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A New Regression Based Software Cost Estimation Model Using Power Values

  • Oktay Adalier
  • Aybars Uğur
  • Serdar Korukoğlu
  • Kadir Ertaş
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4881)

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 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Oktay Adalier
    • 1
  • Aybars Uğur
    • 2
  • Serdar Korukoğlu
    • 2
  • Kadir Ertaş
    • 3
  1. 1.TUBITAK-UEKAE, National Research Institute of Electronics and Cryptology, PK 74 Gebze KOCAELITurkey
  2. 2.Ege University, Department of Computer Engineering, Bornova IZMIRTurkey
  3. 3.Dokuz Eylül University, Department of Econometrics, Buca, IZMIRTurkey

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