Xiaofei Xie

6.3k total citations · 3 hit papers
173 papers, 3.2k citations indexed

About

Xiaofei Xie is a scholar working on Artificial Intelligence, Software and Information Systems. According to data from OpenAlex, Xiaofei Xie has authored 173 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 88 papers in Artificial Intelligence, 59 papers in Software and 55 papers in Information Systems. Recurrent topics in Xiaofei Xie's work include Software Testing and Debugging Techniques (52 papers), Adversarial Robustness in Machine Learning (50 papers) and Software Engineering Research (42 papers). Xiaofei Xie is often cited by papers focused on Software Testing and Debugging Techniques (52 papers), Adversarial Robustness in Machine Learning (50 papers) and Software Engineering Research (42 papers). Xiaofei Xie collaborates with scholars based in Singapore, China and Japan. Xiaofei Xie's co-authors include Yang Liu, Lei Ma, Jianjun Zhao, Felix Juefei-Xu, Hongxu Chen, Qing Guo, Yuekang Li, Xiaohong Li, Qiang Hu and Bihuan Chen and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and Journal of Materials Chemistry A.

In The Last Decade

Xiaofei Xie

149 papers receiving 3.1k citations

Hit Papers

DeepHunter: a coverage-guided fuzz testing framework for ... 2019 2026 2021 2023 2019 2024 2024 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. DeepHunter: a coverage-guided fuzz testing framework for deep neural networks
    2019 269 citations Xiaofei Xie, Lei Ma et al. profile →
  2. Exploring the Potential of ChatGPT in Automated Code Refinement: An Empirical Study
    2024 70 citations Xiaofei Xie, Shangqing Liu et al. profile →
  3. GPTScan: Detecting Logic Vulnerabilities in Smart Contracts by Combining GPT with Program Analysis
    2024 52 citations Xiaofei Xie, Yang Liu et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Xiaofei Xie Singapore 31 1.6k 1.1k 892 852 657 173 3.2k
Lei Ma Japan 32 2.2k 1.4× 1.2k 1.1× 1.0k 1.1× 630 0.7× 770 1.2× 148 3.7k
Jian–Guang Lou China 30 1.9k 1.2× 698 0.7× 1.4k 1.6× 303 0.4× 723 1.1× 114 3.9k
Zhi Quan Zhou Australia 24 614 0.4× 1.7k 1.6× 857 1.0× 338 0.4× 164 0.2× 102 2.4k
Shouling Ji China 38 2.1k 1.3× 229 0.2× 1.1k 1.2× 814 1.0× 680 1.0× 252 4.4k
Marco Vieira Portugal 28 1.0k 0.6× 754 0.7× 1.9k 2.1× 749 0.9× 71 0.1× 223 3.4k
Manju Khari India 26 613 0.4× 210 0.2× 519 0.6× 366 0.4× 396 0.6× 132 2.3k
Franz Wotawa Austria 24 949 0.6× 2.3k 2.2× 1.5k 1.7× 253 0.3× 110 0.2× 372 3.4k
Asaf Shabtai Israel 30 1.8k 1.2× 493 0.5× 1.6k 1.8× 2.5k 2.9× 219 0.3× 169 4.4k
Ding Yuan China 26 572 0.4× 683 0.6× 1.3k 1.4× 146 0.2× 553 0.8× 145 2.7k
Rafiqul Islam Australia 21 944 0.6× 129 0.1× 739 0.8× 971 1.1× 313 0.5× 131 2.1k

Countries citing papers authored by Xiaofei Xie

Since Specialization
Citations

This map shows the geographic impact of Xiaofei Xie's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Xiaofei Xie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaofei Xie more than expected).

Fields of papers citing papers by Xiaofei Xie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiaofei Xie. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Xiaofei Xie. The network helps show where Xiaofei Xie may publish in the future.

Co-authorship network of co-authors of Xiaofei Xie

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaofei Xie. A scholar is included among the top collaborators of Xiaofei Xie based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xiaofei Xie. Xiaofei Xie is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Zhang, Jie M., et al.. (2025). Bias Testing and Mitigation in LLM-based Code Generation. ACM Transactions on Software Engineering and Methodology. 35(1). 1–31. 4 indexed citations
3.
Hu, Qiang, Xiaofei Xie, Maxime Cordy, et al.. (2025). Assessing the Robustness of Test Selection Methods for Deep Neural Networks. ACM Transactions on Software Engineering and Methodology.
4.
Xie, Xiaofei, et al.. (2025). GUI Test Migration via Abstraction and Concretization. ACM Transactions on Software Engineering and Methodology. 35(2). 1–29.
5.
Chen, Sen, et al.. (2024). A Comprehensive Study on Static Application Security Testing (SAST) Tools for Android. IEEE Transactions on Software Engineering. 50(12). 3385–3402. 3 indexed citations
6.
Hu, Ming, Xiaofei Xie, Cheng Chen, et al.. (2024). Is Aggregation the Only Choice? Federated Learning via Layer-wise Model Recombination. 1096–1107. 4 indexed citations
7.
Xie, Xiaofei, et al.. (2024). Neuron Sensitivity-Guided Test Case Selection. ACM Transactions on Software Engineering and Methodology. 33(7). 1–32. 1 indexed citations
8.
Liu, Shangqing, et al.. (2024). Unveiling Code Pre-Trained Models: Investigating Syntax and Semantics Capacities. ACM Transactions on Software Engineering and Methodology. 33(7). 1–29. 11 indexed citations
9.
Zheng, Yaowen, et al.. (2024). How Effective Are They? Exploring Large Language Model Based Fuzz Driver Generation. 1223–1235. 8 indexed citations
10.
Liu, Shangqing, et al.. (2024). Automated Commit Intelligence by Pre-training. ACM Transactions on Software Engineering and Methodology. 3 indexed citations
11.
12.
13.
Li, Hongjia, Xiaofei Xie, Nirwan Ansari, et al.. (2024). Reinforcement Learning Based Online Request Scheduling Framework for Workload-Adaptive Edge Deep Learning Inference. IEEE Transactions on Mobile Computing. 23(12). 13222–13239. 1 indexed citations
14.
Hu, Ming, et al.. (2024). FlexFL: Heterogeneous Federated Learning via APoZ-Guided Flexible Pruning in Uncertain Scenarios. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 43(11). 4069–4080. 2 indexed citations
15.
Zhao, Ziming, et al.. (2023). DDoS family: A novel perspective for massive types of DDoS attacks. Computers & Security. 138. 103663–103663. 18 indexed citations
16.
Xie, Xiaofei, et al.. (2023). DistXplore: Distribution-Guided Testing for Evaluating and Enhancing Deep Learning Systems. Monash University Research Portal (Monash University). 68–80. 5 indexed citations
17.
Li, Haoliang, et al.. (2022). Neuron Coverage-Guided Domain Generalization. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(1). 1302–1311. 26 indexed citations
18.
Xiao, Yan, Ivan Beschastnikh, Yun Lin, et al.. (2022). Self-Checking Deep Neural Networks for Anomalies and Adversaries in Deployment. IEEE Transactions on Dependable and Secure Computing. 1–18. 5 indexed citations
19.
Chan, Alvin, Lei Ma, Felix Juefei-Xu, et al.. (2021). Breaking Neural Reasoning Architectures With Metamorphic Relation-Based Adversarial Examples. IEEE Transactions on Neural Networks and Learning Systems. 33(11). 6976–6982. 9 indexed citations
20.
Guo, Qing, Felix Juefei-Xu, Xiaofei Xie, et al.. (2020). ABBA: Saliency-Regularized Motion-Based Adversarial Blur Attack. arXiv (Cornell University). 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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