Projects

1. Optimization and Evolutionary Algorithms

• Meng Li, Jun Zhou, Lu Yu, Xiaoguang Huang, Yongfeng Gu, Yi Ding, Hao Ding, and Longfei Li. A Rule-based Decision System for Financial Applications. IEEE 39th International Conference on Data Engineering (ICDE 2023) [Link] New
• Yongfeng Gu, Yuxuan Zhou, Zhilei Chen, Hao Ding, Fan Jia, Shiping Wang, Hua Wu, and Jun Zhou. Exploring the Impact of Grouping Strategies on Cooperative Co-evolutionary Algorithms for Solving the Advertising Budget Allocation Problem. IEEE International Conference on Software Security and Reliability (QRS 2022) [Link]
• Yongfeng Gu, Hao Ding, Kecai Gu, Xiaoguang Huang, Hua Wu, and Jun Zhou. A Comparison Analysis of Constraint Handling Techniques on Rule Selection Problem in Credit Risk Assessment: An Industrial View. IEEE International Conference on Software Security and Reliability (QRS 2022) [Link]
• Yongfeng Gu, Yue Ning, Kecai Gu, Daohong Jian, Zhou Xu, Hua Wu, and Jun Zhou. A Self-adaptive Indicator Selection Approach for Solving Credit Risk Assessment. Computers, Software & Applications in an Uncertain World (COMPSAC 2022) [Link]
• Yongfeng Gu, Hao Ding, Kecai Gu, Runsheng Gan, Xiaoguang Huang, Yanming Fang, Zhigang Hua, Hua Wu, Jifeng Xuan, and Jun Zhou. Heuristic Strategies for Solving the Combinatorial Optimization Problem in Real-World Credit Risk Assessment. Annual Conference on Genetic and Evolutionary Computation (GECCO 2022) [Link]
• Yongfeng Gu, Hao Ding, Hua Wu, and Jun Zhou. Opposite Learning and Multi-Migrating Strategy-Based Self-Organizing Migrating Algorithm with the Convergence Monitoring Mechanism. Annual Conference on Genetic and Evolutionary Computation (GECCO 2022 Competition) [Link]
• Hao Ding, Yongfeng Gu, Hua Wu, and Jun Zhou. NL-SOMA-CLP for Real Parameter Single Objective Bound Constrained Optimization. Annual Conference on Genetic and Evolutionary Computation (GECCO 2022 Competition) [Link]

2. Software Crash Analysis

Software crash refers to an unexpected termination of software systems. Developers spend much time and effort in dealing with software crashes. In this project, we mainly focus on crash reproduction, localization, repair, and other relative tasks.

• Yongfeng Gu, Ping Ma, Xiangyang Jia, He Jiang, and Jifeng Xuan. Progress on software crash research. SCIENTIA SINICA Informationis, 2019, 49(11): 1383-1398 [Link]
• Yongfeng Gu, Jifeng Xuan, Hongyu Zhang, Lanxin Zhang, Qingna Fan, Xiaoyuan Xie, and Tieyun Qian. Does the fault reside in a stack trace? Assisting crash localization by predicting crashing fault residence. Journal of Systems and Software, 2019, 148(1): 88-104 [Link]
• Yongfeng Gu, Jifeng Xuan, and Tieyun Qian. Automatic reproducible crash detection. International Conference on Software Analysis, Testing and Evolution (SATE 2016) [Link]

3. System Performance Analysis

Modern software systems often provide tons of configuration options to extend flexibility and functionality. However, the daily-increasing number of options brings challenges in two vital tasks: configuration-related bug detection and system performance optimization. In this project, we tried to explore solutions to solve or assist with the above tasks.

• Yongfeng Gu, Yuntianyi Chen, Xiangyang Jia, and Jifeng Xuan. Multi-Objective Configuration Sampling for Performance Ranking in Configurable Systems. Asian-Pacific Software Engineering Conference (APSEC 2019) [Link]
• Yuntianyi Chen, Yongfeng Gu, Lulu He, and Jifeng Xuan. Regression Models for Performance Ranking of Configurable Systems: A Comparative Study. International Workshop on SOFL + MSVL for Reliability and Security (SOFL+MSVL 2019) [Link]
• Jifeng Xuan, Yongfeng Gu, Zhilei Ren, Xiangyang Jia, and Qingna Fan. Genetic Configuration Sampling: Learning a Sampling Strategy for Fault Detection of Configurable Systems. Annual Conference on Genetic and Evolutionary Computation (GECCO 2018) [Link]