李增扬 (Zengyang Li)

李增扬 (Zengyang Li)

Associate Professor in Software Engineering

Zengyang Li is an Associate Professor with the Department of Software Engineering of the School of Computer Science at Central China Normal University, Wuhan, China. His research interests are in Multilingual Software, Software Architecture, SE4AI, AI4SE, AI4EDU. He has published 80+ papers in prestigious journals (e.g., TOSEM, EMSE, JSS, IST, ASEJ), conferences (ASE, ICSE, ICSME, ESEM, ICPC), and books.

Research Interests

  • Multilingual Software
  • Intelligent Software Engineering
  • Software Maintenance and Evolution
  • Software Architecture
  • AI for Education

Work Experience

  • 2018-present, Associate Professor, School of Computer Science, Central China Normal University, Wuhan, China
  • 2015-2018, Lecturer, School of Computer Science, Wuhan University, Wuhan, China
  • 2007-2010, Senior Engineer, ZTE Corporation, Shenzhen, China

Education

  • 2011-2015, PhD, Software Engineering, University of Groningen, The Netherlands (2012.2-2012.4, visited University of Luxembourg)
  • 2005-2007, Master, Computer Software and Thoery, Wuhan University, China
  • 2001-2005, Bachelor, Information and Computing Science, Wuhan University, China

Academic Services

  • Reviewer for Journals: ACM TOSEM, IEEE TSC, JSS, IST, IEEE TR, IEEE TCSS, JSEP, SPE, IET Software, FCS, IJSEKE etc.
  • PC Member: SEKE 2021-2026、SEAA 2021-2026 STREAM Special Session、CEISEE 2023-2025

Publications

Journal Articles

  1. G. Cai, Z. Li*, P. Liang, R. Mo, H. Liu, Y. Ma, Bug Priority Change Prediction: An Exploratory Study on Apache Software, ACM Transactions on Software Engineering and Methodology, 2025, DOI: http://dx.doi.org/10.1145/3785148.
  2. Z. Li, P. Avgeriou, P. Liang, A systematic mapping study on technical debt and its management, Journal of Systems and Software, 2015, 101(3), pp. 193-220. (1020+ Citations，ESI Highly Cited Paper)
  3. Z. Li, P. Liang, P. Avgeriou, Application of knowledge-based approaches in software architecture: A systematic mapping study, Information and Software Technology, 2013, 55(5), pp. 777-794.
  4. Z. Li, B. Huang, Y. Li, R. Mo, P. Liang, H. Liu, Y. Ma, Unveiling Code Clones in the Eclipse IIoT Software Ecosystem, Journal of System and Software, 2026, 112869.
  5. Z. Li, X. Zhang, W. Wang, P. Liang, R. Mo, H. Liu, Automated Detection of Inter-Language Design Smells in Multi-Language Deep Learning Frameworks, Information and Software Technology, 2025,179, 107656.
  6. W. Cheng, Z. Li*, P. Liang, R. Mo, H. Liu, Unveiling Security Weaknesses in Autonomous Driving Systems: An In-Depth Empirical Study, Information and Software Technology, 2025, 182, 107709.
  7. B. Zhang, P. Liang, X. Zhou, X. Zhou, D. Lo, Q. Feng, Z. Li, L. Li, A Comprehensive Evaluation of Parameter-Efficient Fine-Tuning on Code Smell Detection, ACM Transactions on Software Engineering and Methodology, 2026, In press.
  8. R. Li, R. Mo, Y. Zeng, Z. Liu, Z. Li, Y. Ma, A Multi-Dimensional Quality Evaluation of Code Generated by LLM-Based Tools Across Multiple Programming Languages, ACM Transactions on Software Engineering and Methodology, 2026, DOI：https://doi.org/10.1145/3800582.
  9. R. Li, P. Liang, Y. Wang, Y. Cai, W. Sun, Z. Li, Unveiling the Role of ChatGPT in Software Development: Insights from Developer-ChatGPT Interactions on GitHub, ACM Transactions on Software Engineering and Methodology, 2026, DOI: https://doi.org/10.1145/3798163.
  10. X. Zhou, R. Li, P. Liang, B. Zhang, M. Shahin, Z. Li, C. Yang, Using LLMs in Generating Design Rationale for Software Architecture Decisions, ACM Transactions on Software Engineering and Methodology, 2025, DOI: https://doi.org/10.1145/3785010.
  11. Y. Fu, P. Liang, A. Tahir, Z. Li, M. Shahin, J. Yu, Security Weaknesses of Copilot-Generated Code in GitHub Projects: An Empirical Study, ACM Transactions on Software Engineering and Methodology, 2025, 34(8), Article No.: 218, Pages 1-34.
  12. R. Mo, D. Wang, W. Zhan, Y. Jiang, Y. Wang, Y. Zhao, Z. Li, Y. Ma, Assessing and Analyzing the Correctness of GitHub Copilot’s Code Suggestions, ACM Transactions on Software Engineering and Methodology, 2025, 34(7), Article No.: 194, Pages 1-32.
  13. Y. Jiang, R. Mo, W. Zhan, D. Wang, Z. Li, Y. Ma, Leveraging Modular Architecture for Bug Characterization and Analysis in Automated Driving Software, ACM Transactions on Software Engineering and Methodology, 2025, 34(4), Article No.:114, pp. 1-31.
  14. C. Wu, R. Mo, W. Ding, H. Song, Z. Li, Y. Ma, Exploring and characterizing cross-service defects in microservice projects, Information and Software Technology, 2026, 194, 108063.
  15. X. Zhou, P. Liang, B. Zhang, Z. Li, A. Ahmad, M. Shahin, M. Waseem, Exploring the Problems, their Causes and Solutions of AI Pair Programming: A Study on GitHub and Stack Overflow, Journal of System and Software, 2025, 219, 112204.
  16. H. Liu, M. Lü, X. Zhang, Z. Li, G. Chen, Z. Zeng, J. Lü, Optimizing Pinning-Synchronization and Mining Pinned-Nodes of Directed Networks, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2025, 55(7), 4600-4613.
  17. Z. Li, G. Cai, Q. Yu, P. Liang, R. Mo, H. Liu, Bug Priority Change: An Empirical Study on Apache Projects, Journal of Systems and Software, 2024, 212, 112019.
  18. Z. Li, J. Ji, P. Liang, R. Mo, H. Liu, An Exploratory Study on Just-in-Time Multi-Programming-Language Bug Prediction, Information and Software Technology, 2024, 175, 107524.
  19. M.S. Aktar, P. Liang, M. Waseem, A. Tahir, A. Ahmad, B. Zhang, Z. Li, Architecture Decisions in Quantum Software Systems: An Empirical Study on Stack Exchange and GitHub, Information and Software Technology, 2024, 107587.
  20. M. J. de Dieu, P. Liang, M. Shahin, C. Yang, Z. Li, Mining Architectural Information: A Systematic Mapping Study, Empirical Software Engineering, 2024, 29:79, pp. 1-59.
  21. R. Mo, Y. Zhang, Y. Wang, S. Zhang, P. Xiong, Z. Li, Y. Zhao, Exploring the Impact of Code Clones on Deep Learning Software, ACM Transactions on Software Engineering and Methodology, 2023, Article No.: 153, pp. 1-34.
  22. H. Liu, S. Zhang, C.W. Wu, X. Wu, Z. Li, J. Xu, Intralayer Synchronization in Heterogeneous Multiplex Dynamical Networks Based on Spectral Graph Theory, IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2023, pp. 1-12.
  23. Z. Li, X. Qi, Q. Yu, P. Liang, R. Mo, C. Yang, Exploring Multi-Programming-Language Commits and Their Impacts on Software Quality: An Empirical Study on Apache Projects, Journal of Systems and Software, 2022, 194, 111508.
  24. H. Liu, J. Li, Z. Li*, Z. Zeng, J. Lü, Intralayer Synchronization of Multiplex Dynamical Networks via Pinning Impulsive Control, IEEE Transactions on Cybernetics, 2022, 52(4), pp. 2110-2122.
  25. R. Mo, S. Wei, Q. Feng, Z. Li, An exploratory study of bug prediction at the method level, Information and Software Technology, 2022, 144, 106794.
  26. H. Liu, Y. Li, Z. Li, J. Lu, J.-A. Lu, Topology Identification of Multi-link Complex Dynamical Networks via Adaptive Observers Incorporating Chaotic Exosignals, IEEE Transactions on Cybernetics, 2022, 52(7), pp. 6255-6268.
  27. C. Cheng, B. Li, Z. Li, P. Liang, X. Yang, An In-depth Study of the Effects of Methods on the Dataset Selection of Public Development Projects, IET Software, 2022, 16(2), pp. 146-166.
  28. C. Cheng, B. Li, Z. Li, P. Liang, X. Han, J. Zhang, Improving Generality and Accuracy of Existing Public Development Project Selection Methods: A Study on GitHub Ecosystem, Automated Software Engineering, 2022, 29(1), pp. Article 33: 31-43.
  29. H. Liu, B. Wang, J.-A. Lu, Z. Li, Node-set importance and optimization algorithm of nodes selection in complex networks based on pinning control, Acta Physica Sinica, 2021, 70(5), 056401. (In Chinese)
  30. S. Shcherban, P. Liang, Z. Li, C. Yang, Multiclass Classification of UML Diagrams from Images Using Deep Learning, International Journal of Software Engineering and Knowledge Engineering, 2021, 31(11&12), pp. 1683-1698.
  31. H. Liu, J. Chi, Z. Li, Z. Zeng, J. Lü, Parameter Identification of Memristor-based Chaotic Systems Via the Drive-response Synchronization Method, IEEE Transactions on Circuits and Systems II: Express Briefs, 2021, 68(6), pp. 2082-2086.
  32. H. Liu, J. Xu, Z. Li*, X. Wang, J. Lü, Z. Zeng, Optimizing Synchronizability of Multilayer Networks Based on the Graph Comparison Method, IEEE Transactions on Circuits and Systems I: Regular Papers, 2020, 67(5), pp. 1740-1751.
  33. Z. Li, P. Liang, D. Li, R. Mo, B. Li, Is bug severity in line with bug fixing change complexity?, International Journal of Software Engineering and Knowledge Engineering, 2020, 30(11&12), pp. 1779-1800.
  34. Z. Li, H. Liu, J.-a. Lu, Z. Zeng, J. Lü, Synchronization Regions of Discrete-Time Dynamical Networks with Impulsive Couplings, Information Sciences, 2018, 459, pp. 265-277.
  35. C. Cheng, B. Li, Z. Li*, Y. Zhao, F. Liao, Developer Role Evolution in Open Source Software Ecosystem: An Explanatory Study on GNOME, Journal of Computer Science and Technology, 2017, 32(2), pp. 396-414.
  36. R. Yang, B. Li, J. Wang, Z. Li*, Y. Hu, Reusing Service Process Fragments with A Consensus Between Service Providers and Users, Chinese Journal of Electronics, 2016, 25(4), pp. 648-657.

Conference Papers

  1. S. Gao, Z. Wang, Y. Zhao, Z. Li, Enhancing Edge Microservice Deployment Efficiency with an LLM-empowered Multi-Agent Framework, in: Proceedings of the 32nd International Conference on Neural Information Processing (ICONIP ’25), 2025.
  2. Z. Li, T. Jiang, H. Liu, S. Wang, Sentiment Analysis for Bug Resolution in Multi-language Deep Learning Frameworks, in: Proceedings of the 10th International Conference on Cloud Computing and Big Data Analytics (ICCCBDA’25), 2025, pp. 193-198.
  3. B. Zhang, P. Liang, Q. Feng, Y. Fu, Z. Li, Copilot-in-the-Loop: Fixing Code Smells in Copilot-Generated Python Code using Copilot, in: Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering (ASE’24), NIER track, ACM, 2024, pp. 2230-2234.
  4. R. Mo, Y. Jiang, W. Zhan, D. Wang, Z. Li, A Comprehensive Study on Code Clones in Automated Driving Software, in: Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE’23), 2023.
  5. Z. Li, S. Wang, W. Wang, P. Liang, R. Mo, B. Li, Understanding Bugs in Multi-Language Deep Learning Frameworks, in: Proceedings of the 31st International Conference on Program Comprehension (ICPC’23), 2023, pp. 328-338.
  6. Z. Li, W. Wang, S. Wang, P. Liang, R. Mo, Understanding Resolution of Multi-Language Bugs: An Empirical Study on Apache Projects, in: Proceedings of the 17th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM’23), 2023, pp. 1-11.
  7. R. Mo, Y. Wang, Y. Zhang, Z. Li, Just-in-Time Defect Severity Prediction, in: Proceedings of the 35th International Conference on Software Engineering and Knowledge Engineering (SEKE’23), 2023, pp. 232-237.
  8. L. Fu, P. Liang, Z. Rasheed, Z. Li, A. Tahir, X. Han, Potential Technical Debt and Its Resolution in Code Reviews: An Exploratory Study of the OpenStack and Qt Communities, in: Proceedings of the 16th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM‘22), 2022, pp. 216-226.
  9. Z. Li, J. Xu, G. Cai, P. Liang, R. Mo, A Preliminary Study on the Explicitness of Bug Associations, in: Proceedings of the 34th International Conference on Software Engineering and Knowledge Engineering (SEKE’22), 2022, pp. 212-215.
  10. Y. Luo, P. Liang, M. Shahin, Z. Li, C. Yang, Decisions in Continuous Integration and Delivery: An Exploratory Study, in: Proceedings of the 34th International Conference on Software Engineering and Knowledge Engineering (SEKE’22), 2022, pp. 457-462.
  11. S. Wang, H. Liu, Y. Chen, Z. Li*, Ecological Protected Area Evaluation and Site Selection Methods Based on the Saihanba Ecological Model, in: Proceedings of the 14th International Conference on Advanced Computational Intelligence (ICACI’22), 2022, pp. 350-356.
  12. Z. Li, X. Qi, Q. Yu, P. Liang, R. Mo, C. Yang, Multi-Programming-Language Commits in OSS: An Empirical Study on Apache Projects, in: Proceedings of the 29th IEEE/ACM International Conference on Program Comprehension (ICPC’21), 2021, pp. 219-229.
  13. C. Yang, P. Liang, L. Fu, Z. Li, Self-Claimed Assumptions in Deep Learning Frameworks: An Exploratory Study, in: Proceedings of the 25th International Conference on Evaluation and Assessment in Software Engineering (EASE’21), 2021, pp. 139-148.
  14. S. Wei, R. Mo, P. Xiong, S. Zhang, Y. Zhao, Z. Li, Predicting and Monitoring Bug-Proneness at the Feature Level, in: Proceedings of the 7th International Symposium on Dependable Software Engineering: Theories, Tools, and Applications (SETTA‘21), 2021, pp. 201-218.
  15. S. Shcherban, P. Liang, Z. Li, C. Yang, Multiclass Classification of Four Types of UML Diagrams from Images Using Deep Learning, in: Proceedings of the 33th International Conference on Software Engineering and Knowledge Engineering (SEKE’21), 2021, pp. 57-62.
  16. R. Mo, Y. Zhao, Q. Feng, Z. Li, The Existence and Co-Modifications of Code Clones within and across Microservices, in: Proceedings of the 15th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM’21), 2021, Article 20 (11 pages).
  17. T. Hu, R. Mo, P. Xiong, Z. Li, Q. Feng, Formal Definition and Automatic Generation of Semantic Metrics: An Empirical Study on Bug Prediction, in: Proceedings of the 21st IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM’21), 2021.
  18. Z. Li, Q. Yu, P. Liang, R. Mo, C. Yang, Interest of Defect Technical Debt: An Exploratory Study on Apache Projects, in: Proceedings of the 36th IEEE International Conference on Software Maintenance and Evolution (ICSME’20), 2020, pp. 629-639.
  19. Z. Li, D. Li, P. Liang, R. Mo, An Empirical Investigation on the Relationship Between Bug Severity and Bug Fixing Change Complexity, in: Proceedings of the 32th International Conference on Software Engineering and Knowledge Engineering (SEKE’20), 2020, pp. 365-370.
  20. X. Li, P. Liang, Z. Li, Automatic Identification of Decisions from the Hibernate Developer Mailing List, in: Proceedings of the 24th International Conference on Evaluation and Assessment in Software Engineering (EASE’20), 2020, pp. 51-60.
  21. R. Mo, S. Wei, T. Hu, Z. Li, Detecting and Modeling Method-level Hotspots in Architecture Design Flaws, in: Proceedings of the 32th International Conference on Software Engineering and Knowledge Engineering (SEKE’20), 2020, pp. 111-116.
  22. X. Tang, Z. Wang, J. Qi, Z. Li*, Improving Code Generation From Descriptive Text By Combining Deep Learning and Syntax Rules, in: Proceedings of the 31th International Conference on Software Engineering and Knowledge Engineering (SEKE’19), 2019, pp. 385-390.
  23. D. Zhang, B. Li, Z. Li*, P. Liang, A Preliminary Investigation of Self-Admitted Refactorings in Open Source Software, in: Proceedings of the 30th International Conference on Software Engineering and Knowledge Engineering (SEKE’18), 2018, pp. 165-168.
  24. C. Cheng, B. Li, Z. Li*, P. Liang, Automatic Detection of Public Development Projects in Large Open Source Ecosystems: An Exploratory Study on GitHub, in: Proceedings of the 30th International Conference on Software Engineering and Knowledge Engineering (SEKE’18), 2018, pp. 193-198.
  25. Z. Li, P. Liang, B. Li, Relating Alternate Modifications to Defect Density in Software Development, in: Proceedings of the 39th International Conference on Software Engineering Companion (ICSE’17), 2017, pp. 308-310.
  26. X. He, P. Avgeriou, P. Liang, Z. Li, Technical Debt in MDE: A Case Study on GMF/EMF-Based Projects, in: Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems (MODELS’16), 2016, pp. 162-172.
  27. Z. Li, P. Liang, P. Avgeriou, Architectural technical debt identification based on architecture decisions and change scenarios, in: Proceedings of the 12th Working IEEE/IFIP Conference on Software Architecture (WICSA’15), 2015, pp. 65-74.
  28. M. Shahin, P. Liang, Z. Li, Do Architectural Design Decisions Improve the Understanding of Software Architecture? Two Controlled Experiments, in: Proceedings of the 22nd International Conference on Program Comprehension (ICPC’14), 2014, pp. 3-13.
  29. Z. Li, P. Liang, P. Avgeriou, N. Guelfi, A. Ampatzoglou, An Empirical Investigation of Modularity Metrics for Indicating Architectural Technical Debt, in: Proceedings of the 10th International Conference on the Quality of Software Architectures (QoSA’14), 2014, pp. 119-128.
  30. M. Shahin, P. Liang, Z. Li, Recovering Software Architectural Knowledge from Documentation using Conceptual Model, in: Proceeding of the 25th International Conference on Software Engineering and Knowledge Engineering (SEKE’13), 2013, pp. 556-561.
  31. M. Shahin, P. Liang, Z. Li, Architectural design decision visualization for architecture design: preliminary results of a controlled experiment, Proceedings of the 5th European Conference on Software Architecture: Companion Volume, 2011, pp. 5-12.

Book Chapters

  1. Z. Li, P. Liang, P. Avgeriou, Architecture viewpoints for documenting architectural technical debt, in: I. Mistrik, R. Soley, N. Ali, J. Grundy, B. Tekinerdogan (Eds.) Software Quality Assurance in Large Scale and Complex Software-intensive Systems, Elsevier, 2015, pp. 85-132.
  2. Z. Li, P. Liang, P. Avgeriou, Architectural debt management in value-oriented architecting, in: I. Mistrik, R. Bahsoon, R. Kazman, Y. Zhang (Eds.) Economics-Driven Software Architecture, Elsevier, 2014, pp. 183-204.