• 한국IT서비스학회:학술대회논문집
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• 2003.05a
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• pp.145-152
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• 2003

본 연구의 선행 연구에서는 증권시스템의 기능점수를 직접 구하여 기능점수와 운영비용과의 회귀분석을 실시하였다. 수집된 자료의 건수가 적었던 관계로 통계적 유의성을 충분하게 확보하지 못하였다. 따라서 본 연구에서는 증권시스템의 기능점수를 직접 측정하는 것이 현실적으로 많은 제약이 있음을 감안하여, 비교적 자료 수집이 용이한 프로그램 본 수를 측정하였다. 이러한 프로그램 본 수는 스텝 수로 1차 변환이 되었고, 스텝 수는 다시 기능점수로 2차 변환이 되었다. 이렇게 변환된 기능점수와 운영비용과의 회귀분석을 실시하였으며, 증권정보시스템 운영비용 추정 모델을 제시하였다.

• The KIPS Transactions:PartD
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• v.10D no.7
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• pp.1137-1144
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• 2003

The existing Function Point method to estimate the software size has been utilized frequently with the management information system. Due to the expanding usage of the real-time and embedded system, the Full Function Point method is being proposed. However, despite many research is being carried out relation to the software size, the research on the model to estimate the development cost from the measured software size is inadequate. This paper analyzed the linear regression model and power regression model which estimate the development cost from the software FFP The power model is selected, which shows its estimation is most adequate.

• The KIPS Transactions:PartD
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• v.15D no.3
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• pp.375-386
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• 2008

Recently, development paradigm of information system is turning into object oriented and component based, and this methodology is leading the software industry. To acclimatize aptly to this trend, users demand the assessment of software expenses to change with the appropriate model of computing costs of the environment, and some people are actually studying the concept of Object Oriented Function Point and UCP method. Especially, Object Oriented Function Point Measurement Process has good points in overcoming the bound of LOC and the existing the Function Point Measurement Process because Object Oriented Function Point Measurement Process is applicable to the early stage of development project mainly with the used cases, and valid to the life long period as the each stage of software products develops, and always understandable to communicate with users by the UML mark rules. Accordingly, this research is to measure Functional Point at ROFP and AOFP in accordance with the development project of information system by the national defense CBD methodology procedures and UML Interrelation Analysis that are recently and widely used in the developmental environment of object oriented information system. Furthermore, this study suggests the measurement method to obtain Functional Point, and identifies service function and object/class function in the correlation analysis of use case and class based on the products and UML modeling via traditional FPA model and object oriented FPA model. Above all, this study is to demonstrate the improvement of traditional Function Point Measurement Process, IFPUG-CPM and software cost basis, and reveal Function Point Measurement Process, which is appropriate to the development of object oriented information system, and suggest the evaluation results of the compatibility through case studies.

• Defense and Technology
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• no.8 s.282
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• pp.46-55
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• 2002

지난 7월호에서는 COCOMO 모델, 기능점수모델, PRICE-S모델, 일반 COSDES 모델 등의 무기체계 S/W 개발비용 산정모델들을 조사 및 분석하여 제시하였다. 이번 8월호에서는 무기체계 소프트웨어 개발비용산저에 영향을 미치는 요소를 기존의 '한소협' 모델, PRICE-S 모델, 기능점수 모델, COCOMO 모델 등 여러 소프트웨어 개발비용 산정모델을 참고 후 무기체계의 특성을 고려하여 식별하였다. 또한 식별된 요소들을 '한소협' 모델의 절차와 방법에 따라 무기체계 소프트웨어의 스텝 수 산정 영향요소, 환경요인 보정계수 영향요소, 제경비 및 기술료 산정 영향요소들을 식별하여 제시하였다.

• 한국IT서비스학회:학술대회논문집
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• 2005.05a
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• pp.372-380
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• 2005

소프트웨어 개발노력 추정에 대한 연구는 소프트웨어가 복잡해지고 범위가 크게 증가함에 따라서 그 중은 지속적으로 부각되고 있다. 관련 프로젝트를 발주하는 업체나, 이를 수주하고 개발을 진행하는 업체에게 원가를 고려하는 측면에서 매우 중요한 부분을 차지하고 있다. 이러한 개발노력 추정을 위하여 다양한 접근 방식들이 고려되어지고 있는데, 그중에서 많이 활용되어지고 있는 방식은 소프트웨어 규모에 기반을 둔 LOC(Line Of Code) 기반 COCOMO (Constructive Cost Model) 모델이나 기능점수(Function Point)를 기반으로 한 회귀분석 모델, 인공지능(Artificial Intelligence)을 활용한 신경망(Neural Network) 모델, 사례분석기법 (CBR, Case Based Reasoning) 등이 있다. 이중에서 최근에 기능점수를 활용한 개발노력 추정에 관한 연구들이 활발히 진행되고 있으나 개발노력 추정에는 소프트웨어 규모의 척도인 기능점수 뿐만 아니라, 개발환경을 구성하는 여러 가지 측면에 대한 고려가 추가되어져야 한다. 이에 본 논문은 최신의 소프트웨어 개발 사례들에 대하여 기능점수 및 추가적인 개발환경 요소들을 면밀히 분석하고, 분석한 내용에 대해서 전문가들의 설문을 통한 빈도분석 및 로지스틱 회귀분석, 데이터마이닝 기법인 신경망 분석 등을 활용하여 개발노력 추정 모델을 구축함으로써, 소프트웨어 개발의 다양한 측면의 중요성을 강조하고, 정확한 추정의 방안을 제시 하고자 노력 하였다.

• Journal of Internet Computing and Services
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• v.10 no.4
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• pp.115-126
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• 2009

A software size estimation has to be analyzed in the beginning of the software life-cycle and helpful to the prediction of its size and cost. The software cost has been calculated by estimating software size from the user's point of view since the function point method based on international standards was introduced for the estimation of software size in 2004. However, the current function point method is not easy to be exploited for unfamiliar user, and has a problem that it cannot estimate the proper size for software such as engineering software, scientific calculations and simulation with complicated internal computational logic. This paper presents an improved model which can simplify the existing function point measurement procedure, and perform the estimation of software size in easy and fast way at the initial stage of project. Moreover, it presents a mathematical weighted value calculation model which can solve the problem of the fixed complexity weighted value and reflect the characteristics of organization as its data is pilled up. Our evaluation shows that the presented model has advantage that it can measure the size more rapidly than the existing FPA methods and has more correlation with LOC.

• The KIPS Transactions:PartD
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• v.17D no.5
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• pp.327-336
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• 2010

This paper proposed software equation that is relation with effort and duration based on function point (FP) software size. Existent software equation based on lines of code (LOC). LOC sees big difference according to development language and there are a lot of difficulties in software size estimation. First, considered method that change LOC to FP. But, this method is not decided definitely conversion ratio between LOC and FP by development language. Also, failed though the conversion ratio motives software formula because was not presented about specification development language. Therefore, we derived software formula directly to large project data that was developed by FP. Firstly, datas that reasonable development period is set among development projects. Secondly, FP through regression analysis about this data and effort, motived relation with FP and duration. Finally, software equation was derived from these relation. Proposed model solves application problems that LOC-based model has and has advantage that application is possible easily in business.

• The KIPS Transactions:PartD
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• v.10D no.7
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• pp.1127-1136
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• 2003

Estimation of software project cost, effort and duration in the early stage of software development cycle is a difficult and key problem in software engineering. Most of models estimate the development effort using the function point that is measured from the requirement specification. This paper presents optimal team size and duration prediction based on function point in order to provide information that can be used as a guide in selecting the most Practical and productive team size for a software development project. We introduce to productive metrics and cost for decision criteria of ideal team size and duration. The experimental is based on the analysis of 300 development and enhancement software project data. These data sets are divide in two subgroups. One is a development project; the other is a maintenance project. As a result of evaluation by productivity and cost measured criteria in two subgroups, we come to the conclusion that the most successful projects has small teams and minimum duration. Also, I proposed that predictive model for team sire and duration according to function point size based on experimental results. The presented models gives a criteria for necessary team site and duration according to the software size.

• 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.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.163-172
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• 2004

In the software development project applying object-oriented development methodology, the research on the UCP(Use Case Point) as a method to estimate development effort is being carried on. The existing research proposes the linear model calculating the development effort that multiplies an invariant on AUCP(Adjusted Use Case Point) which applied technical and environmental factors. However, the statistical model that estimates the development effort using AUCP and UUCP(Unadjusted Use Case Point) is not being studied. The irrelevant relationship of the linear regression model, whose development period is increasing tremendously as the software size increases, is confirmed. Moreover, during the UCP calculating process, there can be errors in FP by applying the TCF(Technical Complexity Factor) and EF(Environmental Factor). This paper presents a non-linear regression model, that does not consider the TCF and EF, and that estimate the development effort from UUCP directly by utilizing the exponential function. An exponential function is selected among the linear, logarithm, polynomial, power, and exponential model via statistical evaluations of the models mentioned above.