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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Systematic literature review of machine learning based software development effort estimation models
Jianfeng Wen, Shixian Li, Zhiyong Lin, et al.
Information and Software Technology (2011) Vol. 54, Iss. 1, pp. 41-59
Closed Access | Times Cited: 471

Showing 1-25 of 471 citing articles:

A systematic review of machine learning techniques for software fault prediction
Ruchika Malhotra
Applied Soft Computing (2014) Vol. 27, pp. 504-518
Closed Access | Times Cited: 568
Machine Learning based Digital Twin Framework for Production Optimization in Petrochemical Industry
Qingfei Min, Yangguang Lu, Zhiyong Liu, et al.
International Journal of Information Management (2019) Vol. 49, pp. 502-519
Closed Access | Times Cited: 378
A systematic review of gait analysis methods based on inertial sensors and adaptive algorithms
Rafael Caldas, Marion Mundt, Wolfgang Potthast, et al.
Gait & Posture (2017) Vol. 57, pp. 204-210
Closed Access | Times Cited: 258
Identifying, categorizing and mitigating threats to validity in software engineering secondary studies
Apostolos Ampatzoglou, Stamatia Bibi, Paris Avgeriou, et al.
Information and Software Technology (2018) Vol. 106, pp. 201-230
Open Access | Times Cited: 236
A Systematic Literature Review on Cloud Computing Security: Threats and Mitigation Strategies
Bader Alouffi, Muhammad Hasnain, Abdullah Alharbi, et al.
IEEE Access (2021) Vol. 9, pp. 57792-57807
Open Access | Times Cited: 234
An effective approach for software project effort and duration estimation with machine learning algorithms
Przemysław Pospieszny, Beata Czarnacka-Chrobot, Andrzej Kobyliński
Journal of Systems and Software (2017) Vol. 137, pp. 184-196
Closed Access | Times Cited: 215
An empirical analysis of data preprocessing for machine learning-based software cost estimation
Jianglin Huang, Yan‐Fu Li, Min Xie
Information and Software Technology (2015) Vol. 67, pp. 108-127
Open Access | Times Cited: 192
Analogy-based software development effort estimation: A systematic mapping and review
Ali Idri, Fatima Azzahra Amazal, Alain Abran
Information and Software Technology (2014) Vol. 58, pp. 206-230
Closed Access | Times Cited: 189
Reviewing ensemble classification methods in breast cancer
Mohamed Hosni, Ibtissam Abnane, Ali Idri, et al.
Computer Methods and Programs in Biomedicine (2019) Vol. 177, pp. 89-112
Closed Access | Times Cited: 179
The application of machine learning techniques for driving behavior analysis: A conceptual framework and a systematic literature review
Zouhair Elamrani Abou Elassad, Hajar Mousannif, Hassan Al Moatassime, et al.
Engineering Applications of Artificial Intelligence (2019) Vol. 87, pp. 103312-103312
Closed Access | Times Cited: 173
Applications of artificial intelligence in engineering and manufacturing: a systematic review
Isaac Kofi Nti, Adebayo Felix Adekoya, Benjamin Asubam Weyori, et al.
Journal of Intelligent Manufacturing (2021) Vol. 33, Iss. 6, pp. 1581-1601
Closed Access | Times Cited: 143
Machine learning based methods for software fault prediction: A survey
Sushant Kumar Pandey, Ravi Bhushan Mishra, Anil Kumar Tripathi
Expert Systems with Applications (2021) Vol. 172, pp. 114595-114595
Closed Access | Times Cited: 117
A Systematic Literature Review on the Use of Deep Learning in Software Engineering Research
Cody Watson, Nathan Cooper, David Nader Palacio, et al.
ACM Transactions on Software Engineering and Methodology (2022) Vol. 31, Iss. 2, pp. 1-58
Open Access | Times Cited: 86
Deep learning in wheat diseases classification: A systematic review
Deepak Kumar, Vinay Kukreja
Multimedia Tools and Applications (2022) Vol. 81, Iss. 7, pp. 10143-10187
Closed Access | Times Cited: 82
Forecasting cardiovascular disease mortality using artificial neural networks in Sindh, Pakistan
Moiz Qureshi, Khushboo Ishaq, Muhammad Daniyal, et al.
BMC Public Health (2025) Vol. 25, Iss. 1
Open Access | Times Cited: 2
Effort estimation in agile software development
Muhammad Usman, Emília Mendes, Frâncila Weidt, et al.
(2014), pp. 82-91
Open Access | Times Cited: 180
The challenge of selecting and evaluating third-party reverse logistics providers in a multicriteria perspective: a Brazilian case
Patrícia Guarnieri, Vinícius Amorim Sobreiro, Marcelo Seido Nagano, et al.
Journal of Cleaner Production (2014) Vol. 96, pp. 209-219
Closed Access | Times Cited: 138
Systematic literature review of ensemble effort estimation
Ali Idri, Mohamed Hosni, Alain Abran
Journal of Systems and Software (2016) Vol. 118, pp. 151-175
Closed Access | Times Cited: 134
Neural network models for software development effort estimation: a comparative study
Ali Bou Nassif, Mohammad Azzeh, Luiz Fernando Capretz, et al.
Neural Computing and Applications (2015) Vol. 27, Iss. 8, pp. 2369-2381
Open Access | Times Cited: 117
Machine Learning Stock Market Prediction Studies: Review and Research Directions
Troy J. Strader, John J. Rozycki, Thomas H. Root, et al.
Journal of international technology and information management (2020) Vol. 28, Iss. 4, pp. 63-83
Open Access | Times Cited: 113
A Systematic Review of Intelligence Video Surveillance: Trends, Techniques, Frameworks, and Datasets
Guruh Fajar Shidik, Edi Noersasongko, Adhitya Nugraha, et al.
IEEE Access (2019) Vol. 7, pp. 170457-170473
Open Access | Times Cited: 96
Software Defect Prediction Based on Gated Hierarchical LSTMs
Hao Wang, Weiyuan Zhuang, Xiaofang Zhang
IEEE Transactions on Reliability (2021) Vol. 70, Iss. 2, pp. 711-727
Closed Access | Times Cited: 92
Investigating the use of random forest in software effort estimation
Abdelali Zakrani, Mustapha Hain, Namir Abdelwahed
Procedia Computer Science (2019) Vol. 148, pp. 343-352
Open Access | Times Cited: 86
Empirical Study of Software Defect Prediction: A Systematic Mapping
Lê Hoàng Sơn, Nakul Pritam, Manju Khari, et al.
Symmetry (2019) Vol. 11, Iss. 2, pp. 212-212
Open Access | Times Cited: 83
Software effort estimation accuracy prediction of machine learning techniques: A systematic performance evaluation
Yasir Mahmood, Nazri Kama, Azri Azmi, et al.
Software Practice and Experience (2021) Vol. 52, Iss. 1, pp. 39-65
Open Access | Times Cited: 81
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