Effort Prediction Model Using Similarity for Embedded Software Development
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.
KeywordsMultiple Regression Analysis Recommendation System User Evaluation Project Data Collaborative Filter
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- 1.Tsunoda, M., Ohsugi, N., Monden, A., Matsumoto, K., Sato, S.: Software development effort prediction based on collaborative filtering (in japanese). Journal of Information Processing Society of Japan (IPSJ) 46(5), 1155–1164 (2005)Google Scholar
- 2.Breese, J., Heckerman, D., Kadie, C.: Empirical analysis of predictive algorithms for collaborative filtering. In: Proc. 14th Conf. on Uncertainty in Artificial Intelligence, Wisconsin, pp. 337–386 (2000)Google Scholar
- 3.Salton, G., MacGill, M.: Introduction to modern information retrieval, 448 (1983)Google Scholar
- 4.Manly, B.F.J.: Multivariate Statistical Methods (Translated by Masayasu Murakami and Masaaki Taguri: Tahenryo kaiseki no kiso, Baifukukan (1992). Chapman and Hall Ltd, Boca Raton (1986)Google Scholar
- 5.Hasegawa, K.: Really Understanding Multivariate Analysis (in Japanese). Kyoritsu Shuppan Co., Ltd. (1998)Google Scholar
- 7.Nakamoto, Y., Takada, H., Tamaru, K.: Current state and trend in embedded systems (in japanese). Journal of Information Processing Society of Japan (IPSJ) 38(10), 871–878 (1997)Google Scholar
- 8.Iwata, K., Anan, Y., Nakashima, T.: Studies on project management models for embedded software development projects (in japanese). Journal of Information Processing Society of Japan (IPSJ) 46(5), 1137–1144 (2005)Google Scholar