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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:

Towards more accurate severity prediction and fixer recommendation of software bugs
Tao Zhang, Jiachi Chen, Geunseok Yang, et al.
Journal of Systems and Software (2016) Vol. 117, pp. 166-184
Closed Access | Times Cited: 139

Showing 1-25 of 139 citing articles:

Fusion of Multi-RSMOTE With Fuzzy Integral to Classify Bug Reports With an Imbalanced Distribution
Rong Chen, Shikai Guo, Xizhao Wang, et al.
IEEE Transactions on Fuzzy Systems (2019) Vol. 27, Iss. 12, pp. 2406-2420
Closed Access | Times Cited: 79
Deep Neural Network-Based Severity Prediction of Bug Reports
Waheed Yousuf Ramay, Qasim Umer, Yin Xu, et al.
IEEE Access (2019) Vol. 7, pp. 46846-46857
Open Access | Times Cited: 77
Topic modeling in software engineering research
Camila Costa Silva, Matthias Galster, Fabian Gilson
Empirical Software Engineering (2021) Vol. 26, Iss. 6
Open Access | Times Cited: 70
Emotion Based Automated Priority Prediction for Bug Reports
Qasim Umer, Hui Liu, Yasir Sultan
IEEE Access (2018) Vol. 6, pp. 35743-35752
Open Access | Times Cited: 82
How Practitioners Perceive Automated Bug Report Management Techniques
Weiqin Zou, David Lo, Zhenyu Chen, et al.
IEEE Transactions on Software Engineering (2018) Vol. 46, Iss. 8, pp. 836-862
Open Access | Times Cited: 82
A Novel Deep-Learning-Based Bug Severity Classification Technique Using Convolutional Neural Networks and Random Forest with Boosting
Ashima Kukkar, Rajni Mohana, Anand Nayyar, et al.
Sensors (2019) Vol. 19, Iss. 13, pp. 2964-2964
Open Access | Times Cited: 72
Developer Activity Motivated Bug Triaging: Via Convolutional Neural Network
Shikai Guo, Xinyi Zhang, Xi Yang, et al.
Neural Processing Letters (2020) Vol. 51, Iss. 3, pp. 2589-2606
Closed Access | Times Cited: 55
Bug severity prediction using question-and-answer pairs from Stack Overflow
Youshuai Tan, Sijie Xu, Zhaowei Wang, et al.
Journal of Systems and Software (2020) Vol. 165, pp. 110567-110567
Closed Access | Times Cited: 51
Prioritizing tasks in software development: A systematic literature review
Yegor Bugayenko, Ayomide Bakare, Arina Cheverda, et al.
PLoS ONE (2023) Vol. 18, Iss. 4, pp. e0283838-e0283838
Open Access | Times Cited: 18
An artificial intelligence framework on software bug triaging, technological evolution, and future challenges: A review
Naresh Kumar Nagwani, Jasjit S. Suri
International Journal of Information Management Data Insights (2023) Vol. 3, Iss. 1, pp. 100153-100153
Open Access | Times Cited: 17
Ensemble Data Reduction Techniques and Multi-RSMOTE via Fuzzy Integral for Bug Report Classification
Shikai Guo, Rong Chen, Miaomiao Wei, et al.
IEEE Access (2018) Vol. 6, pp. 45934-45950
Open Access | Times Cited: 59
Entropy Based Software Reliability Analysis of Multi-Version Open Source Software
V. B. Singh, Meera Sharma, Hoang Pham
IEEE Transactions on Software Engineering (2017) Vol. 44, Iss. 12, pp. 1207-1223
Closed Access | Times Cited: 53
The Influence Ranking for Testers in Bug Tracking Systems
Hui Li, Guofeng Gao, Rong Chen, et al.
International Journal of Software Engineering and Knowledge Engineering (2019) Vol. 29, Iss. 01, pp. 93-113
Closed Access | Times Cited: 51
Bug report severity level prediction in open source software: A survey and research opportunities
Luiz Alberto Ferreira Gomes, Ricardo da Silva Torres, Mario Lúcio Côrtes
Information and Software Technology (2019) Vol. 115, pp. 58-78
Closed Access | Times Cited: 46
Bug Report Enrichment with Application of Automated Fixer Recommendation
Tao Zhang, Jiachi Chen, He Jiang, et al.
(2017), pp. 230-240
Closed Access | Times Cited: 44
Automatic prediction of the severity of bugs using stack traces and categorical features
Korosh Koochekian Sabor, Mohammad Hamdaqa, Abdelwahab Hamou‐Lhadj
Information and Software Technology (2019) Vol. 123, pp. 106205-106205
Closed Access | Times Cited: 36
On the classification of bug reports to improve bug localization
Fan Fang, John F. Wu, Yanyan Li, et al.
Soft Computing (2021) Vol. 25, Iss. 11, pp. 7307-7323
Closed Access | Times Cited: 32
Multi-triage: A multi-task learning framework for bug triage
Thazin Win Win Aung, Yao Wan, Huan Huo, et al.
Journal of Systems and Software (2021) Vol. 184, pp. 111133-111133
Closed Access | Times Cited: 32
Production and test bug report classification based on transfer learning
Misoo Kim, Youngkyoung Kim, Eunseok Lee
Information and Software Technology (2025), pp. 107685-107685
Closed Access
Fixer-level supervised contrastive learning for bug assignment
Rongcun Wang, Xingyu Ji, Yuan Tian, et al.
Empirical Software Engineering (2025) Vol. 30, Iss. 3
Closed Access
How incidental are the incidents?
Junjie Chen, Shu Zhang, Xiaoting He, et al.
(2020)
Closed Access | Times Cited: 28
Considering dependencies between bug reports to improve bugs triage
Rafi Almhana, Marouane Kessentini
Automated Software Engineering (2021) Vol. 28, Iss. 1
Closed Access | Times Cited: 27
Effective Prediction of Bug-Fixing Priority via Weighted Graph Convolutional Networks
Sen Fang, Youshuai Tan, Tao Zhang, et al.
IEEE Transactions on Reliability (2021) Vol. 70, Iss. 2, pp. 563-574
Open Access | Times Cited: 27
BTAL: An imbalance software bug report triage approach based on BERT-TextCNN
Yanmei Zhang, Yuhang Sun, Yi Shi, et al.
Information and Software Technology (2025), pp. 107731-107731
Closed Access
Predicting the Severity of Bug Reports Based on Feature Selection
Wenjie Liu, Shanshan Wang, Xin Chen, et al.
International Journal of Software Engineering and Knowledge Engineering (2018) Vol. 28, Iss. 04, pp. 537-558
Closed Access | Times Cited: 29
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