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Effort Prediction Model Using Similarity for Embedded Software Development

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Computational Science and Its Applications - ICCSA 2006 (ICCSA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3981))

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Abstract

In this paper, we propose an effort prediction model in which data including missing values is complemented by using the collaborative filtering [1, 2, 3] and the effort of projects is derived from a multiple regression analysis [4, 5] using the data. Because companies, recently, focus on methods to predict effort of projects, which prevent project failures such as exceeding deadline and cost, due to more complex embedded software, which brings the evolution of the performance and function enhancement [6, 7, 8]. Moreover, we conduct the evaluation experiment that compared the accuracy of our method with other two methods according to five criteria to confirm their accuracy. The results of the experiment shows that our method gives predictions the best in the five evaluation criteria.

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References

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Author information

Authors and Affiliations

  1. Department of Business Administration, Aichi University, 370 Kurozasa, Miyoshi-cho, Nishikamo-gun, Aichi, 470-0296, Japan

    Kazunori Iwata

  2. Business Innovation Driving Department, SPI Driving Group, Planning Office, Omron Software Co., Ltd., Shiokoji Horikawa, Shimogyo-ku, Kyoto, 600-8234, Japan

    Yoshiyuki Anan

  3. Department of Culture-Information Studies, Sugiyama Jogakuen University, 17-3, Moto-machi, Hoshigaoka, Chikusa-ku, Nagoya, Aichi, 464-8662, Japan

    Toyoshiro Nakashima

  4. Department of Marketing and Information Systems, Aichi Institute of Technology, 1247 Yachigusa, Yakusa-cho, Toyota, Aichi, 470-0392, Japan

    Naohiro Ishii

Authors
  1. Kazunori Iwata
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  2. Yoshiyuki Anan
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  3. Toyoshiro Nakashima
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  4. Naohiro Ishii
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Calgary, 2500 University Drive N.W., T2N 1N4, Calgary, AB, Canada

    Marina L. Gavrilova

  2. Department of Mathematics and Computer Science, University of Perugia, via Vanvitelli, 1, I-06123, Perugia, Italy

    Osvaldo Gervasi

  3. William Norris Professor, Head of the Computer Science and Engineering Department, University of Minnesota, USA

    Vipin Kumar

  4. OptimaNumerics Ltd., Cathedral House, 23-31 Waring Street, BT1 2DX, Belfast, UK

    C. J. Kenneth Tan

  5. Clayton School of IT, Monash University, 3800, Clayton, Australia

    David Taniar

  6. Department of Chemistry, University of Perugia, Via Elce di Sotto, 8, I-06123, Perugia, Italy

    Antonio Laganá

  7. School of Computing, Soongsil University, Seoul, Korea

    Youngsong Mun

  8. School of Information and Communication Engineering, Sungkyunkwan University, Korea

    Hyunseung Choo

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© 2006 Springer-Verlag Berlin Heidelberg

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Iwata, K., Anan, Y., Nakashima, T., Ishii, N. (2006). Effort Prediction Model Using Similarity for Embedded Software Development. In: Gavrilova, M.L., et al. Computational Science and Its Applications - ICCSA 2006. ICCSA 2006. Lecture Notes in Computer Science, vol 3981. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11751588_5

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  • DOI: https://doi.org/10.1007/11751588_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34072-0

  • Online ISBN: 978-3-540-34074-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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