A New Approach for Software Cost Estimation with a Hybrid Tabu Search and Invasive Weed Optimization Algorithms
Due to the ever-increasing progress of software projects and their widespread impact on all industries, models must be designed and implemented to analyze and estimate costs and time. Until now, most of the software cost estimation (SCE) has been based on the analyst’s experiences and similar projec...
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| Format: | Article |
| Language: | English |
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University of Human Development
2024-02-01
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| Series: | UHD Journal of Science and Technology |
| Subjects: | |
| Online Access: | https://journals.uhd.edu.iq/index.php/uhdjst/article/view/1256 |
| _version_ | 1797303250864570368 |
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| author | Hoshmen Murad Mohamedyusf Hawar Othman Sharif Mazen Ismaeel Ghareb |
| author_facet | Hoshmen Murad Mohamedyusf Hawar Othman Sharif Mazen Ismaeel Ghareb |
| author_sort | Hoshmen Murad Mohamedyusf |
| collection | DOAJ |
| description | Due to the ever-increasing progress of software projects and their widespread impact on all industries, models must be designed and implemented to analyze and estimate costs and time. Until now, most of the software cost estimation (SCE) has been based on the analyst’s experiences and similar projects and these models are often inaccurate and inappropriate. The project will not be finished in the specified time and will include additional costs. Algorithmic models such as COCOMO are not very accurate in SCE. They are linear and the appropriate value for effort factors is not considered. On the other hand, artificial intelligence models have made significant progress in the cost estimation modeling of software projects in the past three decades. These models determine the correct value for effort factors through iteration and training, providing a more accurate estimate compared to algorithmic models. This paper employs a hybrid model incorporating the Tabu Search (TS) algorithm and the Invasive Weed Optimization (IWO) algorithm for SCE. IWO algorithm solutions are improved using the TS algorithm. The NASA60, NASA63, NASA93, KEMERER, and MAXWELL datasets are used for the evaluation. The proposed model has been able to reduce the MMRE rate compared to the IWO algorithm and the TS algorithm. The proposed model on the NASA60, NASA63, NASA93, KEMERER, and MAXWELL datasets obtained values of MMRE of 15.43, 17.05, 28.75, 58.43, and 22.46, respectively. |
| first_indexed | 2024-03-07T23:50:11Z |
| format | Article |
| id | doaj.art-7d52b4f212a94f4bbd9d70318fa5e80f |
| institution | Directory Open Access Journal |
| issn | 2521-4209 2521-4217 |
| language | English |
| last_indexed | 2024-03-07T23:50:11Z |
| publishDate | 2024-02-01 |
| publisher | University of Human Development |
| record_format | Article |
| series | UHD Journal of Science and Technology |
| spelling | doaj.art-7d52b4f212a94f4bbd9d70318fa5e80f2024-02-19T08:55:25ZengUniversity of Human DevelopmentUHD Journal of Science and Technology2521-42092521-42172024-02-0181425410.21928/uhdjst.v8n1y2024.pp42-541387A New Approach for Software Cost Estimation with a Hybrid Tabu Search and Invasive Weed Optimization AlgorithmsHoshmen Murad Mohamedyusf0Hawar Othman Sharif1Mazen Ismaeel Ghareb2https://orcid.org/0000-0002-3937-2835Department of Plastic Arts, Halabja Fine Arts Institute, Halabja, IraqDepartment of Computer Science, College of Science, University of Sulaimani, IraqDepartment of Computer Science, College of Science and Technology, University of Human Development, Kurdistan Region, IraqDue to the ever-increasing progress of software projects and their widespread impact on all industries, models must be designed and implemented to analyze and estimate costs and time. Until now, most of the software cost estimation (SCE) has been based on the analyst’s experiences and similar projects and these models are often inaccurate and inappropriate. The project will not be finished in the specified time and will include additional costs. Algorithmic models such as COCOMO are not very accurate in SCE. They are linear and the appropriate value for effort factors is not considered. On the other hand, artificial intelligence models have made significant progress in the cost estimation modeling of software projects in the past three decades. These models determine the correct value for effort factors through iteration and training, providing a more accurate estimate compared to algorithmic models. This paper employs a hybrid model incorporating the Tabu Search (TS) algorithm and the Invasive Weed Optimization (IWO) algorithm for SCE. IWO algorithm solutions are improved using the TS algorithm. The NASA60, NASA63, NASA93, KEMERER, and MAXWELL datasets are used for the evaluation. The proposed model has been able to reduce the MMRE rate compared to the IWO algorithm and the TS algorithm. The proposed model on the NASA60, NASA63, NASA93, KEMERER, and MAXWELL datasets obtained values of MMRE of 15.43, 17.05, 28.75, 58.43, and 22.46, respectively.https://journals.uhd.edu.iq/index.php/uhdjst/article/view/1256cocomo modeltabu search algorithminvasive weed optimization algorithmsoftware cost |
| spellingShingle | Hoshmen Murad Mohamedyusf Hawar Othman Sharif Mazen Ismaeel Ghareb A New Approach for Software Cost Estimation with a Hybrid Tabu Search and Invasive Weed Optimization Algorithms UHD Journal of Science and Technology cocomo model tabu search algorithm invasive weed optimization algorithm software cost |
| title | A New Approach for Software Cost Estimation with a Hybrid Tabu Search and Invasive Weed Optimization Algorithms |
| title_full | A New Approach for Software Cost Estimation with a Hybrid Tabu Search and Invasive Weed Optimization Algorithms |
| title_fullStr | A New Approach for Software Cost Estimation with a Hybrid Tabu Search and Invasive Weed Optimization Algorithms |
| title_full_unstemmed | A New Approach for Software Cost Estimation with a Hybrid Tabu Search and Invasive Weed Optimization Algorithms |
| title_short | A New Approach for Software Cost Estimation with a Hybrid Tabu Search and Invasive Weed Optimization Algorithms |
| title_sort | new approach for software cost estimation with a hybrid tabu search and invasive weed optimization algorithms |
| topic | cocomo model tabu search algorithm invasive weed optimization algorithm software cost |
| url | https://journals.uhd.edu.iq/index.php/uhdjst/article/view/1256 |
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