{"title":"Comparative Analysis of the Software Effort Estimation Models","authors":"Jaswinder Kaur, Satwinder Singh, Karanjeet Singh Kahlon","volume":22,"journal":"International Journal of Computer and Systems Engineering","pagesStart":3402,"pagesEnd":3405,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/15566","abstract":"Accurate software cost estimates are critical to both\r\ndevelopers and customers. They can be used for generating request\r\nfor proposals, contract negotiations, scheduling, monitoring and\r\ncontrol. The exact relationship between the attributes of the effort\r\nestimation is difficult to establish. A neural network is good at\r\ndiscovering relationships and pattern in the data. So, in this paper a\r\ncomparative analysis among existing Halstead Model, Walston-Felix\r\nModel, Bailey-Basili Model, Doty Model and Neural Network\r\nBased Model is performed. Neural Network has outperformed the\r\nother considered models. Hence, we proposed Neural Network\r\nsystem as a soft computing approach to model the effort estimation\r\nof the software systems.","references":"[1] M. Boraso, C. Montangero, and H. Sedehi, \"Software cost estimation:\r\nAn experimental study of model performances,\" tech. report, 1996.\r\n[2] O. Benediktsson, D. Dalcher, K. Reed, and M. Woodman, \"COCOMO\r\nbased effort estimation for iterative and incremental software\r\ndevelopment,\" Software Quality Journal, vol. 11, pp. 265-281, 2003.\r\n[3] T. Menzies, D. Port, Z. Chen, J. Hihn, and S. Stukes, \"Validation\r\nmethods for calibrating software effort models,\" in ICSE -05:\r\nProceedings of the 27th international conference on Software\r\nengineering, (New York, NY, USA), pp. 587-595, ACM Press, 2005.\r\n[4] S. Chulani, B. Boehm, and B. Steece, \"Calibrating software cost models\r\nusing bayesian analysis,\" IEEE Trans. Software Engr., July-August\r\n1999, pp. 573-583, 1999.\r\n[5] B. Clark, S. Devnani-Chulani, and B. Boehm, \"Calibrating the\r\nCOCOMO II post-architecture model,\" in ICSE -98: Proceedings of the\r\n20th international conference on Software engineering, (Washington,\r\nDC, USA), pp. 477-480, IEEE Computer Society, 1998.\r\n[6] S. Chulani and B. Boehm, \"Modeling software defect introduction and\r\nremoval: Coqualmo (constructive quality model),\" tech. report.\r\n[7] S. Devnani-Chulani, \"Modeling software defect introduction,\" tech.\r\nreport.\r\n[8] M. Shepper and C. Schofield, \"Estimating software project effort using\r\nanalogies,\" IEEE Tran. Software Engineering, vol. 23, pp. 736-743,\r\n1997.\r\n[9] G. Witting and G. Finnie, \"Estimating software development effort with\r\nconnectionist models,\" in Proceedings of the Information and Software\r\nTechnology Conference, pp. 469-476, 1997.\r\n[10] J. W. Bailey and V. R. Basili, \"A meta model for software development\r\nresource expenditure,\" in Proceedings of the International Conference on\r\nSoftware Engineering, pp. 107-115, 1981.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 22, 2008"}