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Dr. Xiaoxue Ma
馬笑雪 PhD Graduate (2024) 2024Now Senior Lecturer, Department of Electronic Engineering and Computer Science, School of Science and Technology, Hong Kong Metropolitan University, Hong Kong
Personal website ↗About
Dr. Xiaoxue Ma is a PhD graduate in the Department of Computer Science, City University of Hong Kong.
Now Senior Lecturer, Department of Electronic Engineering and Computer Science, School of Science and Technology, Hong Kong Metropolitan University, Hong Kong.
Research Interests
Publications (31)
- Where Do Expectations Diverge? an Empirical Analysis of Software Engineering Graduate Preparedness in Industry.
- UniAda: Universal Adaptive Multi-objective Adversarial Attack for End-to-End Autonomous Driving Systems.
- Understanding How Enterprises Adopt the Model Context Protocol for LLM-Driven Software Engineering.
- Teaching Software Engineering with LLM and MCP Integration: From Classroom to Industry Practice.
- R2Code: A Self-Reflective LLM Framework for Requirements-to-Code Traceability.
- NFR-to-Code Traceability in a Blockchain-IoT System: An Empirical Study.
- Industrial log analysis revisited: A task-oriented evaluation of parsing and anomaly detection under real-world constraints.
- Designing Psychologically Safe AI Tutors for Students: An Emotion-Aware Post-Hoc Intervention for LLM-Assisted Learning.
- Artifact-Constrained Agentic Testing for Black-Box System Testing under Actuarial and Regulatory Constraints.
- An Empirical Study of Perceptions of General LLMs and Multimodal LLMs on Hugging Face.
- A Unified Benchmark for Out-of-Distribution Detection for Autonomous Driving Systems.
- Practitioners' Expectations on Log Anomaly Detection.
- PerProb: Indirectly Evaluating Memorization in Large Language Models.
- On the value of imbalance loss functions in enhancing deep learning-based vulnerability detection.
- On the Influence of Data Resampling for Deep Learning-Based Log Anomaly Detection: Insights and Recommendations.
- Exposing and Defending Membership Leakage in Vulnerability Prediction Models.
- A Comprehensive Study of Bugs in Modern Distributed Deep Learning Systems.
- SimAC: simulating agile collaboration to generate acceptance criteria in user story elaboration.
- Practitioners' Expectations on Code Smell Detection.
- LLM-Based Class Diagram Derivation from User Stories with Chain-of-Thought Promptings.