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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:

The impact of using biased performance metrics on software defect prediction research
Jingxiu Yao, Martin Shepperd
Information and Software Technology (2021) Vol. 139, pp. 106664-106664
Open Access | Times Cited: 43

Showing 1-25 of 43 citing articles:

Predicting test failures induced by software defects: A lightweight alternative to software defect prediction and its industrial application
Lech Madeyski, Szymon Stradowski
Journal of Systems and Software (2025) Vol. 223, pp. 112360-112360
Closed Access | Times Cited: 1
Predicting the precise number of software defects: Are we there yet?
Xiao Yu, Jacky Keung, Yan Xiao, et al.
Information and Software Technology (2022) Vol. 146, pp. 106847-106847
Closed Access | Times Cited: 34
How far are we from reproducible research on code smell detection? A systematic literature review
Tomasz Lewowski, Lech Madeyski
Information and Software Technology (2021) Vol. 144, pp. 106783-106783
Open Access | Times Cited: 36
Detecting code smells using industry-relevant data
Lech Madeyski, Tomasz Lewowski
Information and Software Technology (2022) Vol. 155, pp. 107112-107112
Closed Access | Times Cited: 24
On the Reliability of the Area Under the ROC Curve in Empirical Software Engineering
Luigi Lavazza, Sandro Morasca, Gabriele Rotoloni
(2023), pp. 93-100
Open Access | Times Cited: 15
Adaptive Ensemble Learning Model-Based Binary White Shark Optimizer for Software Defect Classification
Jameel Saraireh, Mary Agoyi, Sofian Kassaymeh
International Journal of Computational Intelligence Systems (2025) Vol. 18, Iss. 1
Open Access
LLMs for product classification in e-commerce: A zero-shot comparative study of GPT and claude models
Konstantinos I. Roumeliotis, Nikolaos D. Tselikas, Dimitrios Κ. Nasiopoulos
Natural Language Processing Journal (2025), pp. 100142-100142
Open Access
Data quality issues in software fault prediction: a systematic literature review
Kirti Bhandari, Kuldeep Kumar, Amrit Lal Sangal
Artificial Intelligence Review (2022) Vol. 56, Iss. 8, pp. 7839-7908
Closed Access | Times Cited: 20
An Adaptive Rank Aggregation-Based Ensemble Multi-Filter Feature Selection Method in Software Defect Prediction
Abdullateef O. Balogun, Shuib Basri, Luiz Fernando Capretz, et al.
Entropy (2021) Vol. 23, Iss. 10, pp. 1274-1274
Open Access | Times Cited: 24
Test case prioritization using test case diversification and fault-proneness estimations
Mostafa Mahdieh, Seyed‐Hassan Mirian‐Hosseinabadi, Mohsen Mahdieh
Automated Software Engineering (2022) Vol. 29, Iss. 2
Open Access | Times Cited: 15
HEDF: A Method for Early Forecasting Software Defects Based on Human Error Mechanisms
Fuqun Huang, Lorenzo Strigini
IEEE Access (2023) Vol. 11, pp. 3626-3652
Open Access | Times Cited: 8
Ensemble learning based software defect prediction
Xin Dong, Yan Liang, Shoichiro Miyamoto, et al.
Journal of Engineering Research (2023) Vol. 11, Iss. 4, pp. 377-391
Open Access | Times Cited: 8
Common Problems With the Usage of F-Measure and Accuracy Metrics in Medical Research
Luigi Lavazza, Sandro Morasca
IEEE Access (2023) Vol. 11, pp. 51515-51526
Open Access | Times Cited: 7
LogSD: Detecting Anomalies from System Logs through Self-Supervised Learning and Frequency-Based Masking
Yongzheng Xie, Hongyu Zhang, Muhammad Ali Babar
Proceedings of the ACM on software engineering. (2024) Vol. 1, Iss. FSE, pp. 2098-2120
Open Access | Times Cited: 2
Comparing ϕ and the F-measure as performance metrics for software-related classifications
Luigi Lavazza, Sandro Morasca
Empirical Software Engineering (2022) Vol. 27, Iss. 7
Open Access | Times Cited: 11
Graph-based machine learning improves just-in-time defect prediction
Jonathan R. Bryan, Pablo Moriano
PLoS ONE (2023) Vol. 18, Iss. 4, pp. e0284077-e0284077
Open Access | Times Cited: 6
On the validity of retrospective predictive performance evaluation procedures in just-in-time software defect prediction
Liyan Song, Leandro L. Minku, Xin Yao
Empirical Software Engineering (2023) Vol. 28, Iss. 5
Open Access | Times Cited: 6
ST-TLF: Cross-version defect prediction framework based transfer learning
Yanyang Zhao, Yawen Wang, Yuwei Zhang, et al.
Information and Software Technology (2022) Vol. 149, pp. 106939-106939
Closed Access | Times Cited: 9
An effective software cross-project fault prediction model for quality improvement
Yogita Khatri, Sandeep Kumar Singh
Science of Computer Programming (2023) Vol. 226, pp. 102918-102918
Closed Access | Times Cited: 5
Eliminating the high false‐positive rate in defect prediction through BayesNet with adjustable weight
Yanyang Zhao, Yawen Wang, Dalin Zhang, et al.
Expert Systems (2022) Vol. 39, Iss. 6
Open Access | Times Cited: 8
The need for more informative defect prediction: A systematic literature review
Natalie Grattan, Daniel Alencar da Costa, Nigel Stanger
Information and Software Technology (2024) Vol. 171, pp. 107456-107456
Open Access | Times Cited: 1
DBOS_US: a density-based graph under-sampling method to handle class imbalance and class overlap issues in software fault prediction
Kirti Bhandari, Kuldeep Kumar, Amrit Lal Sangal
The Journal of Supercomputing (2024) Vol. 80, Iss. 15, pp. 22682-22725
Closed Access | Times Cited: 1
Costs and Benefits of Machine Learning Software Defect Prediction: Industrial Case Study
Szymon Stradowski, Lech Madeyski
(2024), pp. 92-103
Closed Access | Times Cited: 1
Improve cross-project just-in-time defect prediction with dynamic transfer learning
Hongming Dai, Jianqing Xi, Hong‐Liang Dai
Journal of Systems and Software (2024), pp. 112214-112214
Closed Access | Times Cited: 1
End-to-end ancient ceramic classification toolkit based on deep learning: A case study of black glazed wares of Jian kilns (Song Dynasty, Fujian province)
Yong Qi, Meng-Zhe Qiu, Haizhao Jing, et al.
Ceramics International (2022) Vol. 48, Iss. 23, pp. 34516-34532
Closed Access | Times Cited: 7
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