• Journal of Korea Society of Industrial Information Systems
• /
• v.5 no.3
• /
• pp.18-29
• /
• 2000

This study presents a cost of efforts estimation model under the environment of developing a software using component software package tools. The approach taken was to drive from variety of sources in an attempt to identify the most significant factors. These sources ranged from already existing cost models like COTS integration cost and COCOMO models to information gathered in a data collection survey. Once the candidate drivers had been identified, the next step was to interview with the experts who had been experienced more than 5 years in component development area to identify the most significant driving factors. From those selected drivers, I established the Cost Estimation Model which is suitable for the developing a software using component software package tools by applying the general from of the well-know COCOMO software cost estimation model. To established the best fit in Korean Software industry, I used Regression statistical analysis with 31 data collections.

• International Journal of Internet, Broadcasting and Communication
• /
• v.15 no.2
• /
• pp.218-226
• /
• 2023

In Korea, we still use function point based cost estimations for software size and cost of a project. The current problem is that we make difficultly calculating function points with requirements and also have less accurate. That is, it is difficult for non-experts to analyze requirements and calculate function point values with them, and even experts often derive different function points. In addition, all stakeholders strongly make the validity and accuracy of the function point values of the project before /after the development is completed. There are methods for performing function point analysis using source code [1][2][3][4] and some researchers [5][6][7] attempt empirical verification of function points about the estimated cost. There is no research on automatic cost validation with source code after the final development is completed. In this paper, we propose automatically how to calculate Function Points based on natural language requirements before development and prove FP calculation based on the final source code after development. We expect validation by comparing the function scores calculated by forward engineering and reverse engineering methods.

• Journal of Software Assessment and Valuation
• /
• v.16 no.1
• /
• pp.27-36
• /
• 2020

The software development cost appraisal is treated as a part of the program completion appraisal, and the software engineering methodology is applied. In particular, software cost estimation techniques have been actively applied. For more information about the software development costs calculation, we can refer to the "SW cost estimation guide". Although successful appraisal of a number of development costs based on the guide has been processed, but a number of cases requiring discussion of appraisal results have been discovered. In this study, we propose a use case-based size estimation method to maintain the accuracy and consistency of size estimation. As a result of performing performance evaluation of the proposed method in an environment similar to the development cost appraisal case, it was proved that the accuracy was improved over the existing function points method.

• The KIPS Transactions:PartD
• /
• v.12D no.5 s.101
• /
• pp.737-744
• /
• 2005

As the portion of software cost in construction of the system related to the national defence is getting higher, the required accuracy of cost estimation on defense software in development is also getting higher. The PRICE S is used to estimate the software cost at the first stage in the development of software promptly. However, the PRICE S is appropriate for the American environment not for the Korean circumstances. Thus, we will present a method to compensate the PRICE S with comparing with the model of Korea Software Industry Association. Moreover, we also present another method to estimate software cost based on function point with backfiring approach, which will be used for the software projects planned. Finally, we expect that our works will provide a solution for applying the function point in the future and will increase the accuracy of cost estimation in software development.

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

• Korean Management Science Review
• /
• v.20 no.2
• /
• pp.179-196
• /
• 2003

Function point model is the international standard method to measure the software size which is one of the most important factors to determine the software development cost. Function point model can successfully be applied only when the detailed specification of users' requirements is available. In the domestic public sector, however, the budgeting for software projects is carried out before the requirements of softwares ere specified in detail. Therefore, an efficient function point estimation method is required to apply function point model at the early stage of software development projects. The purpose of this paper is to compare various function point estimation methods and analyse their accuracies in domestic software projects. We consider four methods : NESMA model, ISBSG model, the simplified function point model and the backfiring method. The methods are applied to about one hundred of domestic projects, and their estimation errors are compared. The results can used as a criterion to select an adequate estimation model for function point counts.

• Proceedings of the KSR Conference
• /
• 2007.11a
• /
• pp.777-783
• /
• 2007

Life cycle costing is one of the most effective cost approaches when we choose a solution from series of alternative so the least long-term cost ownership is achieved. Life cycle costing in railway industry has been focused on the prediction of investment for railway vehicles. But in today, the life cycle cost, LCC, prediction on the aspect of operation and maintenance cost through whole life cycle is highly necessary. In this paper, we present a strategy for the development of life cycle cost estimation software on the aspect of maintenance strategies of railway vehicle. For this purpose, we suggested a structure of LCC software based on the UNIFE LCC model. And we developed a pilot version of software to evaluate the LCC model that we suggested for railway vehicle. We performed LCC analysis on the brake module of metro vehicle in case study and concluded that the software and model developed in this research could enough to support engineers in choosing better cost effective solutions from many alternatives.

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

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.3
• /
• pp.209-216
• /
• 2009

The accurate estimation of software development cost is important to a successful development in software engineering. This paper presents a software cost estimation method using a support vector machine. Support vector machine is one of the efficient techniques for classification, and it is the classification method of input data based on Maximum-Margin Hyperplane. But SVM has the problem of the selection of optimal parameters, because it is dependent on user's parameters. This paper selects optimized SVM parameters using advanced method, and estimates software development cost. The proposed approach outperform some recent results reported in the literature.

• The KIPS Transactions:PartD
• /
• v.16D no.5
• /
• pp.729-736
• /
• 2009

The accurate estimation of software development cost is important to a successful development in software engineering. Until recent days, the model using regression analysis based on statistical algorithm and machine learning method have been used. However, this paper estimates the software cost using support vector regression, a sort of machine learning technique. Also, it finds the best set of optimized parameters applying genetic algorithm. The proposed GA-SVR model outperform some recent results reported in the literature.