo, Seong-Hwa
    • 한국지구물리탐사학회:학술대회논문집
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    • 2006.06a
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    • pp.247-252
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    • 2006
  • This study analysed the sensitivity of the attenuation functions for the seismic hazard estimation. For the seismic hazard estimation, this study used HAZUS software, which is developed originally by FEMA(USA). The scenario earthquake (Mw=6.0) is located the Hongsung area, where one of the recent macro earthquakes occurred in 1978. The area for seismic hazard estimation is assumed to be Boryung city in Choongnam-do. Three attenuation functions were applied for the sensitivity analysis. The results show that the attenuation functions have much influences on the seismic hazard on the various types of buildings. Therefore the attenuation function is very important factor for the seismic hazard estimation.

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Virtual Environment Modeling for Battery Management System

  • Piao, Chang-Hao;Yu, Qi-Fan;Duan, Chong-Xi;Su, Ling;Zhang, Yan
    • Journal of Electrical Engineering and Technology
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    • v.9 no.5
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    • pp.1729-1738
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    • 2014
  • The offline verification of state of charge estimation, power estimation, fault diagnosis and emergency control of battery management system (BMS) is one of the key technologies in the field of electric vehicle battery system. It is difficult to test and verify the battery management system software in the early stage, especially for algorithms such as system state estimation, emergency control and so on. This article carried out the virtual environment modeling for verification of battery management system. According to the input/output parameters of battery management system, virtual environment is determined to run the battery management system. With the integration of the developed BMS model and the external model, the virtual environment model has been established for battery management system in the vehicle's working environment. Through the virtual environment model, the effectiveness of software algorithm of BMS was verified, such as battery state parameters estimation, power estimation, fault diagnosis, charge and discharge management, etc.

Non-intrusive Calibration for User Interaction based Gaze Estimation (사용자 상호작용 기반의 시선 검출을 위한 비강압식 캘리브레이션)

  • Lee, Tae-Gyun;Yoo, Jang-Hee
    • Journal of Software Assessment and Valuation
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    • v.16 no.1
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    • pp.45-53
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    • 2020
  • In this paper, we describe a new method for acquiring calibration data using a user interaction process, which occurs continuously during web browsing in gaze estimation, and for performing calibration naturally while estimating the user's gaze. The proposed non-intrusive calibration is a tuning process over the pre-trained gaze estimation model to adapt to a new user using the obtained data. To achieve this, a generalized CNN model for estimating gaze is trained, then the non-intrusive calibration is employed to adapt quickly to new users through online learning. In experiments, the gaze estimation model is calibrated with a combination of various user interactions to compare the performance, and improved accuracy is achieved compared to existing methods.