Enhancing software effort estimation in the analogy-based approach through the combination of regression methods
The success of software projects is closely linked to accurate effort estimation, driving continuous efforts by researchers to refine estimation methods. Among various techniques, the analogy-based approach has emerged as a widely-used method for software effort estimation. However, there is still a...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2024
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| Online Access: | http://psasir.upm.edu.my/id/eprint/114702/ http://psasir.upm.edu.my/id/eprint/114702/1/114702.pdf |
| _version_ | 1848866570608050176 |
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| author | Javdani Gandomani, Taghi Dashti, Maedeh Zulzalil, Hazura Md Sultan, Abu Bakar |
| author_facet | Javdani Gandomani, Taghi Dashti, Maedeh Zulzalil, Hazura Md Sultan, Abu Bakar |
| author_sort | Javdani Gandomani, Taghi |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | The success of software projects is closely linked to accurate effort estimation, driving continuous efforts by researchers to refine estimation methods. Among various techniques, the analogy-based approach has emerged as a widely-used method for software effort estimation. However, there is still a need to improve its accuracy and reliability. This study aims to enhance software effort estimation in analogy-based methods by introducing a hybrid approach that combines multiple regression methods with feature weighting. The proposed approach evaluates various regression models, integrating them with analogy-based estimation using a weighted combination of project features. The objective is to improve the precision of effort estimation by optimizing similarity functions and project attribute weights. Experimental results demonstrate that the hybrid model significantly outperforms traditional analogy-based methods, achieving superior accuracy across various software project datasets. The findings highlight the potential of this approach to offer a more dependable foundation for software effort estimation, contributing to the success of software projects. |
| first_indexed | 2025-11-15T14:22:42Z |
| format | Article |
| id | upm-114702 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T14:22:42Z |
| publishDate | 2024 |
| publisher | Institute of Electrical and Electronics Engineers Inc. |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1147022025-01-23T07:58:08Z http://psasir.upm.edu.my/id/eprint/114702/ Enhancing software effort estimation in the analogy-based approach through the combination of regression methods Javdani Gandomani, Taghi Dashti, Maedeh Zulzalil, Hazura Md Sultan, Abu Bakar The success of software projects is closely linked to accurate effort estimation, driving continuous efforts by researchers to refine estimation methods. Among various techniques, the analogy-based approach has emerged as a widely-used method for software effort estimation. However, there is still a need to improve its accuracy and reliability. This study aims to enhance software effort estimation in analogy-based methods by introducing a hybrid approach that combines multiple regression methods with feature weighting. The proposed approach evaluates various regression models, integrating them with analogy-based estimation using a weighted combination of project features. The objective is to improve the precision of effort estimation by optimizing similarity functions and project attribute weights. Experimental results demonstrate that the hybrid model significantly outperforms traditional analogy-based methods, achieving superior accuracy across various software project datasets. The findings highlight the potential of this approach to offer a more dependable foundation for software effort estimation, contributing to the success of software projects. Institute of Electrical and Electronics Engineers Inc. 2024 Article PeerReviewed text en cc_by_nc_nd_4 http://psasir.upm.edu.my/id/eprint/114702/1/114702.pdf Javdani Gandomani, Taghi and Dashti, Maedeh and Zulzalil, Hazura and Md Sultan, Abu Bakar (2024) Enhancing software effort estimation in the analogy-based approach through the combination of regression methods. IEEE Access, 12. pp. 152122-152137. ISSN 2169-3536; eISSN: 2169-3536 https://ieeexplore.ieee.org/document/10716622/ 10.1109/ACCESS.2024.3480829 |
| spellingShingle | Javdani Gandomani, Taghi Dashti, Maedeh Zulzalil, Hazura Md Sultan, Abu Bakar Enhancing software effort estimation in the analogy-based approach through the combination of regression methods |
| title | Enhancing software effort estimation in the analogy-based approach through the combination of regression methods |
| title_full | Enhancing software effort estimation in the analogy-based approach through the combination of regression methods |
| title_fullStr | Enhancing software effort estimation in the analogy-based approach through the combination of regression methods |
| title_full_unstemmed | Enhancing software effort estimation in the analogy-based approach through the combination of regression methods |
| title_short | Enhancing software effort estimation in the analogy-based approach through the combination of regression methods |
| title_sort | enhancing software effort estimation in the analogy-based approach through the combination of regression methods |
| url | http://psasir.upm.edu.my/id/eprint/114702/ http://psasir.upm.edu.my/id/eprint/114702/ http://psasir.upm.edu.my/id/eprint/114702/ http://psasir.upm.edu.my/id/eprint/114702/1/114702.pdf |