A New Regression Based Software Cost Estimation Model Using Power Values
The paper aims to provide for the improvement of software estimation research through a new regression model. The study design of the paper is organized as follows. Evaluation of estimation methods based on historical data sets requires that these data se
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UBITAK-UEKAE, National Research Institute of Electronics and Cryptology, PK 74 Gebze KOCAELI - Turkey [email protected] 2 Ege University, Department of Computer Engineering, Bornova IZMIR – Turkey {aybars.ugur, serdar.korukoglu}@ege.edu.tr 3 Dokuz Eylül University, Department of Econometrics, Buca, IZMIR – Turkey [email protected]
Abstract. The paper aims to provide for the improvement of software estimation research through a new regression model. The study design of the paper is organized as follows. Evaluation of estimation methods based on historical data sets requires that these data sets be representative for current or future projects. For that reason the data set for software cost estimation model the International Software Benchmarking Standards Group (ISBSG) data set Release 9 is used. The data set records true project values in the real world, and can be used to extract information to predict new projects cost in terms of effort. As estimation method regression models are used. The main contribution of this study is the new cost production function that is used to obtain software cost estimation. The new proposed cost estimation function performance is compared with related work in the literature. In the study same calibration on the production function is made in order to obtain maximum performance. There is some important discussion on how the results can be improved and how they can be applied to other estimation models and datasets. Keywords: Software Cost Estimation, Regression Analysis, Software Cost Models.
1 Introduction Software development effort estimates are the basis for project bidding, budgeting and planning. These are critical practices in the software industry, because poor budgeting and planning often has dramatic consequences [1]. The common argument on the project cost overruns is very large. Boraso reported that [2] 60% of large projects significantly overrun their estimates and 15% of the software projects are never completed due to the gross misestimating of development effort. Delivering a software product on time, within budget, and to an agreed level of quality is a critical concern for software organizations. Accurate estimates are crucial for better planning, monitoring and control [3]. Jones [4] proposes software quality as H. Yin et al. (Eds.): IDEAL 2007, LNCS 4881, pp. 326–334, 2007. © Springer-Verlag Berlin Heidelberg 2007
A New Regression Based Software Cost Estimation Model Using Power Values
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“software quality means being on time, within budget, and meeting user needs”. On the other hand, it is necessary to give the customer or the developer organization an early indication of the project costs. As a consequence, considerable research attention is now directed at gaining a better understanding of the software development process as well as constructing and evaluating software cost estimation tools. Therefore, there has been excessive focus of research on estimation methods from a variety of fields. Statistical regression analysis is the most sui
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