Study Of Approaches To Test Effort Estimation , Metrics Used For Software Project Size Estimation And Shortcomings Of Function Point (FP) Metric
Keywords:
Software testing effort estimation, LOCAbstract
Software testing effort estimation has always been an on-going challenge to software engineers, as testing is one of the critical activities of SDLC. Accurate effort estimation is the state of art of software engineering, as it is the preliminary phase between the client and the business enterprise. The credibility of the client to the business enterprise increases with the accurate estimation. The earlier test estimation is done, the more benefits will be achieved in the testing life cycle. This paper proposes an approach for estimating the size and efforts required in the testing projects using test case point. The proposed model outlines all major factors that affect testing projects. Covering all major factors helps to do a fair estimation using the proposed approach.
References
Ali Idri, Azeddine Zahi, "Software cost estimation by classical and Fuzzy Analogy for Web Hypermedia Applications: A replicated study", Computational Intelligence and Data Mining (CIDM) 2013 IEEE Symposium on, pp. 207-213, 2013.
Emilia Mendes, Nile Mosley, "Bayesian Network Models for Web Effort Prediction: A Comparative Study", Software Engineering IEEE Transactions on, vol. 34, pp. 723-737, 2008, ISSN 0098-5589.
E. Mendes, N. Mosley, S. Counsell, "A replicated assessment of the use of adaptation rules to improve Web cost estimation", Empirical Software Engineering 2003. ISESE 2003. Proceedings. 2003 International Symposium on, pp. 100-109, 2003.
A comparison of software effort estimation techniques: Using function points with neural networks, case-based reasoning and regression models, Journal of Systems and Software, Volume 39, Issue 3, 1997, Pages 281-289, ISSN 0164-1212, https://doi.org/10.1016/S0164-1212(97)00055-1.
N. E. Fenton, P. Krause, and M. Neil, “Software measurement: Uncertainty and causal modeling,” IEEE Software, vol. 19, no. 4, pp. 116–122, 2002.
D. Settas, S. Bibi, P. Sfetsos, I. Stamelos, and V. Gerogiannis, “Using Bayesian belief networks to model software project management antipatterns,” in SERA ’06: Proceedings of the Fourth International Conference on Software Engineering Research, Management and Applications.
