• Journal of KIISE:Software and Applications
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• v.35 no.10
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• pp.589-599
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• 2008

Accurate software effort estimation has always been a challenge for the software industrial and academic software engineering communities. Many studies have focused on effort estimation methods to improve the estimation accuracy of software effort. Although data quality is one of important factors for accurate effort estimation, most of the work has not considered it. In this paper, we investigate the influence of outlier elimination on the accuracy of software effort estimation through empirical studies applying two outlier elimination methods(Least trimmed square regression and K-means clustering) and three effort estimation methods(Least squares regression, Neural network and Bayesian network) associatively. The empirical studies are performed using two industry data sets(the ISBSG Release 9 and the Bank data set which consists of the project data collected from a bank in Korea) with or without outlier elimination.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.566-570
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• 2010

Use Case Point(UCP) is a measure of a software project size for software effort estimation based on use case. UCP measures the size of the software project based on the use case model. Because UCP is based on the use case model, it is intuitive and easy to obtain. Also, it does not require extra artifacts. On the other hand, UCP has some problems. UCP assumes every transaction has the same complexity. But, the number of operations and complexity of operations may affect complexity of transaction. In addition, UCP uses simple rating scale of complexity, but it may be inadequate for detailed estimates. To solve these problems, we suggest "Transaction Point(TP)", a size measure based on use case transaction. TP considers actors and operations in transaction. Complexity of transaction is based on the number of operations and complexity of operation, so it can support detailed estimation.

• Smart Media Journal
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• v.11 no.7
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• pp.19-27
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• 2022

The artificial intelligence software market is expected to grow sixfold from 2020 to 2025. However, the software development process is not standardized and there is no standard for calculating the cost. Accordingly, each AI software development company calculates the input man-hours according to their respective development procedures and presents this as the basis for the development cost. In this study, the development stage of "artificial intelligence-based software" that learns with a large amount of data and derives and applies an algorithm was defined, and the required labor was collected by conducting a survey on the number of man-hours required for each development stage targeting developers. Correlation analysis and regression analysis were performed between the collected man-hours for each development stage, and a model for predicting the man-hours for each development stage was derived. As a result of testing the model, it showed an accuracy of 92% compared to the collected airborne effort. The man-hour prediction model proposed in this study is expected to be a tool that can be used simply for estimating man-hours and costs.

• Journal of Software Engineering Society
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• v.26 no.4
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• pp.77-92
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• 2013

To plan a software project, the manager (1)make a work breakdown structure (WBS), (2) estimate efforts for each task, (3) assign employee to each task, and (4) estimate overall schedule. When software project becomes complicated, the possible combination of WBS, effort, and employee assignments dramatically becomes larger. Software planning tool can help software project managers to deal with this complexity. In this research, we discuss with a group of experts who work in software industry, to elicit practical requirements that should be considered in the software planning technique. Considering these requirements, we develop a software project planning tool APP (Automatic Project Planner) which provide effort estimation based on historical knowledge data and automatic human resource allocation. Our technique can be the basis of reasonable and practical software project planing.

• 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.

• Explosives and Blasting
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• v.19 no.1
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• pp.63-70
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• 2001

발파진동에 영향을 미치는 여러 매개변수들 중에서 현재 발파진동 예상식을 도출하기 위해 장약량과 거리를 매개변수로 하여 발파진동을 예측하고 있다. 여기에 사용되는 장약랑은 지발당 최대장약량으로, 발파당 장약량과의 관계는 언급하고있지 않다. 따라서 본 연구에서는 지발당 최대장약량이 동일한 상태에서 발파공수를 변화시키는 방법으로 발파당 장약량이 변화할 때 발파진동속도의 변화를 비교·분석하였다. 발파공수를 5공에서 10공까지 변화시 켜가며 발파진동을 폭정하고 분석한 결과 지발당 장약량이 동일함에도 불구하고 공수가 증가함에 따라 환산거리 60∼90 구간에서 진동속도가 높게 측정되었다

• The Transactions of the Korea Information Processing Society
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• v.2 no.1
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• pp.34-44
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• 1995

One of the most important problems faced by software developers and users is the prediction of the size of programming system and its development effort. This article define the identical characteristics for structured specification which is consisted of Data Flow Diagram, Data Dictionary and Mini Specification and apply quantitative estimation factor of structured specification to program code metrics, Moreover, concerning DFD which is made up of component element of structured specification executed quantitative estimation experiment. In the result, we propose man/month prediction model of lower progression with production on analysis phase of upper progression.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.424-426
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• 2005

다양하고 복잡해지는 소프트웨어 프로젝트를 효율적으로 수행하기 위한 방법론들 중에서 프로세스 평가와 개선에 대한 관심이 높아지고 있다. 그러나 소프트웨어 프로세스 개선을 위한 방법론들은 조직이 비즈니스 목표인 정량적인 품질 관리에 도달하게 하기 위한 측정과 분석활동에 대한 구체적인 가이드라인을 제시하지 않는다. 본 연구는 효과적인 정량적인 프로세스 및 프로젝트 관리를 위해 Six Sigma 방법론을 도입, CMM 레벨 2의 예측공수모델에 적용하여 제시, 프로세스 측정과 분석활동의 개선 가능성에 대해 모색하고자 한다.

• The KIPS Transactions:PartD
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• v.8D no.2
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• pp.154-165
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• 2001

A number of attempts to develop methods for measuring software effort have been focused on the area of software engineering and many models have also been suggested to estimate the effort of software projects. Almost all current models use algorithmic or statistical mechanisms, but the existing algorithmic effort estimation models have failed to produce accurate estimates. Furthermore, they are unable to reflect the rapidly changing technical environment of software development such as module reuse, 4GL, CASE tool, etc. In addition, these models do not consider the paradigm shift of software engineering and information systems(i.e., Object Oriented system, Client-Server architecture, Internet/Intranet based system etc.). Thus, a new approach to software effort estimation is needed. After reviewing and analyzing the problems of the current estimation models, we have developed a model and a system architecture that will improve estimation performance. In this paper, we have adopted a neural network model to overcome some drawbacks and to increase estimation performance. We will also address the efficient system architecture and estimation procedure by a similar case-based approach and finally suggest the heuristic search method to find the best estimate of target project through empirical experiments. According to our experiment with the optimally parsimonious neural network model the mean error rate was significantly reduced to 14.3%.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.233-240
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• 2016

Information system development projects, have a mechanism for many of the costs generated by a variety of risk factors. In general, the probability that the software project of the information system is carried out successfully in the delivery time is very low. This prediction of a formal cost is needed as the most important factor since it can prevent the project from being failed. However, objectivity of most of the project scale calculation during the calculation criteria is insufficient. Further, it is the actual situation that the management of the base line is not properly made during the project. Therefore, in this paper, we propose a model to calculate the number of steps it takes to develop on the basis of a methodology in an attempt to overcome the limitation of being unpractical in the early stage of the information system development project. It is expected to be a tool to estimate the effort and cost required by the information system development business through these convergence proposals model.