| 2024 | CSCWD | KEWS: A KPIs-Based Evaluation Framework of Workload Simulation On Microservice System. | Pengsheng Li, Qingfeng Du, Shengjie Zhao |
| 2024 | CSCWD | Advancing Root Cause Analysis in Cloud-native System with Knowledge Graph Path Embedding Translation. | Pengsheng Li, Qingfeng Du, Shengjie Zhao, Pei Fang |
| 2024 | ICASSP | Semi-Supervised Metrics-Based Self-Training Root Cause Analysis for Cloud-Native Systems with Class-Imbalanced Data. | Ying Huang, Qingfeng Du, Yongqi Han, Cheng He, Fulong Tian |
| 2023 | APSEC | LogFold: Enhancing Log Anomaly Detection Through Sequence Folding and Reconstruction. | Xiaonan Shi, Rui Li, Qingfeng Du, Cheng He, Fulong Tian |
| 2023 | DEXA | Trace-Based Anomaly Detection with Contextual Sequential Invocations. | Qingfeng Du, Liang Zhao, Fulong Tian, Yongqi Han |
| 2021 | COMPSAC | A Requirement-based Regression Test Selection Technique in Behavior-Driven Development. | Jincheng Xu, Qingfeng Du, Xiaojun Li |
| 2021 | DEXA | Log-Based Anomaly Detection with Multi-Head Scaled Dot-Product Attention Mechanism. | Qingfeng Du, Liang Zhao, Jincheng Xu, Yongqi Han, Shuangli Zhang |
| 2021 | SMC | Predicting Cutterhead Torque for TBM based on Different Characteristics and AGA-Optimized LSTM-MLP. | Shuangli Zhang, Qingfeng Du, Sicheng Zhao |
| 2021 | SEKE | Model-Agnostic Local Explanations with Genetic Algorithms for Text Classification. | Qingfeng Du, Jincheng Xu |
| 2021 | SEKE | Towards a Better Understanding of Gradient-Based Explanatory Methods in NLP. | Qingfeng Du, Jincheng Xu |
| 2020 | APSEC | Software Defect Prediction and Localization with Attention-Based Models and Ensemble Learning. | Tianhang Zhang, Qingfeng Du, Jincheng Xu, Jiechu Li, Xiaojun Li |
| 2020 | ECAI | On the Interpretation of Convolutional Neural Networks for Text Classification. | Jincheng Xu, Qingfeng Du |
| 2020 | KSEM | Document-Improved Hierarchical Modular Attention for Event Detection. | Yiwei Ni, Qingfeng Du, Jincheng Xu |
| 2019 | COMPSAC | Short-Term Performance Metrics Forecasting for Virtual Machine to Support Anomaly Detection Using Hybrid ARIMA-WNN Model. | Juan Qiu, Qingfeng Du, Wei Wang, Kanglin Yin, Liang Chen |
| 2019 | HPCC | A Deep Investigation into fastText. | Jincheng Xu, Qingfeng Du |
| 2018 | HPCC | A Learning-Based Adjustment Model with Genetic Algorithm of Function Point Estimation. | Jiaqi Liu, Qingfeng Du, Jincheng Xu |
| 2018 | ICA3PP | An Approach of Collecting Performance Anomaly Dataset for NFV Infrastructure. | Qingfeng Du, Yu He, Tiandi Xie, Kanglin Yin, Juan Qiu |
| 2018 | ICA3PP | Anomaly Detection and Diagnosis for Container-Based Microservices with Performance Monitoring. | Qingfeng Du, Tiandi Xie, Yu He |
| 2018 | ICANN | Performance Anomaly Detection Models of Virtual Machines for Network Function Virtualization Infrastructure with Machine Learning. | Juan Qiu, Qingfeng Du, Yu He, YiQun Lin, Jiaye Zhu, Kanglin Yin |
| 2018 | SEKE | Helpful or Not? An investigation on the feasibility of identifier splitting via CNN-BiLSTM-CRF. | Jiechu Li, Qingfeng Du, Kun Shi, Yu He, Xin Wang, Jincheng Xu |