Abstract
This article is aimed to using the analytical programming and the Use Case Points method to estimate time effort in software engineering. The calculation of Use Case Points method is strictly algorithmically defined, and the calculation of this method is simple and fast. Despite a lot of research on this field, there are many attempts to calibrating the weights of Use Case Points method. In this paper is described idea that equation used in Use Case Points method could be less accurate in estimation than other equations. The aim of this research is to create new method, that will be able to create new equations for Use Case Points method. Analytical programming with self-organizing migration algorithm is used for this task. The experimental results shows that this method improving accuracy of effort estimation by 25–40 %.
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References
Keung, J W.: Theoretical maximum prediction accuracy for analogy-based software cost estimation. 2008 15th Asia-Pacific Software Engineering Conference, pp. 495–502 (2008)
Attarzadeh, I., and Ow, S.: ‘Software Development Cost and Time Forecasting Using a High Performance Artificial Neural Network Model’, in Chen, R. (Ed.): ‘Intelligent Computing and Information Science’ (Springer Berlin Heidelberg, 2011), pp. 18–26
Karner, G.: Metrics for Objectory. Diploma thesis, University of Linköping, Sweden. No. LiTH-IDA-Ex-9344:21. (1993)
Kominkova Oplatkova, Z., Senkerik, R., Zelinka, I., Pluhacek, M.: Analytic programming in the task of evolutionary synthesis of a controller for high order oscillations stabilization of discrete chaotic systems. Comput. Math. Appl. 66(2), 177–189 (2013)
Zelinka, I.: SOMA—Self Organizing Migrating Algorithm in New Optimization Techniques in Engineering, pp. 167–218. Springer, Berlin (2004)
Shepperd, M., Cartwright, M.: Predicting with sparse data. IEEE Trans. Softw. Eng. 27(11), 987–998 (2001)
Kocaguneli, Ekrem, Menzies, T., Keung, J.: On the value of ensemble effort estimation. IEEE Trans. Softw. Eng. 38(6), 1403–1416 (2011)
Menzies, T., Chen, Z., Hihn, J., Lum, K.: Selecting best practices for effort estimation. IEEE Trans. Softw. Eng. 32(11), 883–895 (2006)
Myrtveit, I., Stensrud, E., Shepperd, M.: Reliability and validity in comparative studies of software prediction models. IEEE Trans. Softw. Eng. 31(5), 380–391 (2005)
Shepperd, M., Schofield, C.: Estimating software project effort using analogies. IEEE Trans. Softw. Eng. 23(12), 736–743 (1997)
Stellman, A., Greene, J.: Applied Software Project Management, 1st edn. O’Reilly Media, Sebastopol (2005)
Boehm, B.W.: Software engineering economics. IEEE Trans. Softw. Eng. 10(1), 4–21 (1984)
Albrecht, A.J., Gaffney, J.E.: Software function, source lines of code, and development effort prediction: a software science validation. IEEE Trans. Softw.Eng. 9(6), 639–648 (1983)
Atkinson, K., Shepperd, M.: Using function points to find cost analogies. In: 5th European Software Cost Modelling Meeting, Ivrea, Italy, pp. 1–5, 1994
Kaushik, A., Soni, A.K., Soni, R.: An adaptive learning approach to software cost estimation. 2012 National Conference on Computing and Communication Systems, 1–6 Nov 2012
Park, H., Baek, S.: An empirical validation of a neural network model for software effort estimation. Expert Syst. Appl. 35(3), 929–937 (2008)
Xia, W., Capretz, L.F., Ho, D., Ahmed, F.: A new calibration for function point complexity weights. Inf. Softw. Technol. 50(7–8), 670–683 (2008)
Jiang, Z., Naudé, P., Jiang, B.: The effects of software size on development effort and software quality. J. Comput. Inf. Sci. 1(4), 492–496 (2007)
Ochodek, M., Nawrocki, J., Kwarciak, K.: Simplifying effort estimation based on use case points. Inf. Softw. Technol. 53(3), 200–213 (2011)
Acknowledgment
This study was supported by the internal grant of TBU in Zlin
No. IGA/FAI/2013/032 and No. IGA/FAI/2013/039
funded from the resources of specific university research.
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Urbanek, T., Prokopova, Z., Silhavy, R., Sehnalek, S. (2014). Using Analytical Programming and UCP Method for Effort Estimation. In: Silhavy, R., Senkerik, R., Oplatkova, Z., Silhavy, P., Prokopova, Z. (eds) Modern Trends and Techniques in Computer Science. Advances in Intelligent Systems and Computing, vol 285. Springer, Cham. https://doi.org/10.1007/978-3-319-06740-7_49
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DOI: https://doi.org/10.1007/978-3-319-06740-7_49
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