How to cite this paper
Bansal, A., Kumar, B & Garg, R. (2017). Multi-criteria decision making approach for the selection of software effort estimation model.Management Science Letters , 7(6), 285-296.
Refrences
Abbas, S. A., Liao, X., Rehman, A. U., Azam, A., & Abdullah, M. I. (2012). Cost estimation: A sur-vey of well-known historic cost estimation techniques. Journal of Emerging Trends in Computing and Information Sciences, 3(4), 612-636.
Amit, G., Ramesh, K., & Tewari, P. C. (2014). Ranking of inventory policies using distance based ap-proach method. World Academy of Science, Engineering and Technology, International Journal of Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering, 8(2), 395-400.
Basha, S., & Ponnurangam, D. (2010). Analysis of empirical software effort estimation models. arXiv preprint arXiv:1004.1239.
Garcia-Diaz, N., Lopez-Martin, C., & Chavoya, A. (2013). A comparative study of two fuzzy logic models for software development effort estimation. Procedia Technology, 7, 305-314.
Garg, R. K., Sharma, K., Nagpal, C. K., Garg, R., Garg, R., & Kumar, R. (2013). Ranking of soft-ware engineering metrics by fuzzy‐based matrix methodology. Software Testing, Verification and Reliability, 23(2), 149-168.
Garg, R., Sharma, R., & Sharma, K. (2016). Ranking and selection of commercial off-the-shelf using fuzzy distance based approach. Decision Science Letters, 5(2), 201-210.
Jain, D., Garg, R., Bansal, A., & Saini, K. K. (2016). Selection and ranking of E-learning websites us-ing weighted distance-based approximation. Journal of Computers in Education, 3(2), 193-207.
Jarial, S. K., & Garg, R. K. (2012). Ranking of vendors based on criteria by MCDM-matrix method-a case study for commercial vehicles in an industry. International Journal of Latest Research in Sci-ence & Technology, 1(4), 337-341.
Kaur, J., Singh, S., Kahlon, K. S., & Bassi, P. (2010). Neural network-a novel technique for software effort estimation. International Journal of Computer Theory and Engineering, 2(1), 17.
Leung, H., & Fan, Z. (2002). Software cost estimation. Handbook of Software Engineering, Hong Kong Polytechnic University, 1-14.
Malathi, S., & Sridhar, S. (2012). Analysis of size metrics and effort performance criterion in software cost estimation. Indian Journal of Computer Science and Engineering, 3(1), 24-31.
Menzies, T., Chen, Z., Hihn, J., & Lum, K. (2006). Selecting best practices for effort estimation. IEEE Transactions on Software Engineering, 32(11), 883-895.
Mittas, N., & Angelis, L. (2013). Ranking and clustering software cost estimation models through a multiple comparisons algorithm. IEEE Transactions on Software Engineering, 39(4), 537-551.
Moløkken-Østvold, K., Jørgensen, M., Tanilkan, S. S., Gallis, H., Lien, A. C., & Hove, S. W. (2004, September). A survey on software estimation in the Norwegian industry. In Software Metrics, 2004. Proceedings. 10th International Symposium on (pp. 208-219). IEEE.
Nayebi, F., Abran, A., & Desharnais, J. M. (2015). Automated selection of a software effort estima-tion model based on accuracy and uncertainty. Artificial Intelligence Research, 4(2), p45.
Pandey, P. (2013, April). Analysis of the techniques for software cost estimation. In Advanced Com-puting and Communication Technologies (ACCT), 3rd International Conference on (pp. 16-19).
Preeth, R., ShivaKumar, N., & Balaji, N. (2014). Software effort estimation using attribute refinement based adaptive Neuro Fuzzy Model. International Journal of Innovative Research in Science Engi-neering and Technology, 3(3).
Ramesh, K., & Karunanidhi, P. (2013). Literature survey on algorithmic and non-algorithmic models for software development effort estimation. International Journal of Engineering And Computer Science ISSN, 2319-7242.
Rao, R. (2012). Weighted Euclidean distance based approach as a multiple attribute decision making method for plant or facility layout design selection. International Journal of Industrial Engineering Computations, 3(3), 365-382.
Sehra, S. K., Brar, D., Singh, Y., & Kaur, D. (2013). Multi criteria decision making approach for se-lecting effort estimation model. arXiv preprint arXiv:1310.5220.
Wen, J., Li, S., Lin, Z., Hu, Y., & Huang, C. (2012). Systematic literature review of machine learning based software development effort estimation models. Information and Software Technolo-gy, 54(1), 41-59.
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338–353.
Amit, G., Ramesh, K., & Tewari, P. C. (2014). Ranking of inventory policies using distance based ap-proach method. World Academy of Science, Engineering and Technology, International Journal of Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering, 8(2), 395-400.
Basha, S., & Ponnurangam, D. (2010). Analysis of empirical software effort estimation models. arXiv preprint arXiv:1004.1239.
Garcia-Diaz, N., Lopez-Martin, C., & Chavoya, A. (2013). A comparative study of two fuzzy logic models for software development effort estimation. Procedia Technology, 7, 305-314.
Garg, R. K., Sharma, K., Nagpal, C. K., Garg, R., Garg, R., & Kumar, R. (2013). Ranking of soft-ware engineering metrics by fuzzy‐based matrix methodology. Software Testing, Verification and Reliability, 23(2), 149-168.
Garg, R., Sharma, R., & Sharma, K. (2016). Ranking and selection of commercial off-the-shelf using fuzzy distance based approach. Decision Science Letters, 5(2), 201-210.
Jain, D., Garg, R., Bansal, A., & Saini, K. K. (2016). Selection and ranking of E-learning websites us-ing weighted distance-based approximation. Journal of Computers in Education, 3(2), 193-207.
Jarial, S. K., & Garg, R. K. (2012). Ranking of vendors based on criteria by MCDM-matrix method-a case study for commercial vehicles in an industry. International Journal of Latest Research in Sci-ence & Technology, 1(4), 337-341.
Kaur, J., Singh, S., Kahlon, K. S., & Bassi, P. (2010). Neural network-a novel technique for software effort estimation. International Journal of Computer Theory and Engineering, 2(1), 17.
Leung, H., & Fan, Z. (2002). Software cost estimation. Handbook of Software Engineering, Hong Kong Polytechnic University, 1-14.
Malathi, S., & Sridhar, S. (2012). Analysis of size metrics and effort performance criterion in software cost estimation. Indian Journal of Computer Science and Engineering, 3(1), 24-31.
Menzies, T., Chen, Z., Hihn, J., & Lum, K. (2006). Selecting best practices for effort estimation. IEEE Transactions on Software Engineering, 32(11), 883-895.
Mittas, N., & Angelis, L. (2013). Ranking and clustering software cost estimation models through a multiple comparisons algorithm. IEEE Transactions on Software Engineering, 39(4), 537-551.
Moløkken-Østvold, K., Jørgensen, M., Tanilkan, S. S., Gallis, H., Lien, A. C., & Hove, S. W. (2004, September). A survey on software estimation in the Norwegian industry. In Software Metrics, 2004. Proceedings. 10th International Symposium on (pp. 208-219). IEEE.
Nayebi, F., Abran, A., & Desharnais, J. M. (2015). Automated selection of a software effort estima-tion model based on accuracy and uncertainty. Artificial Intelligence Research, 4(2), p45.
Pandey, P. (2013, April). Analysis of the techniques for software cost estimation. In Advanced Com-puting and Communication Technologies (ACCT), 3rd International Conference on (pp. 16-19).
Preeth, R., ShivaKumar, N., & Balaji, N. (2014). Software effort estimation using attribute refinement based adaptive Neuro Fuzzy Model. International Journal of Innovative Research in Science Engi-neering and Technology, 3(3).
Ramesh, K., & Karunanidhi, P. (2013). Literature survey on algorithmic and non-algorithmic models for software development effort estimation. International Journal of Engineering And Computer Science ISSN, 2319-7242.
Rao, R. (2012). Weighted Euclidean distance based approach as a multiple attribute decision making method for plant or facility layout design selection. International Journal of Industrial Engineering Computations, 3(3), 365-382.
Sehra, S. K., Brar, D., Singh, Y., & Kaur, D. (2013). Multi criteria decision making approach for se-lecting effort estimation model. arXiv preprint arXiv:1310.5220.
Wen, J., Li, S., Lin, Z., Hu, Y., & Huang, C. (2012). Systematic literature review of machine learning based software development effort estimation models. Information and Software Technolo-gy, 54(1), 41-59.
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338–353.