%0 Generic %1 kashyap2014refining %A Kashyap, Divya %A Shukla, Durgesh %A and A. K. Misra, %B Int. Conf. on Recent Trends in Information, Telecommunication and Computing , ITC %D 2014 %I ACEEE (A Computer division of IDES) %K Cost Estimation Function Fuzzy Logic MMRE Point %T Refining the Use Case Classification for Use Case Point Method for Software Effort Estimation %U http://searchdl.org/public/conference/2014/ITC/501.pdf %X Software cost estimation is a key open issue for the software industry, which suffers from cost overruns frequently. As the most popular technique for object-oriented software cost estimation is Use Case Points (UCP) method, however, it has two major drawbacks: the uncertainty of the cost factors and the abrupt classification. To address these two issues, refined the use case complexity classification using fuzzy logic th eory which mitigate the uncertainty of cost factors and improve the accuracy of classification. Software estimation is a crucial task in software engineering. Software estimation encompasses cost, effort, schedule, and size. The importance of software estimation becomes critical in the early stages of the software life cycle when the details of software have not been revealed yet. Several commercial and non-commercial tools exist to estimate software in the early stages. Most software effort estimation methods require software size as one of the important metric inputs and consequently, software size estimation in the early stages becomes essential. The proposed method presents a techniques using fuzzy logic theory to improve the accuracy of the use case points method by refining the use case classification

@conference{kashyap2014refining, abstract = { Software cost estimation is a key open issue for the software industry, which suffers from cost overruns frequently. As the most popular technique for object-oriented software cost estimation is Use Case Points (UCP) method, however, it has two major drawbacks: the uncertainty of the cost factors and the abrupt classification. To address these two issues, refined the use case complexity classification using fuzzy logic th eory which mitigate the uncertainty of cost factors and improve the accuracy of classification. Software estimation is a crucial task in software engineering. Software estimation encompasses cost, effort, schedule, and size. The importance of software estimation becomes critical in the early stages of the software life cycle when the details of software have not been revealed yet. Several commercial and non-commercial tools exist to estimate software in the early stages. Most software effort estimation methods require software size as one of the important metric inputs and consequently, software size estimation in the early stages becomes essential. The proposed method presents a techniques using fuzzy logic theory to improve the accuracy of the use case points method by refining the use case classification}, added-at = {2014-03-21T10:59:38.000+0100}, author = {Kashyap, Divya and Shukla, Durgesh and and A. K. Misra}, biburl = {https://www.bibsonomy.org/bibtex/2f99c27545dde623db6c245a3351f216c/idescitation}, booktitle = {Int. Conf. on Recent Trends in Information, Telecommunication and Computing , ITC}, interhash = {4ee8a03de43e44212ffeb3c4526257c1}, intrahash = {f99c27545dde623db6c245a3351f216c}, keywords = {Cost Estimation Function Fuzzy Logic MMRE Point}, organization = {Institute of Doctors Engineers and Scientists}, publisher = {ACEEE (A Computer division of IDES)}, timestamp = {2014-03-21T10:59:38.000+0100}, title = {Refining the Use Case Classification for Use Case Point Method for Software Effort Estimation}, url = {http://searchdl.org/public/conference/2014/ITC/501.pdf}, year = 2014 }