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Customer goodwill and profitability are very important for a software organization\u2019s continued business. A large proportion of software products are delivered late or go over-budget causing significant inconvenience to the customers. This work proposes an accurate development effort estimation approach for software products. The Class Point (CP) approach with regression analysis method has been used for estimation of the development effort. This work uses a two step estimation approach. In the first step, an enhanced CP approach is used to evaluate the development effort of the system. In the second step, regression analysis models are utilized to refine the estimated effort accuracy. The results derived by applying the proposed two step approach confirmed the validity and the accuracy of this approach. It was observed that the SVR with RBF kernel is providing the best accuracy compared to other approaches.<\/jats:p>","DOI":"10.3233\/idt-210110","type":"journal-article","created":{"date-parts":[[2022,5,24]],"date-time":"2022-05-24T11:51:03Z","timestamp":1653393063000},"page":"357-367","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["Improving effort estimation of software products by augmenting class point approach with regression analysis"],"prefix":"10.1177","volume":"16","author":[{"given":"Pulak","family":"Sahoo","sequence":"first","affiliation":[{"name":"Silicon Institute of Technology","place":["India"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pamela","family":"Chaudhury","sequence":"additional","affiliation":[{"name":"Silicon Institute of Technology","place":["India"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J.R.","family":"Mohanty","sequence":"additional","affiliation":[{"name":"KIIT Deemed to be University","place":["India"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2022,5]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2005.5"},{"issue":"1","key":"e_1_3_1_3_2","first-page":"215","article-title":"Test effort estimation in early stages using use case and class models for web applications","volume":"22","author":"Sahoo P","year":"2018","unstructured":"SahooP MohantyJR. 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Test effort estimation and prediction of traditional and rapid release models using machine learning algorithms. Journal of Intelligent and Fuzzy Systems. 2018; 35(2): 1657-1669.","DOI":"10.3233\/JIFS-169703"},{"key":"e_1_3_1_11_2","doi-asserted-by":"crossref","unstructured":"SharmaP SinghJ. Systematic literature review on software effort estimation using machine learning approaches International Conference on Next Generation Computing and Information Systems (ICNGCIS). IEEE. 2017; 43-47.","DOI":"10.1109\/ICNGCIS.2017.33"},{"key":"e_1_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.3233\/AO-170177"},{"key":"e_1_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.3233\/JAD-191169"},{"key":"e_1_3_1_14_2","doi-asserted-by":"crossref","unstructured":"SatapathySM RathSK. 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