R. Folgieri, G. Barabino, G. Concas, Erika Corona, R. D. Lorenzi, M. Marchesi, Andrea Segni
{"title":"A revised web objects method to estimate web application development effort","authors":"R. Folgieri, G. Barabino, G. Concas, Erika Corona, R. D. Lorenzi, M. Marchesi, Andrea Segni","doi":"10.1145/1985374.1985388","DOIUrl":null,"url":null,"abstract":"We present a study of the effectiveness of estimating web application development effort using Function Points and Web Objects methods, and a method we propose - the Revised Web Objects (RWO). RWO is an upgrading of WO method, aimed to account for new web development styles and technologies. It also introduces an up-front classification of web applications according to their size, scope and technology, to further refine their effort estimation. These methods were applied to a data-set of 24 projects obtained by Datasiel spa, a mid-sized Italian company, focused on web application projects, showing that RWO performs statistically better than WO, and roughly in the same way as FP.","PeriodicalId":103819,"journal":{"name":"Workshop on Emerging Trends in Software Metrics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Workshop on Emerging Trends in Software Metrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1985374.1985388","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
We present a study of the effectiveness of estimating web application development effort using Function Points and Web Objects methods, and a method we propose - the Revised Web Objects (RWO). RWO is an upgrading of WO method, aimed to account for new web development styles and technologies. It also introduces an up-front classification of web applications according to their size, scope and technology, to further refine their effort estimation. These methods were applied to a data-set of 24 projects obtained by Datasiel spa, a mid-sized Italian company, focused on web application projects, showing that RWO performs statistically better than WO, and roughly in the same way as FP.