Abstract
In the presented paper the new software effort estimation method is proposed. The Least Square Regression is used to predict a value of correction parameters, which have a significant impact. The accuracy estimationis of 85% better than the convectional use case points methods in tested dataset.
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References
Karner, G.: Metrics for objectory, Diploma, University of Linkoping, Sweden, No. LiTH-IDA-Ex-9344. 21 (December 1993)
Braz, M.R., Vergilio, S.R.: Software effort estimation based on use cases. In: 30th Annual International Computer Software and Applications Conference, COMPSAC 2006. IEEE (2006)
Wang, F., et al.: Extended Use Case Points Method for Software Cost Estimation, pp. 1–5 (2009)
Diev, S.: Use cases modeling and software estimation. ACM SIGSOFT Software Engineering Notes 31(6), 1 (2006)
Mohagheghi, P., Anda, B., Conradi, R.: Effort estimation of use cases for incremental large-scale software development, pp. 303–311 (2005)
Azevedo, S., et al.: On the refinement of use case models with variability support. Innovations in Systems and Software Engineering 8(1), 51–64 (2011)
Ochodek, M., Nawrocki, J., Kwarciak, K.: Simplifying effort estimation based on Use Case Points. Information and Software Technology 53(3), 200–213 (2011)
Ochodek, M., et al.: Improving the reliability of transaction identification in use cases. Information and Software Technology 53(8), 885–897 (2011)
Pindyck, R.S., Rubinfeld, D.L.: Econometric models and economic forecasts. Irwin/McGraw-Hill, Boston (1998)
Silhavy, R., Silhavy, P., Prokopova, Z.: Requirements Based Estimation Approach for System Engineering Projects. In: Innovations and Advances in Computing, Informatics, Systems Sciences, Networking and Engineering, pp. 467–472. Springer International Publishing (2015)
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Silhavy, R., Silhavy, P., Prokopova, Z. (2015). Applied Least Square Regression in Use Case Estimation Precision Tuning. In: Silhavy, R., Senkerik, R., Oplatkova, Z., Prokopova, Z., Silhavy, P. (eds) Software Engineering in Intelligent Systems. Advances in Intelligent Systems and Computing, vol 349. Springer, Cham. https://doi.org/10.1007/978-3-319-18473-9_2
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DOI: https://doi.org/10.1007/978-3-319-18473-9_2
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-18472-2
Online ISBN: 978-3-319-18473-9
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