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dc.title | An evaluation of technical and environmental complexity factors for improving use case points estimation | en |
dc.contributor.author | Ho, Le Thi Kim Nhung | |
dc.contributor.author | Huynh Thai, Hoc | |
dc.contributor.author | Vo Van, Hai | |
dc.relation.ispartof | Advances in Intelligent Systems and Computing | |
dc.identifier.issn | 2194-5357 Scopus Sources, Sherpa/RoMEO, JCR | |
dc.identifier.isbn | 978-3-03-063321-9 | |
dc.date.issued | 2020 | |
utb.relation.volume | 1294 | |
dc.citation.spage | 757 | |
dc.citation.epage | 768 | |
dc.event.title | 4th Computational Methods in Systems and Software, CoMeSySo 2020 | |
dc.event.location | online | |
dc.event.sdate | 2020-10-14 | |
dc.event.edate | 2020-10-17 | |
dc.type | conferenceObject | |
dc.language.iso | en | |
dc.publisher | Springer Science and Business Media Deutschland GmbH | |
dc.identifier.doi | 10.1007/978-3-030-63322-6_64 | |
dc.relation.uri | https://link.springer.com/chapter/10.1007/978-3-030-63322-6_64 | |
dc.subject | multiple linear regression | en |
dc.subject | software effort estimation | en |
dc.subject | Use Case Points | en |
dc.description.abstract | This paper presents a proposed method for improving the prediction ability of the Use Case Points method. Our main goal is to use the Least Absolute Shrinkage and Selection Operator Regression methods to find out which of the technical and environmental complexity factors significantly affect the accuracy of the Use Case Points method. Two regression models were used to calculate the selected significant variables. The results of several evaluation measures show that the proposed estimation method ability is better than the original Use Case Points method. The Sum of Squared Error of the proposed method is better than the results obtained by the original one. The study also enables project managers to understand how to assess the technical and environmental complexity factors better - since they do have an important impact on effort estimation. © 2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG. | en |
utb.faculty | Faculty of Applied Informatics | |
dc.identifier.uri | http://hdl.handle.net/10563/1010144 | |
utb.identifier.obdid | 43882279 | |
utb.identifier.scopus | 2-s2.0-85098212049 | |
utb.source | d-scopus | |
dc.date.accessioned | 2021-01-08T14:02:34Z | |
dc.date.available | 2021-01-08T14:02:34Z | |
utb.contributor.internalauthor | Ho, Le Thi Kim Nhung | |
utb.contributor.internalauthor | Huynh Thai, Hoc | |
utb.contributor.internalauthor | Vo Van, Hai | |
utb.fulltext.affiliation | Ho Le Thi Kim Nhung, Huynh Thai Hoc, Vo Van Hai Faculty of Applied Informatics, Tomas Bata University in Zlin, Nad Stranemi 4511, 76001 Zlin, Czech Republic {lho,huynh_thai,vo_van}@utb.cz | |
utb.fulltext.dates | - | |
utb.fulltext.sponsorship | This work was supported by the Faculty of Applied Informatics, Tomas Bata University in Zlín, under Project SV13202001020-PU30, Project IGA/CebiaTech/2020/001, and Project RVO/FAI/2020/002. | |
utb.scopus.affiliation | Faculty of Applied Informatics, Tomas Bata University in Zlin, Nad Stranemi 4511, Zlin, 76001, Czech Republic | |
utb.fulltext.projects | SV13202001020-PU30 | |
utb.fulltext.projects | IGA/CebiaTech/2020/001 | |
utb.fulltext.projects | RVO/FAI/2020/002 | |
utb.fulltext.faculty | Faculty of Applied Informatics | |
utb.fulltext.faculty | Faculty of Applied Informatics | |
utb.fulltext.faculty | Faculty of Applied Informatics |