A New Approach for Software Cost Estimation with a Hybrid Tabu Search and Invasive Weed Optimization Algorithms

Authors

  • Hoshmen Murad Mohamedyusf Department of Plastic Arts, Halabja Fine Arts Institute, Halabja, Iraq
  • Hawar Othman Sharif Department of Computer Science, College of Science, University of Sulaimani, Iraq
  • Mazen Ismaeel Ghareb Department of Computer Science, College of Science and Technology, University of Human Development, Kurdistan Region, Iraq https://orcid.org/0000-0002-3937-2835

DOI:

https://doi.org/10.21928/uhdjst.v8n1y2024.pp42-54

Keywords:

COCOMO Model, Tabu Search Algorithm, Invasive Weed Optimization Algorithm, Software Cost

Abstract

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.

Author Biographies

Hawar Othman Sharif, Department of Computer Science, College of Science, University of Sulaimani, Iraq

Welcome to my Academic Profile page. My name is Hawar Othman Sharif. I am Assistant Lecturer with a M.Sc. Degree in Computer Science(C.S.), teaching in the College of Science  at the University of Sulaimani in Kurdistan Region.

Recently I am Assistant Lecturer in the Department.

 

e-mail: hawar.Sharif@univsul.edu.iq

Mobile: (+964) - 07701916310

Mazen Ismaeel Ghareb, Department of Computer Science, College of Science and Technology, University of Human Development, Kurdistan Region, Iraq

I am Mazen I. Ghareb, a Lecturer and Head of the Computer Science Department at the University of Human Development in Sulaymaniyah, Iraq. I earned my undergraduate degree from Sulaymaniyah University's Computer Department in 2006.

I began my career at Fanoos Telecommunication Company, where I served as an IT Developer for two years. During this period, I successfully designed and implemented an Electronic Point of Sale (EPOS) system for the sales department. Additionally, I contributed to the development of a Mini Billing system for the Intelligence Network department.

While working at Fanoos Telecommunication Company, I concurrently held a position as a Lab Assistant Lecturer at Sulaymaniyah University's Computer and Statistics Department. In this role, I worked part-time in the Network lab, providing valuable insights and assistance to students.

In 2007, I obtained an Oracle Administrator certificate from Iraqcom Company, further enhancing my skills in database administration. In 2008, I seized an opportunity to join Lafarge Cement Company in Tasluja-Bazyan. Here, I took on responsibilities for the development and upgrades of the Oracle application for the Sales system, successfully transitioning it to a new and improved version.

Since 2009, I have been serving as an Assistant Lecturer in the Computer Department at the University of Human Development. In 2011, I was granted admission to the Human Capacity Development Programme (HCDP), allowing me to pursue a Master's degree in Advanced Computer Science in the United Kingdom. I successfully completed my Master's degree with Distinction from the University of Huddersfield-UK.

My areas of interest encompass a wide range of topics within the field of computer science, reflecting my dedication to continuous learning and professional development.

He successfully completed his Ph.D. in Computer Science, specializing in the measurement metrics of Aspect-Oriented Programming, in the year 2022 from University of Huddersfield United Kingdom.

References

S. K. Gouda and A. K. Mehta. “Software cost estimation model based on fuzzy C-means and improved self-adaptive differential evolution algorithm”. International Journal of Information Technology, vol. 14, no. 4, p. 2171-2182, 2022.

S. K. Gouda and A. K. Mehta. “A self-adaptive differential evolution using a new adaption based operator for software cost estimation”. Journal of the Institution of Engineers (India): Series B, vol. 104, no. 1, pp. 23-42, 2023.

W. Rhmann, B. Pandey and G. A. Ansari. “Software effort estimation using ensemble of hybrid search-based algorithms based on metaheuristic algorithms”. Innovations in Systems and Software Engineering, vol. 18, pp. 1-11, 2021.

Z. A. Dizaji and F. S. Gharehchopogh. “A hybrid of ant colony optimization and chaos optimization algorithms approach for software cost estimation”. Indian Journal of Science and Technology, vol. 8, no. 2, p. 128, 2015.

R. Mehrabian and C. Lucas. “A novel numerical optimization algorithm inspired from weed colonization”. Ecological Informatics, vol. 1, no. 4, pp. 355-366, 2006.

B. Boehm, C. Abts and S. Chulani. “Software development cost estimation approaches-a survey”. Annals of Software Engineering, vol. 10, no. 1-4, pp. 177-205, 2000.

O. Adalier, A. Ugur, S. Korukoglu, K. Ertas, H. Yin, P. Tino, E. Corchado, W. Byrne and X. Yao. “A New Regression Based Software Cost Estimation Model Using Power Values”. In: Proceedings of Intelligent Data Engineering and Automated Learning-IDEAL 2007: 8th International Conference, Birmingham, UK”. Springer, Germany, 2007.

T. R. Benala, K. Chinnababu, R. Mall and S. Dehuri. “A Particle Swarm Optimized Functional Link Artificial Neural Network (PSO- FLANN) in Software Cost Estimation. In: Proceedings of the International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA)”. Springer, Germany, 2013.

Z. H. Wani and S. Quadri. “Artificial Bee Colony-Trained Functional Link Artificial Neural Network Model for Software Cost Estimation. In: Proceedings of Fifth International Conference on Soft Computing for Problem Solving: SocProS 2015”. vol. 2, Springer, Germany, 2016.

T. S. Sethi, C. V. Hari, B. T. Kaushal and S. Sharma. “Cluster Analysis and PSO for Software Cost Estimation. In: Proceedings of Information Technology and Mobile Communication. Springer, Germany, 2011.

T. R. Benala, S. Dehuri, S. C. Satapathy and S. Madhurakshara. “Genetic Algorithm for Optimizing Functional Link Artificial Neural Network based Software Cost Estimation. In: Proceedings of the International Conference on Information Systems Design and Intelligent Applications 2012 (INDIA 2012) held in Visakhapatnam, India”. Springer, Germany, 2012.

G. S. Rao, C. V. P. Krishna and K. R. Rao. “Multi Objective Particle Swarm Optimization for Software Cost Estimation. In: ICT and Critical Infrastructure: Proceedings of the 48th Annual Convention of Computer Society of India”. vol. 1. Springer International Publishing, Cham, 2014.

F. S. Gharehchopogh, R. Rezaii and B. Arasteh. “A New Approach by Using Tabu Search and Genetic algorithms in Software Cost Estimation. In 2015 9th International Conference on Application of Information and Communication Technologies (AICT)”. IEEE, United States, 2015.

S. S. Jafari and F. Ziaaddini. “Optimization of Software Cost Estimation Using Harmony Search Algorithm. In: 2016 1st Conference on Swarm Intelligence and Evolutionary Computation (CSIEC)”. IEEE, United States, 2016.

F. S. Gharehchopogh, L. Ebrahimi, I. Maleki and S. J. Gourabi. “A novel PSO based approach with hybrid of fuzzy C-means and learning automata in software cost estimation”. Indian Journal of Science and Technology, vol. 7, no. 6, p. 795, 2014.

Z. A. Khalifelu and F. S. Gharehchopogh. “Comparison and evaluation of data mining techniques with algorithmic models in software cost estimation”. Procedia Technology, vol. 1, pp. 65-71, 2012.

F. S. Gharehchopogh. “Neural Networks Application in Software Cost Estimation: A Case Study. In: 2011 International Symposium on Innovations in Intelligent Systems and Applications, Istanbul, Turkey”. IEEE, United States.

L. Oliveira, P. L. Braga, R. M. F. Lima and M. L. Cornélio. “GA-based method for feature selection and parameters optimization for machine learning regression applied to software effort estimation”. Information and Software Technology, vol. 52, no. 11, pp. 1155-1166, 2010.

Malik, V. Pandey and A. Kaushik. “An analysis of fuzzy approaches for COCOMO II”. International Journal of Intelligent Systems and Applications, vol. 5, no. 5, p. 68, 2013.

M. Molani, A. Ghaffari and A. Jafarian. “A new approach to software project cost estimation using a hybrid model of radial basis function neural network and genetic algorithm”. Indian Journal of Science and Technology, vol. 7, no. 6, pp. 838-843, 2014.

A. Hamdy. “Genetic fuzzy system for enhancing software estimation models”. International Journal of Modeling and Optimization, vol. 4, no. 3, p. 227, 2014.

Attarzadeh and S. H. Ow. “Proposing A New Software Cost Estimation Model Based on Artificial Neural Networks. In: 2010 2nd International Conference on Computer Engineering and Technology”. IEEE, United States, 2010.

T. R. Benala, S. Dehuri, S. Satapathy and C. S. Raghavi. “Genetic Algorithm for Optimizing Neural Network Based Software Cost Estimation. In: Swarm, Evolutionary, and Memetic Computing. Springer, Berlin, Heidelberg, 2011.

G. S. Rao, C. V. P. Krishna and K. R. Rao. “Multi Objective Particle Swarm Optimization for Software Cost Estimation. In: ICT and Critical Infrastructure: Proceedings of the 48th Annual Convention of Computer Society of India”. vol. 1. Springer International Publishing, Cham, 2014.

Kaushik, N. Choudhary and P. Srivastava. “Software Cost Estimation Using LSTM-RNN. In: Proceedings of International Conference on Artificial Intelligence and Applications: ICAIA 2020”. Springer, Germany, 2021.

N. Rankovic, D. Rankovic, M. Ivanovic and L. Lazic. “Improved effort and cost estimation model using artificial neural networks and Taguchi method with different activation functions”. Entropy (Basel), vol. 23, no. 7, p. 851, 2021.

M. Dashti, T. J. Gandomani, D. H. Adeh, H. Zulzalil and A. B. Sultan. “LEMABE: A novel framework to improve analogy-based software cost estimation using learnable evolution model”. PeerJ - Computer Science, vol. 8, p. e800, 2022.

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Published

2024-02-13

How to Cite

Mohamedyusf, H. M., Sharif, H. O., & Ghareb, M. I. (2024). A New Approach for Software Cost Estimation with a Hybrid Tabu Search and Invasive Weed Optimization Algorithms. UHD Journal of Science and Technology, 8(1), 42–54. https://doi.org/10.21928/uhdjst.v8n1y2024.pp42-54

Issue

Vol. 8 No. 1 (2024)

Section

Articles

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Copyright (c) 2024 Hoshmen Murad Mohamedyusf, Hawar Othman Sharif, Mazen Ismaeel Ghareb

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