• Journal of Information Technology Services
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• v.5 no.1
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• pp.97-109
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• 2006

As software becomes more complex and its scope dramatically increases, the importance of research on developing methods for estimating software development efforts has been increased. Such accurate estimation has a prominent impact on the development projects. To develop accurate effort estimation models, many studies have been conducted among the academia and the practitioners. Out of the numerous methods, Constructive Cost Model (COCOMO) based on Line of Code (LOC), Regression Model based on Function Point (FP) were the most popular models in the past. As today's development environments are dynamically changing, these traditional methods do not work anymore. There is an impending need to develop an accurate estimation model which accommodates itself to the new environments. As a possible solution, this research proposes and evaluates an software development estimation model based on function points and neural networks.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.11a
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• pp.349-352
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• 2004

성공적인 소프트웨어 프로젝트를 목표로 합리적인 계획을 수립하기 위하여 프로젝트의 전체 규모에 대한 신속하고 정확한 견적이 중요해지고 있다. IFPUG의 FPA 견적방식은 이미 검증되어 널리 사용되고 있으나, 복잡성과 모호성으로 인하여 실제 SI 업체의 견적 수행에는 어려움이 있으며 견적작업의 고비용을 초래하고 있다. 본 논문은 기존 FPA 방식의 문제점을 지적하고 이를 개선한 PFP 모델을 제시함으로써 기존보다 쉽고 효과적이며 효율적인 기능점수 견적을 가능하게 하였다.

• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.397-402
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• 2003

This paper proposes an efficient fixed-point (FP) algorithm for improving performances of the independent component analysis (ICA) based on neural networks. The proposed algorithm is the FP algorithm based on Newton method for ICA using the adaptive learning parameters. The purpose of this algorithm is to improve the separation speed and performance by using the learning parameters in Newton method, which is based on the first order differential computation of entropy optimization function. The learning rate and the moment are adaptively adjusted according to an updating state of inverse mixing matrix. The proposed algorithm has been applied to the fingerprints and the images generated by random mixing matrix in the 8 fingerprints of 256${\times}$256-pixel and the 10 images of 512$\times$512-pixel, respectively. The simulation results show that the proposed algorithm has the separation speed and performance better than those using the conventional FP algorithm based on Newton method. Especially, the proposed algorithm gives relatively larger improvement degree as the problem size increases.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.433-440
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• 2013

The Ministry of Land, Infrastructure and Transport was developed the Construction CALS system for improvement of the construction economy. Construction CALS system is consist by Construction Portal System, Construction Management System, Construction Authorization and Permission System, Compensation Management System, Facility Maintenance Management System and has utilized at construction site of more than 900. Ministry of Land, Infrastructure and Transport and related researcher was proposed method of various function improvements for usability of the system. However, the proposed method was expanded the problems like increase of system management cost and development cost with decrease of data process rate. The problem was increases because has added of only service function without modify of software structure to the system on each different platform base. One of the methods for solving problems is to apply the e-Government framework and then integrated the different platform. The purpose of this paper is analyse of the applicability and efficiency of e-Government framework to the construction CALS system. For that was analyzed the e-Government standard framework and the developments case. And then was verified about the adaption possibility and efficiency by use the Function Point tool.

• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.597-604
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• 2004

Accurate software cost estimation is essential to both developers and customers. Most of the cost estimating models based on the size measure methods, such as LOC and FP, are obtained through size estimation. The accuracy of size estimation directly influences the accuracy of cost estimation. As a result, the overall structure of regression-based cost models applies the power function based on software size. Many growth phenomenon in nature such as the growth in living organism, performance of technology, and learning capability of human show an S-shaped curve. This paper proposes a model which estimates the developing effort by using the growth curve. The presented model assumes that the relation cost and size follows the growth curve. The appropriateness of the growth curve model based on Function Point, Full-Function Point and Use-Case Point, which are the general methods in estimating the software size have been confirmed. The proposed growth curve model shows similar performance with power function model. In conclusion, the growth curve model can be applied in the estimation of the software cost.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.4
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• pp.139-148
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• 2014

With the development of IT, the financial sector has grown dramatically in Non face-to-face channel. However, because the initial costs calculation model which reflects the characteristics of the financial system does not exist, deteriorating reliability of budget establishment and low-price booking competition appeared. This negative situation leads to degradation of Internet Banking systems and customers who use these financial products have many troubles. Therefore, this paper improves the Initial Costs Expectation Model based on FPA & Expert Judgement Model. And it verified the effectiveness of this model through the regression analysis. As a result, we developed the Initial Costs Expectation Model for Internet Banking systems based on FPA, which is increased in accuracy than existing Cost Expectation Models.

• The KIPS Transactions:PartD
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• v.8D no.3
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• pp.241-246
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• 2001

Area of software measurement in software engineering is active more than thirty years. There is a huge collection of researches but still no a concrete software cost estimation model. If we want to measure the cost-effort of a software project, we need to estimate the size of the software. A number of software metrics are identified in the literature ; the most frequently cited measures are LOC(line of code) and FPA(function point analysis). The FPA approach has features that overcome the major problems with using LOC as a measure of system size. This paper presents an neural networks(NN) models that related software development effort to software size measured in FPs and function element types. The research describes appropriate NN modeling in the context of a case study for 24 software development projects. Also, this paper compared the NN model with a regression analysis model and found the NN model has better estimative accuracy.

• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.36-44
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• 2021

Estimation on SW Sizing applied to fintech is very difficult, a task requiring long time, it is difficult for client companies and developer companies to accurately calculate the size of software development. The size is generally estimated based on the experience of project managers and the general functional scoring method. In this paper, propose a model that can be applied to fintech development projects by quantitatively calculating the required functions from the user's point of view, measuring the scale, and calculating the scale in real time. Through the proposed model, the amount of work can be estimated prior to development and the size can be measured, and the M/M and the estimated quotation amount can be calculated based on the program list by each layer. In future studies, by securing size computation data on existing the Fintech Project in mass, research on accurate size computation would be required.

• The KIPS Transactions:PartD
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• v.9D no.2
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• pp.259-266
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• 2002

The main issue in software development is the ability of software project effort and cost estimation in the early phase of software life cycle. The regression models for project effort and cost estimation are presented by function point that is a software sire. The data sets used to conduct previous studies are of ten small and not too recent. Applying these models to 789 project data developed from 1990 ; the models only explain fewer than 0.53 $R^2$(Coefficient of determination) of the data variation. Homogeneous group in accordance with project delivery rate (PDR) divides the data sets. Then this paper presents general effort estimation models using project delivery rate. The presented model has a random distribution of residuals and explains more than 0.93 $R^2$ of data variation in most of PDR ranges.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.3
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• pp.210-218
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• 2002

This paper proposes an efficient separation method of the composite images by using independent component analysis(ICA) based on neural networks of the approximate learning algorithm. The Proposed learning algorithm is the fixed point(FP) algorithm based on Secant method which can be approximately computed by only the values of function for estimating the root of objective function for optimizing entropy. The secant method is an alternative of the Newton method which is essential to differentiate the function for estimating the root. It can achieve a superior property of the FP algorithm for ICA due to simplify the composite computation of differential process. The proposed algorithm has been applied to the composite signals and image generated by random mixing matrix in the 4 signal of 500-sample and the 10 images of $512{\times}512-pixel$, respectively The simulation results show that the proposed algorithm has better performance of the learning speed and the separation than those using the conventional algorithm based method. It also solved the training performances depending on initial points setting and the nonrealistic learning time for separating the large size image by using the conventional algorithm.