Effort Estimation in Agile Software Projects Using Kohonen Maps
Abstract
Software development through agile methods is directly linked to the execution of the various activities planned throughout the iterations. Good deadline estimates make the project stable, the development team safer and the customer more satisfied. However, estimating the deadline for developing a task is somewhat sensitive to errors, since all techniques have some practical use limitations. This work aims to carry out a study on the use of self-organizing Kohonen maps to assist in these estimates, providing an initial estimate of the duration of a task, using as a basis measures obtained from similar and previously performed tasks. To evaluate the approach, data obtained from a local software development company were used. From the evaluation it was possible to draw conclusions regarding the quality of the records made by the developers of this company, and to evaluate the accuracy of the estimate made by the approach.
Keywords:
Estimate, Agile Projects, Kohonen Maps
References
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Attarzadeh, I. and Ow, S. H. (2011). Improving estimation accuracy of the cocomo ii using an adaptive fuzzy logic model. In 2011 IEEE International Conference on Fuzzy Systems (FUZZ), pages 2458–2464.
Beck, K., Beedle, M., van Bennekum, A., Cockburn, A., Cunningham, W., Fowler, M., Grenning, J., Highsmith, J., Hunt, A., Jeffries, R., Kern, J., Marick, B., Martin, R. C., Mellor, S., Schwaber, K., Sutherland, J., and Thomas, D. (2001). Manifesto for agile software development.
Boehm, B. W. (1981). Software Engineering Economics. Prentice Hall PTR, Upper Saddle River, NJ, USA, 1st edition.
Conte, S. D., Dunsmore, H. E., and Shen, V. Y. (1986). Software Engineering Metrics and Models. Benjamin-Cummings Publishing Co., Inc., Redwood City, CA, USA.
Haykin, S. (1998). Neural Networks: A Comprehensive Foundation. Prentice Hall PTR,Upper Saddle River, NJ, USA, 2nd edition.
Jones, C. (1986). Programming Productivity. McGraw-Hill Series in Software Enginee-ring & Technology. McGraw-Hill.
Jones, C. (1991). Applied Software Measurement: Assuring Productivity and Quality. McGraw-Hill, Inc., New York, NY, USA.
Kemerer, C. F. (1987). An empirical validation of software cost estimation models. Communications of the ACM, 30(5):416–429.
Kohonen, T. (1982). Self-organized formation of topologically correct feature maps. Biological Cybernetics, 43(1):59–69.
Kumar, J., Rao, T., Babu, Y., Chaitanya, S., and Subrahmanyam, K. (2011). A novel method for software effort estimation using inverse regression as firing interval infuzzy logic. In 2011 3rd International Conference on Electronics Computer Technology (ICECT), volume 4, pages 177–182.
Manapian, A. and Prompoon, N. (2014). Software time estimation model for requirements change based on software prototype profiles using an analogy estimation method. In Computer Science and Engineering Conference (ICSEC), 2014 International, pages 366–371.
McCabe, T. J. (1976). A complexity measure. IEEE Transactions on Software Engineering, 2(4):308–320.
Pressman, R. (2010). Software Engineering: A Practitioner’s Approach. McGraw-Hill, Inc., New York, NY, USA, 7 edition.
Putnam, L. (1978). A general empirical solution to the macro software sizing and estimating problem. Software Engineering, IEEE Transactions on, SE-4(4):345–361.
Rastogi, H., Dhankhar, S., and Kakkar, M. (2014). A survey on software effort estimation techniques. In 2014 5th International Conference Confluence The Next Generation Information Technology Summit (Confluence), pages 826–830.
Satapathy, S., Kumar, M., and Rath, S. (2013). Class point approach for software effort estimation using soft computing techniques. In 2013 International Conference onAdvances in Computing, Communications and Informatics (ICACCI), pages 178–183.
Saxena, U. and Singh, S. (2012). Software effort estimation using neuro-fuzzy approach. In 2012 CSI Sixth International Conference on Software Engineering (CONSEG), pages 1–6.
Schwaber, K. and Beedle, M. (2001). Agile Software Development with Scrum. Prentice Hall PTR, Upper Saddle River, NJ, USA, 1st edition.
Usman, M., Mendes, E., Weidt, F., and Britto, R. (2014). Effort estimation in agile software development: A systematic literature review. In Proceedings of the 10th International Conference on Predictive Models in Software Engineering, PROMISE ’14, pages 82–91, New York, NY, USA. ACM.
Published
2015-08-17
How to Cite
LIRA, Werney Ayala Luz; ALVES, Francisco Vanderson de Moura; DOS SANTOS NETO, Pedro de Alcântara; RABELO, Ricardo de Andrade Lira; BRITTO, Ricardo de Sousa.
Effort Estimation in Agile Software Projects Using Kohonen Maps. In: BRAZILIAN SOFTWARE QUALITY SYMPOSIUM (SBQS), 14. , 2015, Manaus.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2015
.
p. 19-33.
DOI: https://doi.org/10.5753/sbqs.2015.15211.
