Publication

(#co-first author, *corrsponding author)

    --- 2024 ---


  • Yufan Cai, Zhe Hou, David Sanan, Xiaokun Luan, Yun Lin, Jun Sun, and Jin Song Dong. Automated Program Refinement: Guide and Verify Code Large Language Model with Refinement Calculus (POPL 2024). [pdf]
  • Yifan Liao#, Ming Xu#, Yun Lin*, Xiwen Teoh, Xiaofei Xie, Ruitao Feng, Frank Liauw, Hongyu Zhang, and Jin Song Dong. Detecting and Explaining Anomalies Caused by Web Tamper Attacks via Building Consistency-based Normality (ASE 2024). [pdf]
  • Jinhao Dong, Jun Sun, Yun Lin, Yedi Zhang, Murong Ma, Jin Song Dong, and Dan Hao. Revisiting the Conflict-Resolving Problem from a Semantic Perspective (ASE 2024). [pdf]
  • Ruofan Liu, Yun Lin*, Xiwen Teoh, Gongshen Liu, Zhiyong Huang, and Jin Song Dong. Less Defined Knowledge and More True Alarms: Reference-based Phishing Detection without a Pre-defined Reference List (USENIX Security 2024). [pdf]
  • Xiwen Teoh, Yun Lin*, Ruofan Liu, Zhiyong Huang, and Jin Song Dong. PhishDecloaker: Detecting CAPTCHA-cloaked Phishing Websites via Hybrid Vision-based Interactive Models (USENIX Security 2024). [pdf]
  • Chenyan Liu#, Yufan Cai#, Yun Lin*, Yuhuan Huang, Yunrui Pei, Bo Jiang, Ping Yang, Jin Song Dong, and Hong Mei. CoEdPilot: Recommending Code Edits with Learned Prior Edit Relevance, Project-wise Awareness, and Interactive Nature (ISSTA 2024). [pdf]
  • Xiezhi Song, Yijian Wu, Shuning Liu, Bihuan Chen, Yun Lin, and Xin Peng. Extracting Critical Changes for Real-World Bugs with Dependency-Sensitive Delta Debugging (ISSTA 2024). [pdf]
  • Yudai Pan, Jun Liu, Tianzhe Zhao, Lingling Zhang, Yun Lin, and Jin Song Dong. A Symbolic Rule Integration Framework with Logic Transformer for Inductive Relation Prediction (WWW 2024). [pdf]

    --- 2023 ---


  • Yufan Cai, Yun Lin*, Chenyan Liu, Jinglian Wu, Yifan Zhang, Yiming Liu, Yeyun Gong, and Jin Song Dong. On-the-Fly Adapting Code Summarization on Trainable Cost-Effective Language Models (NeurIPS 2023). [pdf]
  • Zhaoyu Liu, Kan Jiang, Zhe Hou, Yun Lin, and Jin Song Dong. Insight Analysis for Tennis Strategy and Tactics (ICDM 2023). [pdf]
  • Xianglin Yang, Yun Lin*, Yifan Zhang, Linpeng Huang, Jin Song Dong, and Hong Mei. DeepDebugger: An Interactive Time-Travelling Debugging Approach for Deep Classifiers (FSE 2023). [pdf]
  • Xiaoxue Ren, Xinyuan Ye, Yun Lin, Zhenchang Xing, Shuqing Li, Michael R. Lyu. API-Knowledge Aware Search-based Software Testing: Where, What and How (FSE 2023). [pdf]
  • Mengyue Liu, Yun Lin*, Jun Liu*, Bohao Liu, Qinghua Zheng, and Jin Song Dong. B2-Sampling: Fusing Balanced and Biased Sampling for Graph Contrastive Learning (KDD 2023). [pdf]
  • Jihong Wang, Minnan Luo, Jundong Li, Yun Lin, Jin Song Dong, and Qinghua Zheng. Empower Post-hoc Graph Explanations with Information Bottleneck: A Pre-training and Fine-tuning Perspective (KDD 2023). [pdf]
  • Ruofan Liu, Yun Lin*, Yifan Zhang, Penn Han Lee, and Jin Song Dong. Knowledge Expansion and Counterfactual Interaction for Reference-Based Phishing Detection (USENIX Security 2023). [pdf]
  • Xiaoning Ren, Yun Lin*, Yinxing Xue*, Ruofan Liu, Jun Sun, Zhiyong Feng and Jin Song Dong. DeepArc: Modularizing Neural Networks for the Model Maintenance (ICSE 2023). [pdf]

    • --- 2022 ---


  • Xiaonan Li, Daya Guo, Yeyun Gong, Yun Lin, Yelong Shen, Xipeng Qiu, Daxin Jiang, Weizhu Chen and Nan Duan. Soft-Labeled Contrastive Pre-Training for Function-Level Code Representation (EMNLP 2022, Findings). [pdf]
  • Ruofan Liu, Yun Lin*, Xianglin Yang, and Jin Song Dong. Debugging and Explaining Metric Learning Approaches: An Influence Function Based Perspective (NeurIPS 2022). [pdf]
  • Xuezhi Song, Yun Lin*, Yijian Wu, Yifan Zhang, Xin Peng, Jin Song Dong, and Hong Mei. RegMiner: Mining Replicable Regression Dataset from Code Repositories (FSE 2022, demo track). [pdf] (to appear)
  • Yan Xiao, Yun Lin*, Ivan Beschastnikh, Chagnsheng Sun, David Rosenblum, and Jin Song Dong. Repairing Failure-inducing Inputs with Input Reflection (ASE 2022). [pdf]
  • Siqi Li, Xiaofei Xie, Yun Lin*, Yuekang Li, Ruitao Feng, Xiaohong Li, Weimin Ge, and Jin Song Dong. Deep Learning for Coverage-Guided Fuzzing: How Far Are We? (TDSC 2022). [pdf]
  • Yan Xiao, Ivan Beschastnikh, Yun Lin*, Rajdeep Singh Hundal, Xiaofei Xie, David Rosenblum, and Jin Song Dong. Self-Checking Deep Neural Networks for Anomalies and Adversaries in Deployment (TDSC 2022). [pdf]
  • Huasong Meng, Guangdong Bai, Sin Gee Teo, Zhe Hou, Yan Xiao, Yun Lin, and Jin Song Dong. Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective (TDSC 2022). [pdf]
  • Xuezhi Song, Yun Lin*, Siang Hwee Ng, Yijian Wu, Xin Peng, Jin Song Dong and Hong Mei. RegMiner: Towards Constructing a Large Regression Dataset from Code Evolution History (ISSTA 2022). [pdf, video1, video2, more details]
  • Xianglin Yang, Yun Lin*, Ruofan Liu, and Jin Song Dong. Temporality Spatialization: A Scalable and Faithful Time-Travelling Visualization for Deep Classifier Training (IJCAI 2022). [pdf, video, more details]
  • Yao Zhang, Xiaofei Xie, Yi Li, Yun Lin, Sen Chen, Yang Liu, and Xiaohong Li. Demystifying Performance Regressions in String Solvers (TSE 2022). [pdf]
  • Ruofan Liu, Yun Lin*, Xianglin Yang, Siang Hwee Ng, Dinil Mon Divakaran, and Jin Song Dong. Inferring Phishing Intention via Webpage Appearance and Dynamics: A Deep Vision Based Approach (USENIX Security 2022). [pdf, video, more details]
  • Yunkai Liang, Yun Lin*, Xuezhi Song, Jun Sun, Zhiyong Feng, and Jin Song Dong. gDefect4DL: A Dataset of General Real-World Deep Learning Program Defects (ICSE 2022, demo track). [pdf, video, more details]
  • Xianglin Yang#, Yun Lin#*, Ruofan Liu, Zhenfeng He, Chao Wang, Jin Song Dong, and Hong Mei. DeepVisualInsight: Time-Travelling Visualization for Spatio-Temporal Causality of Deep Classification Training (AAAI 2022, Oral Presentation) [pdf, video, more details].

    • --- 2021 ---


  • Yun Lin, You Sheng Ong, Jun Sun, Gordon Fraser, Jin Song Dong. Graph-based Seed Object Synthesis for Search-Based Unit Testing (ESEC/FSE 2021), to appear [pdf, video, more details].
  • Yun Lin, Ruofan Liu, Dinil Mon Divakaran, Jun Yang Ng, Qing Zhou Chan, Yiwen Lu, Yuxuan Si, Fan Zhang, Jin Song Dong. Phishpedia: A Hybrid Deep Learning Based Approach to Visually Identify Phishing Webpages (USENIX Security 2021), to appear [pdf, video, code, more details].
  • Yan Xiao, Ivan Beschastnikh, David S. Rosenblum, Changsheng Sun, Sebastian Elbaum, Yun Lin, Jin Song Dong. Self-Checking Deep Neural Networks in Deployment (ICSE 2021), to appear. [pdf]
  • Qian Li, Yong Qi, Qingquan Hu, Yun Lin, and Jin Song Dong. Adversarial Adaptive Neighborhood with Feature Importance-Aware Convex Interpolation (TIFS 2021), to appear. [pdf]

    • --- 2020 ---


  • Yinxing Xue, Mingliang Ma, Yun Lin*, Yulei Sui, Jiaming Ye, and Tianyong Peng. Cross-Contract Static Analysis for Detecting Practical Reentrancy Vulnerabilities in Smart Contracts (ASE 2020) [pdf].
  • Yun Lin, Jun Sun, Gordon Fraser, Ziheng Xiu, Ting Liu, and Jin Song Dong. Recovering Fitness Gradients for Interprocedural Boolean Flags in Search-Based Testing (ISSTA 2020), pp. 440--451 [pdf, video, more details].
  • Duy Tai Nguyen, Long H. Pham, Jun Sun, Yun Lin, and Minh Quang Tran. sFuzz: An Efficient Adaptive Fuzzer for Solidity Smart Contracts (ICSE 2020), to appear. [pdf]

    • --- 2019 ---


  • Haijun Wang#, Yun Lin#*, Zijiang Yang, Jun Sun, Yang Liu, Jin Song Dong, Qinghua Zhen, and Ting Liu. Explaining Regressions via Alignment Slicing and Mending (TSE 2019). [pdf, video, more details]
  • Haijun Wang, Xie Xiaofei, Shang-Wei Lin, Yun Lin, Yuekang Li, Shengchao Qin, Yang Liu and Ting Liu. Locating Vulnerabilities in Binaries via Memory Layout Recovering. The 27th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2019), pp. 718-728. [pdf]
  • Pardeep Kumar, Yun Lin, Guangdong Bai, Andrew Parvard, Andrew Martin, and Jinsong Dong. Smart Grid Metering Networks: A Survey on Security, Privacy and Open Research Issues. IEEE Communications Surveys and Tutorials (COMST 2019, IF: 20.34).

    • --- 2018 (and before) ---


  • Yun Lin, Jun Sun, Lyly Tran, Guangdong Bai, Haijun Wang, and Jin Song Dong. Break the Dead End of Dynamic Slicing: Localizing Data and Control Omission Bug. (ASE 2018), pp. 509-519. [pdf, more details]
  • Xinyu Wang, Jun Sun, Zhenbang Chen, Peixin Zhang, Jingyi Wang, and Yun Lin. Towards Optimal Concolic Testing. The 40th International Conference on Software Engineering (ICSE 2018, Distinguished Paper Award), pp. 291-302. [pdf]
  • Yun Lin, Guozhu Meng, Yinxing Xue, Zhenchang Xing, Jun Sun, Xin Peng, Yang Liu, Wenyun Zhao, and Jin Song Dong. Mining Implicit Design Templates for Actionable Code Reuse. (ASE 2017), pp. 394-404. [pdf, more details]
  • Yun Lin, Jun Sun, Yinxing Xue, Yang Liu, and Jin Song Dong. Feedback-based Debugging (ICSE 2017), pp. 393-403. [pdf, more details]
  • Yun Lin, Xin Peng, Yuanfang Cai, Danny Dig, Diwen Zheng, and Wenyun Zhao. Interactive and Guided Architectural Refactoring with Search-Based Recommendation. The 24th ACM SIGSOFT International Symposium on the Foundations of Software Engineering (FSE 2016), pp. 535-546. [pdf, more details]
  • Yun Lin, Xin Peng, Zhenchang Xing, Diwen Zheng, and Wenyun Zhao. Clone-Based and Interactive Recommendation for Modifying Pasted Code. The 10th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering (ESEC/FSE 2015), pp. 520-531. [pdf, more details]
  • Yun Lin, Zhenchang Xing, Yinxing Xue, Yang Liu, Xin Peng, Jun Sun, and Wenyun Zhao. Detecting Differences across Multiple Instances of Code Clones. The 36th International Conference on Software Engineering (ICSE 2014), pp. 164-174. [pdf, more details]
  • Yun Lin, Zhenchang Xing, Xin Peng, Yang Liu, Jun Sun, Wenyun Zhao, and Jinsong Dong. Clonepedia: Summarizing Code Clones by Common Syntactic Context for Software Maintenance. The 30th International Conference on Software Maintenance and Evolution (ICSME 2014), pp. 341-350. [pdf, more details]