• The Journal of Society for e-Business Studies
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• v.7 no.2
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• pp.173-190
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• 2002

Over the past decade, numerous software managers and engineers have been concerned with measuring the size and complexity of software systems. Function point analysis technique is one of the most popular software sizing techniques. A reasonable software development plan through cost and time estimation should be a prerequisite for the successful project at the beginning stage of the project. It is generally known that software size measurement is useful for this kind of estimation and the function point analysis technique would be more effective than the others. However, it is difficult to apply the technique to object-oriented methodology widely used in the software industry. Thus, the purpose of this study is to present a case study on how to apply function point analysis technique to sizing of the software systems based on UML. The results of this study can be useful to managers and engineers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1307-1317
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• 2010

The various models that estimate the reliability of application software system had been made. But most of the existing models are inconvenient to industrial fields because so complicated mathematic methods as method of estimation parameter have been used. The two purposes of this paper are to develop the reliability estimation model which was easily applied to industrial fields, and to prove no differences between the existing models and the developed model. Therefore the reliability of software system and handled informations are upgraded by far.

• Convergence Security Journal
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• v.12 no.1
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• pp.9-16
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• 2012

Due to the large scale application of software systems, software reliability plays an important role in software developments. In this paper, a software reliability growth model (SRGM) is proposed for testing time. The testing time on the right is truncated in this model. The intensity function, mean-value function, reliability of the software, estimation of parameters and the special applications of Pareto NHPP model are discussed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection, depended on difference between predictions and actual values, were efficient using the mean square error and $R_{SQ}$.

• Journal of KIISE:Software and Applications
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• v.36 no.4
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• pp.273-282
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• 2009

Missing data is one of the common problems in building analysis or prediction models using software project data. Missing imputation methods are known to be more effective missing data handling method than deleting methods in small software project data. While K nearest neighbor imputation is a proper missing imputation method in the software project data, it cannot use non-missing information of incomplete project instances. In this paper, we propose an approach to missing data imputation for numerical software project data by combining K nearest neighbor and maximum likelihood estimation; we also extend the average absolute error measure by normalization for accurate evaluation. Our approach overcomes the limitation of K nearest neighbor imputation and outperforms on our real data sets.

• Journal of the Korea Society of Computer and Information
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• v.14 no.7
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• pp.1-8
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• 2009

In this paper, make a study decision problem called an optimal release policies after testing a software system in development phase and transfer it to the user. The optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement is generally accepted. The Bayesian parametric inference of model using log Poisson execution time employ tool of Markov chain(Gibbs sampling and Metropolis algorithm). In a numerical example by T1 data was illustrated. make out estimating software optimal release time from the maximum likelihood estimation and Bayesian parametric estimation.

• The KIPS Transactions:PartD
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• v.13D no.6 s.109
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• pp.815-822
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• 2006

It is very important that they accurately predict the software development cost in the early stage of a software development. Because cost estimations are required when bidding for a contract or determining whether a project is feasible in terms of a cost-benefit analysis. The criterions of the software cost estimation was set up to calculate software development cost more exactly, which is applied to made up a budget of the software business or to calculate a suitable cost to start the business in our country. However, as the software technology and environment are changing very rapidly, it need to enhance the criterion of the cost estimation continuously. Therefore, we tried to apply technology of software and a variety of factors of environment changes in present. Most of all, we proposed an introduction and readjustment of the adjustment factor applying 14 general system characteristics to improve the accuracy of the cost estimation and the schedule adjustment factor that is required by practicians. For evaluating the accuracy in terms of the real data, we have used MMRE & PRED. In result, we proved that the accuracy was clearly improved by applying the scale factor and readjusted VAF with 14 general system characteristics. Moreover, we evaluated the accuracy of the schedule adjustment factor.

• Journal of Astronomy and Space Sciences
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• v.41 no.2
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• pp.61-78
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• 2024

This study developed a real-time spacecraft pose estimation algorithm that combined a deep learning model and the least-squares method. Pose estimation in space is crucial for automatic rendezvous docking and inter-spacecraft communication. Owing to the difficulty in training deep learning models in space, we showed that actual experimental results could be predicted through software simulations on the ground. We integrated deep learning with nonlinear least squares (NLS) to predict the pose from a single spacecraft image in real time. We constructed a virtual environment capable of mass-producing synthetic images to train a deep learning model. This study proposed a method for training a deep learning model using pure synthetic images. Further, a visual-based real-time estimation system suitable for use in a flight testbed was constructed. Consequently, it was verified that the hardware experimental results could be predicted from software simulations with the same environment and relative distance. This study showed that a deep learning model trained using only synthetic images can be sufficiently applied to real images. Thus, this study proposed a real-time pose estimation software for automatic docking and demonstrated that the method constructed with only synthetic data was applicable in space.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.2
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• pp.1-10
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• 2013

In this paper, make a study decision problem called an optimal release policies after testing a software system in development phase and transfer it to the user. In the course of correcting or modifying the software, finite failure non-homogeneous Poisson process model, presented and was proposed release policies of the life distribution, half-logistic and log-logistic distributions model which used to an area of reliability because of various shape and scale parameter. In this paper, discuss optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement. In a numerical example, the parameter estimation using maximum likelihood estimation of failure time data make out, and software optimal release time was estimated.

• Journal of Software Assessment and Valuation
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• v.16 no.1
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• pp.21-26
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• 2020

The completeness appraisal of software is performed in various forms, such as assessing the completion level in the development process, calculating the defect rate, estimating the development cost, and calculating the redevelopment cost. Along with this, the problem that is often dealt with is estimation of the development time. Even in a dispute over completeness due to delays in software development, issues of calculating an appropriate development time required to develop a delivery software or a development time required for change requests are often included in the appraisal request. In this paper, we introduce the procedure and method for estimating the appropriate project time of software development so that the appraiser can be applied to the appraisal work for determining the completeness. The method is based on the manual for calculating the appropriate project period of software development project.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1999.05a
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• pp.97-105
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• 1999

An important task for any software project manager is to be able to predict and control project size. Unfortunately, there is comparatively little work that deals with the problem of building estimation methods for software size in fourth-generation languages systems. In this paper, we propose a new estimation method for estimating for software size based on minimum relative error(MRE) criterion. The characteristic of the proposed method is insensitive to the extreme values of the observed measures which can be obtained early in the development life cycle. In order to verify the performance of the proposed estimation method for software size in terms of both quality of fit and predictive quality, the experiments has been conducted for the dataset I and II, respectively. For the data set I and II, our proposed estimation method was shown to be superior to the traditional method LS and RLS in terms of both the quality of fit and predictive quality when applied to data obtained from actual software development projects.