NOTICE: The electronic versions of the papers listed on this webpage are provided for personal use. Copyright is owned by the respective publishers or persons, and should be included explicitly in any distribution of the papers. You may also find links to my publications here: [Google Scholar][DBLP] (results may not be complete).

Conference/Symposium/Workshop Papers

  1. [ASE 2024, CORE-A*/CCF-A] Yujia Fan, Sinan Wang, Zebang Fei, Yao Qin, Huaxuan Li, and Yepang Liu. Can Cooperative Multi-Agent Reinforcement Learning Boost Automatic Web Testing? An Exploratory Study. In the 39th IEEE/ACM International Conference on Automated Software Engineering, October 2024, Sacremento, California, United States, to appear.

  2. [ASE 2024 Demonstration] Yige Chen, Sinan Wang, Yida Tao, and Yepang Liu. Model-based GUI Testing for HarmonyOS Apps. In the Demonstration Track of the 39th IEEE/ACM International Conference on Automated Software Engineering, October 2024, Sacramento, California, United States, to appear.

  3. [ISSTA 2024, CORE-A*/CCF-A] Hao Guan, Guangdong Bai, and Yepang Liu. Large Language Models Can Connect the Dots: Exploring Model Optimization Bugs with Domain Knowledge-aware Prompts. In the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis, September 2024, Vienna, Austria, to appear. [acceptance rate: 20.6%]

  4. [ICSME 2024, CORE-A/CCF-B] Siyi Wang, Sinan Wang, Yujia Fan, Xiaolei Li, and Yepang Liu. Leveraging Large Vision-Language Model for Better Automatic Web GUI Testing. In the 40th IEEE International Conference on Software Maintenance and Evolution, October 2024, Flagstaff, AZ, USA, to appear. [acceptance rate: 26%]

  5. [ICSME 2024, CORE-A/CCF-B] Junfeng Chen, Kevin Li, Yifei Chen, Lili Wei, and Yepang Liu. Demystifying Device-specific Compatibility Issues in Android Apps. In the 40th IEEE International Conference on Software Maintenance and Evolution, October 2024, Flagstaff, AZ, USA, to appear. [pdf][acceptance rate: 26%]

  6. [FSE 2024, CORE-A*/CCF-A] Ying Xiao, Jie M. Zhang, Yepang Liu, Mohammad Reza Mousavi, Sicen Liu, and Dingyuan Xue. MirrorFair: Fixing Fairness Bugs in Machine Learning Software via Counterfactual Predictions. In the ACM International Conference on the Foundations of Software Engineering, July 2024, Porto de Galinhas, Brazil, to appear. [pdf]

  7. [FSE 2024, CORE-A*/CCF-A] Shuqing Li, Cuiyun Gao, Jianping Zhang, Yujia Zhang, Yepang Liu, Jiazhen Gu, Yun Peng, and Michael R. Lyu. Less Cybersickness, Please: Demystifying and Detecting Stereoscopic Visual Inconsistencies in Virtual Reality Applications. In the ACM International Conference on the Foundations of Software Engineering, July 2024, Porto de Galinhas, Brazil, to appear. [pdf]

  8. [TASE 2024, CCF-C] Pengkun Jiang, Sinan Wang, and Yepang Liu. Tree-Based Synthesis of Web Test Sequences From Manual Actions. In the 18th Theoretical Aspects of Software Engineering Conference, Guiyang, China, to appear.

  9. [ICSE 2024, CORE-A*/CCF-A] Dinghua Wang, Shuqing Li, Guanping Xiao, Yepang Liu, Yulei Sui, Pinjia He, and Michael R. Lyu. An Exploratory Investigation of Log Anomalies in Unmanned Aerial Vehicles. In the 46th International Conference on Software Engineering, April 2024, Lisbon, Portugal, to appear.

  10. [S&P 2024, CORE-A*/CCF-A] Wuqi Zhang, Zhuo Zhang, Qingkai Shi, Lu Liu, Lili Wei, Yepang Liu, Xiangyu Zhang, and Shing-Chi Cheung. Nyx: Detecting Exploitable Front-Running Vulnerabilities in Smart Contracts. In the 45th IEEE Symposium on Security and Privacy, May 2024, San Francisco, California, USA. [pdf]

  11. [APSEC 2023, CORE-B/CCF-C] Siqi Zhou, Xian Zhan, Linlin Li, and Yepang Liu. Effective Anomaly Detection for Microservice Systems with Real-Time Feature Selection. In the 30th Asia-Pacific Software Engineering Conference, December 2023, Seoul, South Korea, pp. 101-110. [pdf]

  12. [ESEC/FSE 2023, CORE-A*/CCF-A] Jun Wang, Guanping Xiao, Shuai Zhang, Huashan Lei, Yepang Liu, and Yulei Sui. Compatibility Issues in Deep Learning Systems: Problems and Opportunities. In the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, December 2023, San Francisco, California, United States, pp. 476-488. [pdf]

  13. [ESEC/FSE 2023, CORE-A*/CCF-A] Shangwen Wang, Gengming Yang, Bo Lin, Zhensu Sun, Ming Wen, Yepang Liu, Li Li, Tegawende Bissyande, and Xiaoguang Mao. Natural Language to Code: How Far are We? In the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, December 2023, San Francisco, California, United States, pp. 375-387. [pdf]

  14. [ESEC/FSE 2023, CORE-A*/CCF-A] Bo Lin, Shangwen Wang, Zhongxin Liu, Yepang Liu, Xin Xia, and Xiaoguang Mao. CCT5: A Code-Change-Oriented Pre-Trained Model. In the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, December 2023, San Francisco, California, United States, pp. 1509-1521. [pdf][artifacts]

  15. [ISSRE 2023, CORE-A/CCF-B] Huashan Lei, Shuai Zhang, Jun Wang, Guanping Xiao, Yepang Liu, and Yulei Sui. Why Do Deep Learning Projects Differ in Compatible Framework Versions? An Exploratory Study. In the 34th IEEE International Symposium on Software Reliability Engineering, October 2023, Florence, Italy, pp. 509-520. [pdf]

  16. [QRS 2023 Short Paper] Jiacheng Li, Kerui Huang, Sinan Wang, and Yepang Liu. Towards the Adoption and Adaptation of the AndroidX Library: An Empirical Study. In the 23rd IEEE International Conference on Software Quality, Reliability, and Security, October 2023, Chiang Mai, Thailand, pp. 418-427. [pdf]

  17. [QRS 2023 Workshop] Jinrun Liu, Xinyu Tang, Linlin Li, Panpan Chen, and Yepang Liu. ChatGPT vs. Stack Overflow: An Exploratory Comparison of Programming Assistance Tools. In the Companion Proceedings of the 23rd IEEE International Conference on Software Quality, Reliability, and Security, October 2023, Chiang Mai, Thailand, pp. 364-373. [pdf]

  18. [OOPSLA 2023, CORE-A/CCF-A] Shangwen Wang, Bo Lin, Zhensu Sun, Ming Wen, Yepang Liu, Yan Lei, and Xiaoguang Mao. Two Birds with One Stone: Boosting Code Generation and Code Search via Generative Adversarial Network. In the 2023 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications, October 2023, Cascais, Portugal, 30 pages. [pdf]

  19. [DSA 2023] Yujia Fan, Siyi Wang, Sinan Wang, Yepang Liu, Guoyao Wen, and Qi Rong. A Comprehensive Evaluation of Q-Learning Based Automatic Web GUI Testing. In the 10th International Conference on Dependable Systems and Their Applications, August 2023, Tokyo, Japan, to appear.

  20. [Internetware 2023, CCF-C] Lei Liu, Sinan Wang, Yepang Liu, Jinliang Deng, and Sicen Liu. DRIFT: Fine-Grained Prediction of the Co-Evolution of Production and Test Code via Machine Learning. In the 14th Asia-Pacific Symposium on Internetware, to appear. [acceptance rate: 40%][pdf]

  21. [ISSTA 2023, CORE-A/CCF-A] Jiajun Hu, Lili Wei, Yepang Liu, and Shing-Chi Cheung. wTest: WebView-Oriented Testing for Android Applications. In the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis, July 2023, pp. 992-1004. [acceptance rate: 28.8%][pdf]

  22. [ISSTA 2023, CORE-A/CCF-A] Linlin Li, Ruifeng Wang, Xian Zhan, Ying Wang, Cuiyun Gao, Sinan Wang, and Yepang Liu. What You See Is What You Get? It Is Not the Case! Detecting Misleading Icons for Mobile Applications. In the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis, July 2023, pp. 538-550. [acceptance rate: 28.8%][pdf]

  23. [ISSTA 2023, CORE-A/CCF-A] Huaxun Huang, Chi Xu, Ming Wen, Yepang Liu, and Shing-Chi Cheung. ConfFix: Repairing Configuration Compatibility Issues in Android Apps. In the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis, July 2023, pp. 514-525. [acceptance rate: 28.8%][pdf]

  24. [WWW 2023, CORE-A*/CCF-A] Yanjie Zhao, Tianming Liu, Haoyu Wang, Yepang Liu, John Grundy, and Li Li. Are Mobile Advertisements in Compliance with App’s Age Group? In the ACM Web Conference, pp. 3132-3141, April 2023, Austin, TX, USA. [acceptance rate: 19.2%][pdf]

  25. [ICST 2023, CORE-A/CCF-C] Jiayuan Liang, Sinan Wang, Xiangbo Deng, and Yepang Liu. RIDA: Cross-App Record and Replay for Android. In the 16th IEEE International Conference on Software Testing, Verification and Validation, pp. 246-257, April 2023, Dublin, Ireland. [acceptance rate: 28.9%][pdf]

  26. [ICSE 2023, CORE-A*/CCF-A] Jiwei Yan, Miaomiao Wang, Yepang Liu, Jun Yan, and Long Zhang. Locating Framework-specific Crashing Faults with Compact and Explainable Candidate Set. In the 45th International Conference on Software Engineering, pp. 172-183, May 2023, Melbourne, Australia. [acceptance rate: 26.7%][pdf]

  27. [ICSE 2023, CORE-A*/CCF-A] Hao Guan, Ying Xiao, Jiaying Li, Yepang Liu, and Guangdong Bai. A Comprehensive Study of Real-World Bugs in Machine Learning Model Optimization. In the 45th International Conference on Software Engineering, pp. 147-158, May 2023, Melbourne, Australia. [acceptance rate: 26.7%][pdf]

  28. [ICSE 2023, CORE-A*/CCF-A] Kaifa Zhao, Xian Zhan, Le Yu, Shiyao Zhou, Hao Zhou, Xiapu Luo, Haoyu Wang, and Yepang Liu. Demystifying Privacy Policy of Third-Party Libraries in Mobile Apps. In the 45th International Conference on Software Engineering, pp. 172-183, May 2023, Melbourne, Australia. [acceptance rate: 26.7%]

  29. [ASE 2022, CORE-A*/CCF-A] Jiwei Yan, Shixin Zhang, Yepang Liu, Xi Deng, Jun Yan, and Jian Zhang. A Comprehensive Evaluation of Android ICC Resolution Techniques. In the 37th IEEE/ACM International Conference on Automated Software Engineering, pp. 1-13, October 2022, Oakland Center, Michigan, USA. [acceptance rate: 18.8%][pdf]

  30. [ISSRE 2022, CORE-A/CCF-B] Yue Liu, Chakkrit Tantithamthavorn, Li Li, and Yepang Liu. Explainable AI for Android Malware Detection: Towards Understanding Why the Models Perform So Well? In the 33rd International Symposium on Software Engineering Reliability, pp. 169-180, November 2022, Charlotte, NC, USA. [acceptance rate: 29%][pdf]

  31. [MICRO 2022, CORE-A/CCF-A] Xueliang Li, Zhuobin Shi, Junyang Chen, and Yepang Liu. Realizing Emotional Interactions to Learn User Experience and Guide Energy Optimization for Mobile Architectures. In the 55th IEEE/ACM International Symposium on Microarchitecture, pp. 868-884, October 2022, Chicago, IL, USA. [acceptance rate: 22%][paper]

  32. [Internetware 2022, CCF-C] Chenyu Zhou, Xian Zhan, Linlin Li, and Yepang Liu. Automatic Maturity Rating for Android Apps. In the 13th Asia-Pacific Symposium on Internetware, pp. 16-27, June 2022, Hohhot, China. [acceptance rate: 43.5%][pdf]

  33. [ICSE 2022 Demo] Jiwei Yan, Shixin Zhang, Yepang Liu, Jun Yan, and Jian Zhang. ICCBot: Fragment-Aware and Context-Sensitive ICC Resolution for Android Applications. In the Demonstrations Track of the 44th International Conference on Software Engineering, pp. 105-109, May 2022, Pittsburgh, PA, USA. [pdf]

  34. [ICSE 2022, CORE-A*/CCF-A] Sinan Wang, Yibo Wang, Xian Zhan, Ying Wang, Yepang Liu, Xiapu Luo, and Shing-Chi Cheung. Aper: Evolution-Aware Runtime Permission Misuse Detection for Android Apps. In the 44th International Conference on Software Engineering, pp. 125-137, May 2022, Pittsburgh, PA, USA. [acceptance rate: 28.5%][pdf][tool]

  35. [ASE 2021, CORE-A*/CCF-A] Mingwei Zheng, Jun Yang, Ming Wen, Hengcheng Zhu, Yepang Liu, and Hai Jin. Why Do Developers Remove Lambda Expressions in Java?. In the 36th IEEE/ACM International Conference on Automated Software Engineering, pp. 67-78, November 2021, Melbourne, Australia. [acceptance rate: 18.6%][pdf]

  36. [ASE 2021, CORE-A*/CCF-A] Huaxun Huang, Ming Wen, Lili Wei, Yepang Liu, and Shing-Chi Cheung. Characterizing and Detecting Configuration Compatibility Issues in Android Apps. In the 36th IEEE/ACM International Conference on Automated Software Engineering, pp. 517–528, November 2021, Melbourne, Australia. [acceptance rate: 18.6%][pdf]

  37. [ASE 2021, CORE-A*/CCF-A] Lu Liu, Lili Wei, Wuqi Zhang, Ming Wen, Yepang Liu, and Shing-Chi Cheung. Characterizing Transaction-Reverting Statements in Ethereum Smart Contracts. In the 36th IEEE/ACM International Conference on Automated Software Engineering, pp. 630–641, November 2021, Melbourne, Australia. [acceptance rate: 18.6%][pdf]

  38. [ESEC/FSE 2021, CORE-A*/CCF-A] Dinghua Wang, Shuqing Li, Guanping Xiao, Yepang Liu, and Yulei Sui. An Exploratory Study of Autopilot Software Bugs in Unmanned Aerial Vehicles. In the 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, pp. 20–31, August 2021, Athens, Greece. [acceptance rate: 24.5%][pdf]

  39. [ESEC/FSE 2021, CORE-A*/CCF-A] Wuqi Zhang, Lili Wei, Shuqing Li, Yepang Liu, and Shing-Chi Cheung. ÐArcher: Detecting On-Chain-Off-Chain Synchronization Bugs in Decentralized Applications. In the 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, pp. 553–565, August 2021, Athens, Greece. [acceptance rate: 24.5%][pdf]

  40. [ESEC/FSE 2021, CORE-A*/CCF-A] Yida Tao, Zhihui Chen, Yepang Liu, Zhiwu Xu, and Shengchao Qin. Demystifying “Bad” Error Messages in Data Science Libraries. In the 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, pp. 818–829, August 2021, Athens, Greece. [acceptance rate: 24.5%][pdf]

  41. [ICSE 2021, CORE-A*/CCF-A] Yan Zheng, Yi Liu, Xiaofei Xie, Yepang Liu, Lei Ma, Jianye Hao, and Yang Liu. Automatic Web Testing using Curiosity-Driven Reinforcement Learning. In the 43rd ACM/IEEE International Conference on Software Engineering, pp. 423–435, May 2021, Madrid, Spain. [acceptance rate: 22.4%][pdf]

  42. award [ICSE 2021, CORE-A*/CCF-A] Ying Wang, Liang Qiao, Chang Xu, Yepang Liu, Shing-Chi Cheung, Na Meng, Hai Yu, and Zhiliang Zhu. Hero: On the Chaos When PATH Meets Modules. In the 43rd ACM/IEEE International Conference on Software Engineering, pp. 99-111, Madrid, Spain, May 2021. [acceptance rate: 22.4%][pdf][tool]

  43. [SANER 2021, CORE-A/CCF-B] Sinan Wang, Ming Wen, Yepang Liu, Ying Wang, and Rongxin Wu. Understanding and Facilitating the Co-Evolution of Production and Test Code. In the 28th IEEE International Conference on Software Analysis, Evolution and Reengineering, pp. 272-283, March 2021, Honolulu, HI, USA. [acceptance rate: 25%][pdf][artifacts]

  44. [ISSRE 2020, CORE-A/CCF-B] Shuqing Li, Yechang Wu, Yi Liu, Dinghua Wang, Ming Wen, Yida Tao, Yulei Sui, Yepang Liu. An Exploratory Study of Bugs in Extended Reality Applications on the Web. In the 31st International Symposium on Software Reliability Engineering, pp. 172-183, October 2020, Coimbra, Portugal. [acceptance rate: 20.8%][pdf][artifacts]

  45. [ASE 2020, CORE-A*/CCF-A] Hengcheng Zhu, Lili Wei, Ming Wen, Yepang Liu, Shing-Chi Cheung, Qin Sheng, Cui Zhou. MockSniffer: Characterizing and Recommending Mocking Decisions for Unit Tests. In the 35th IEEE/ACM International Conference on Automated Software Engineering, pp. 436-447, September 2020, Melbourne, Australia. [acceptance rate: 22.5%][pdf]

  46. [ASE 2020, CORE-A*/CCF-A] Yida Tao, Jiefang Jiang, Yepang Liu, Zhiwu Xu, Shengchao Qin. Understanding Performance Concerns in the API Documentation of Data Science Libraries. In the 35th IEEE/ACM International Conference on Automated Software Engineering, pp. 895-906, September 2020, Melbourne, Australia. [acceptance rate: 22.4%][pdf]

  47. [ASE 2020 Industry Showcase] Yi Liu, Jinhui Xie, Jianbo Yang, Shiyu Guo, Yuetang Deng, Shuqing Li, Yechang Wu, and Yepang Liu. Industry Practice of JavaScript Dynamic Analysis on WeChat Mini-Programs. In the 35th IEEE/ACM International Conference on Automated Software Engineering (Industry Showcase track), pp. 1189-1193, September 2020, Melbourne, Australia. [pdf]

  48. [ISSTA 2020, CORE-A/CCF-A] Xueliang Li, Yuming Yang, Yepang Liu, John P. Gallagher, Kaishun Wu. Detecting and Diagnosing Energy Issues for Mobile Applications. In the 29th ACM SIGSOFT International Symposium on Software Testing and Analysis, pp.115-127, July 2020, Los Angeles, California, United States. [acceptance rate: 26.5%][pdf]

  49. [ICSE 2020 Demo] Yongqiang Tian, Zhihua Zeng, Ming Wen, Yepang Liu, Tzu-yang Kuo, Shing-Chi Cheung. EvalDNN: A Toolbox for Evaluating Deep Neural Network Models. In the 42nd International Conference on Software Engineering, Demonstrations Track, pp. 45-48, May 2020, Seoul, South Korea. [acceptance rate: 33.3%][tool][benchmark][pdf]

  50. [ICSE 2020 NIER] Ming Wen, Yepang Liu, and Shing-Chi Cheung. Boosting Automated Program Repair with Bug-Inducing Commits. In the 42nd International Conference on Software Engineering, New Ideas and Emerging Results Track, pp. 77-80, May 2020, Seoul, South Korea. [acceptance rate: 30.1%][pdf]

  51. [ICSE 2020, CORE-A*/CCF-A] Ying Wang, Ming Wen, Yepang Liu, Yibo Wang, Zhenming Li, Chao Wang, Hai Yu, Shing-Chi Cheung, Chang Xu, and Zhiliang Zhu. Watchman: Monitoring Dependency Conflicts for Python Library Ecosystem. In the 42nd International Conference on Software Engineering, pp. 125-135, May 2020, Seoul, South Korea. [acceptance rate: 20.9%][pdf][website]

  52. [SANER 2020, CORE-A/CCF-B] Zhaoxu Zhang, Hengcheng Zhu, Ming Wen, Yida Tao, Yepang Liu, and Yingfei Xiong. How Do Python Framework APIs Evolve? An Exploratory Study. In the 27th IEEE International Conference on Software Analysis, Evolution and Reengineering, pp. 81-92, February 2020, London, ON, Canada. [acceptance rate: 21.1%][pdf][talk][slides][artifacts]

  53. [ASE 2019 NIER] Yida Tao, Shan Tang, Yepang Liu, Zhiwu Xu, and Shengchao Qin. How Do API Selections Affect the Runtime Performance of Data Analytics Tasks?. In the 34th IEEE/ACM International Conference on Automated Software Engineering (New Ideas Paper), pp. 665-668, November 2019, San Diego, CA, USA. [pdf]

  54. [ESEC/FSE 2019, CORE-A*/CCF-A] Ming Wen, Rongxin Wu, Yepang Liu, Yongqiang Tian, Xuan Xie, Shing-Chi Cheung, and Zhendong Su. Exploring and Exploiting the Correlations between Bug-Inducing and Bug-Fixing Commits. In the 27th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, pp. 326-337, Tallinn, Estonia, August 2019. [acceptance rate: 24.4%][pdf]

  55. [ICSE 2019, CORE-A*/CCF-A] Ming Wen, Yepang Liu, Rongxin Wu, Xuan Xie, Shing-Chi Cheung, and Zhendong Su. Exposing Library API Misuses via Mutation Analysis. In the 41st ACM/IEEE International Conference on Software Engineering, pp. 866-877, Montreal, Quebec, Canada, May 2019. [acceptance rate: 21.0%][pdf]

  56. award [ICSE 2019, CORE-A*/CCF-A] Lili Wei, Yepang Liu, and Shing-Chi Cheung. PIVOT: Learning API-Device Correlations to Facilitate Android Compatibility Issue Detection. In the 41st ACM/IEEE International Conference on Software Engineering, pp. 878-888, Montreal, Quebec, Canada, May 2019. [acceptance rate: 21.0%][pdf]

  57. [SANER 2019, CORE-A/CCF-B] Wenjie Li, Yanyan Jiang, Chang Xu, Yepang Liu, Xiaoxing Ma, and Jian Lu. Characterizing and Detecting Inefficient Image Displaying Issues in Android Apps. In the 26th edition of the IEEE International Conference on Software Analysis, Evolution and Reengineering, pp. 355-365, Hangzhou, China, March 2019. [acceptance rate: 27.0%][pdf]

  58. [ASE 2018, CORE-A*/CCF-A] Huaxun Huang,Lili Wei, Yepang Liu, and Shing-Chi Cheung. Understanding and Detecting Callback Compatibility Issues for Android Applications. In the 33rd IEEE/ACM International Conference on Automated Software Engineering, pp. 532-542, Montpellier, France, September 2018. [acceptance rate: 19.9%][pdf]

  59. [ASE 2018, CORE-A*/CCF-A] Jiajun Hu, Lili Wei, Yepang Liu, Shing-Chi Cheung, and Huaxun Huang. A Tale of Two Cities: How WebView Induces Bugs to Android Applications. In the 33rd IEEE/ACM International Conference on Automated Software Engineering, pp. 702-713, Montpellier, France, September 2018. [acceptance rate: 19.9%][pdf][tool]

  60. [ESEC/FSE 2017, CORE-A*/CCF-A] Lili Wei, Yepang Liu, and Shing-Chi Cheung. OASIS: Prioritizing Static Analysis Warnings for Android Apps Based on App User Reviews. In the 11th Joint Meeting Of The European Software Engineering Conference and The ACM SIGSOFT Symposium on the Foundations of Software Engineering, pp. 672-682, Paderborn, Germany, September 2017. [acceptance rate: 24.4%][pdf][tool and data]

  61. [FSE 2016, CORE-A*/CCF-A] Yepang Liu, Chang Xu, Shing-Chi Cheung, and Valerio Terragni. Understanding and Detecting Wake Lock Misuses for Android Applications. In the 24th ACM SIGSOFT International Symposium on the Foundations of Software Engineering, pp. 396-409, Seattle, WA, USA, November 2016. [acceptance rate: 27.1%][pdf][slides][dataset]

  62. [Internetware 2016, CCF-C] Jue Wang, Yepang Liu, Chang Xu, Xiaoxing Ma, and Jian Lu. E-GreenDroid: Effective Energy Inefficiency Analysis for Android Applications. In the 8th Asia-Pacific Symposium on Internetware, pp. 71-80, Beijing, China, September 2016. [pdf]

  63. award [ASE 2016, CORE-A*/CCF-A] Lili Wei, Yepang Liu, and Shing-Chi Cheung. Taming Android Fragmentation: Characterizing and Detecting Compatibility Issues for Android Apps. In the 31st IEEE/ACM International Conference on Automated Software Engineering, pp. 226-237, Singapore, September 2016. [acceptance rate: 19.1%][pdf][dataset][slides]

  64. [ISSTA 2016, CORE-A/CCF-A] Valerio Terragni, Yepang Liu, and Shing-Chi Cheung. CSNIPPEX: Automated Synthesis of Compilable Code Snippets from Q&A Sites. In the 25th International Symposium on Software Testing and Analysis, pp. 118-129, Saarbrücken, Germany, July 2016. [acceptance rate: 25.2%][pdf][tool]

  65. [ICSE 2016, CORE-A*/CCF-A] Shing-Chi Cheung, Wanjun Chen, Yepang Liu, and Chang Xu. CUSTODES: Automatic Spreadsheet Cell Clustering and Smell Detection Using Strong and Weak Features. In The 38th International Conference on Software Engineering, pp. 464-475, Austin, TX, USA, May 2016. [acceptance rate: 19.1%][pdf][tool and dataset]

  66. [APSEC 2014, CORE-B/CCF-C] Xiujiang Li, Yanyan Jiang, Yepang Liu, Chang Xu, Xiaoxing Ma, and Jian Lu. User Guided Automation for Testing Mobile Apps. In the 21st Asia-Pacific Software Engineering Conference, pp. 27-34, Jeju, Korean, December 2014. [acceptance rate: 29.6%][pdf]

  67. [ASE 2014, CORE-A*/CCF-A] Wenhua Yang, Chang Xu, Yepang Liu, Chun Cao, Xiaoxing Ma, and Jian Lu. Verifying Self-adaptive Applications Suffering Uncertainty. In the 29th IEEE/ACM International Conference on Automated Software Engineering, pp. 199-209, Vasteras, Sweden, September 2014. [acceptance rate: 20.0%][pdf]

  68. award [ICSE 2014, CORE-A*/CCF-A] Yepang Liu, Chang Xu, and Shing-Chi Cheung. Characterizing and Detecting Performance Bugs for Smartphone Applications. In the 36th International Conference on Software Engineering, pp. 1013-1024, Hyderabad, India, May 2014. [acceptance rate: 20.0%][pdf][project website][slides]

  69. [Middleware 2013 DS] Yepang Liu and Chang Xu. VeriDroid: Automating Android Application Verification. In the 14th ACM/IFIP/USENIX International Middleware Conference, Doctoral Symposium, Article 5, pp. 1-6, Beijing, China, December 2013. [pdf]

  70. [PerCom 2013, CORE-A*/CCF-B] Yepang Liu, Chang Xu, and Shing-Chi Cheung. Where Has My Battery Gone? Finding Sensor Related Energy Black Holes in Smartphone Applications. In the 11th IEEE International Conference on Pervasive Computing and Communications, pp. 2-10, San Diego, CA, USA, March 2013. [acceptance rate: 11.2%][pdf][project website][slides]

Journal/Magazine Papers

  1. [TSE 2024, JCR-Q1/CCF-A] Shangwen Wang, Mingyang Geng, Bo Lin, Ming Wen, Yepang Liu, Li Li, Tegawende Bissyande, and Xiaoguang Mao. Fusing Code Searchers. In IEEE Transactions on Software Engineering, to appear.

  2. [TOSEM 2023, JCR-Q1/CCF-A] Hengcheng Zhu, Lili Wei, Valerio Terragni, Yepang Liu, Shing-Chi Cheung, Jiarong Wu, Qin Sheng, Bing Zhang, and Lihong Song. StubCoder: Automated Generation and Repair of Stub Code for Mock Objects. In ACM Transactions on Software Engineering and Methodology, to appear.

  3. [TOSEM 2023, JCR-Q1/CCF-A] Shangwen Wang, Ming Wen, Bo Lin, Yepang Liu, Tegawende Bissyande, and Xiaoguang Mao. Pre-Implementation Method Name Prediction for Object-Oriented Programming. In ACM Transactions on Software Engineering and Methodology, 2023, to appear.

  4. [TSE 2023, JCR-Q1/CCF-A] Wuqi Zhang, Lili Wei, Shing-Chi Cheung, Yepang Liu, Shuqing Li, Lu Liu, and Michael R. Lyu. Combatting Front-Running in Smart Contracts: Attack Mining, Benchmark Construction and Vulnerability Detector Evaluation. In IEEE Transactions on Software Engineering, to appear. [preprint]

  5. [CSUR 2023, JCR-Q1] Yue Liu, Chakkrit Tantithamthavorn, Li Li, and Yepang Liu. Deep Learning for Android Malware Defenses: a Systematic Literature Review. In ACM Computing Surveys, Vol. 55, Iss. 8, No. 153, pp. 1–36, August 2023 (online date: 23 December 2022). [pdf]

  6. [TSE 2023, JCR-Q1/CCF-A] Ying Wang, Yibo Wang, Sinan Wang, Yepang Liu, Chang Xu, Shing-Chi Cheung, Hai Yu, and Zhiliang Zhu. Runtime Permission Issues in Android Apps: Taxonomy, Practices, and Ways Forward. In IEEE Transactions on Software Engineering, Vol. 49, Iss. 1, pp. 185-210, January 2023 (online date: 4 February 2022). [pdf]

  7. [FCS 2023, JCR-Q2/CCF-B] Yuxia Sun, Jiefeng Fang, Yanjia Chen, Yepang Liu, Zhao Chen, Song Guo, Xinkai Chen, and Ziyuan Tan. Energy Inefficiency Diagnosis for Android Applications: A Literature Review. In Frontiers of Computer Science, Vol. 17, No. 171201, 2023 (online: August 2022).

  8. [SCIS 2022, JCR-Q1/CCF-A] Yingfei Xiong, Yongqiang Tian, Yepang Liu, and Shing-Chi Cheung. Towards Actionable Testing of Deep Learning Models. In Science China Information Sciences, 26 September 2022 (online). [pdf]

  9. [TOSEM 2022, JCR-Q1/CCF-A] Xueliang Li, Junyang Chen, Yepang Liu, John P. Gallagher, Kaishun Wu. Combatting Energy Issues for Mobile Applications. In ACM Transactions on Software Engineering and Methodology, April 2022 (online). [pdf]

  10. [TSE 2022, JCR-Q1/CCF-A] Xian Zhan, Tianming Liu, Yepang Liu, Yang Liu, Li Li, Haoyu Wang, and Xiapu Luo. A Systematic Assessment on Android Third-party Library Detection Tools. In IEEE Transactions on Software Engineering, Vol. 48, Iss. 11, pp. 4249-4273, November 2022 (online date: September 2021). [pdf]

  11. [TSE 2022, JCR-Q1/CCF-A] Ying Wang, Rongxin Wu, Chao Wang, Ming Wen, Yepang Liu, Shing-Chi Cheung, Hai Yu, Chang Xu, and Zhiliang Zhu. Will Dependency Conflicts Affect My Program’s Semantics?. In IEEE Transactions on Software Engineering, Vol. 48, Iss. 7, pp. 2295-2316, July 2022 (online date: 8 February 2021). [pdf]

  12. [EMSE 2021, JCR-Q1/CCF-B] Yongqiang Tian, Shiqing Ma, Ming Wen, Yepang Liu, Shing-Chi Cheung, and Xiangyu Zhang. To What Extent Do DNN-based Image Classification Models Make Unreliable Inferences?. In Empirical Software Engineering, Vol. 26, Iss. 5, September 2021. [data and tool][pdf]

  13. [TOSEM 2021, JCR-Q1/CCF-A] Yida Tao, Shan Tang, Yepang Liu, Zhiwu Xu, and Shengchao Qin. Speeding up Data Manipulation Tasks with Alternative Implementations: An Exploratory Study. In ACM Transactions on Software Engineering and Methodology, Vol. 30, Iss. 4O, October 2021. [data and tool][pdf]

  14. [IST 2021, JCR-Q1/CCF-B] Sen Fang, Youshuai Tian, Tao Zhang, and Yepang Liu. Self-Attention Networks for Code Search. In Information and Software Technology, Volume 134, 2021. [paper]

  15. [TSE 2020, JCR-Q1/CCF-A] Lili Wei, Yepang Liu, Shing-Chi Cheung, Huaxun Huang, Xuan Lu, and Xuanzhe Liu. Understanding and Detecting Fragmentation-Induced Compatibility Issues for Android Apps. In IEEE Transactions on Software Engineering, vol. 46, no. 11, pp. 1176-1199, 1 Nov. 2020. [paper]

  16. [EMSE 2019, JCR-Q1/CCF-B] Yepang Liu, Jue Wang, Lili Wei, Chang Xu, Shing-Chi Cheung, Tianyong Wu, Jun Yan, and Jian Zhang. DroidLeaks: A Comprehensive Database of Resource Leaks in Android Apps. In Empirical Software Engineering, Vol. 24, pp. 3435–3483, 16 May 2019 (online). [pdf][dataset]

  17. [SCIS 2017, JCR-Q1/CCF-A] Qiwei Li, Chang Xu, Yepang Liu, Chun Cao, Xiaoxing Ma, and Jian Lu. CyanDroid: Stable and Effective Energy Inefficiency Diagnosis for Android Apps. In Science China Information Sciences, Vol. 60, No. 1, Article 012104, pp. 1-18, Jan 2017. [pdf]

  18. [SCIS 2015, JCR-Q1/CCF-A] Wenhua Yang, Yepang Liu, Chang Xu, and Shing-Chi Cheung. A Survey on Dependability Improvement Techniques for Pervasive Computing Systems. In Science China Information Sciences, Vol. 58, No. 5, Article 052102, pp. 1-14, May 2015. [pdf]

  19. [IEEE SW 2015, JCR-Q2] Yepang Liu, Chang Xu, and Shing-Chi Cheung. Diagnosing Energy Efficiency and Performance for Mobile Internetware Applications. In IEEE Software, Vol. 32, No. 1, pp. 67-75, January 2015. [pdf]

  20. [CCCF 2014] Yepang Liu, Chang Xu, and Shing-Chi Cheung. Detecting Energy and Performance Bugs for Smartphone Applications (智能手机应用的能耗与性能问题诊断). In Communications of the CCF (CCCF/中国计算机学会通讯), Vol. 10, No. 12, pp. 40-42, December 2014. [pdf]

  21. [TSE 2014, JCR-Q1/CCF-A] Yepang Liu, Chang Xu, Shing-Chi Cheung, and Jian Lu. GreenDroid: Automated Diagnosis of Energy Inefficiency for Smartphone Applications. In IEEE Transactions on Software Engineering, Vol. 40, No. 9, pp. 911-940, September 2014. [pdf][project website]

  22. [IJSI 2014] Yepang Liu, Chang Xu, Shing-Chi Cheung, and Wenhua Yang. CHECKERDROID: Automated Quality Assurance for Smartphone Applications. In International Journal of Software and Informatics, Vol. 8, Iss. 1, pp. 21-41, 2014. [pdf] (Invited article based on a keynote talk at Internetware 2013)

  23. [TOSEM 2014, CCF-A] Yueqi Li, Shing-Chi Cheung, Xiangyu Zhang, and Yepang Liu. Scaling Up Symbolic Analysis by Removing Z-Equivalent States. In ACM Transactions on Software Engineering and Methodology, Vol. 23, Iss. 4, Article 34, pp. 1-32, August 2014. [pdf]

  24. [SCIS 2013, JCR-Q1/CCF-A] Chang Xu, Yepang Liu, Shing-Chi Cheung, Chun Cao, and Jian Lu. Towards Context Consistency by Concurrent Checking for Internetware Applications. In Science China Information Sciences, Vol. 56, No. 8, Article 082105, pp. 1-20, August 2013. [pdf]

  25. [JSS 2013, JCR-Q2/CCF-B] Yepang Liu, Chang Xu, and Shing-Chi Cheung. AFChecker: Effective Model Checking for Context-Aware Adaptive Applications. In Journal of Systems and Software, Vol. 86, Iss. 3, pp. 854-867, March 2013. [pdf][project website]

Book Chapters

  1. Yepang Liu, Chang Xu, Shing-Chi Cheung, and Jian Lu. Greendroid: Automated Diagnosis of Energy Inefficiency for Smartphone Applications. Book Chapter in Internetware: A New Software Paradigm for Internet Computing (edited by Hong Mei and Jian Lu), Springer Singapore, pp. 389-438, Dec 2016.

Doctoral Thesis

  1. Yepang Liu. Automated Analysis of Energy Efficiency and Execution Performance for Mobile Applications. Doctoral Thesis, Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, June 2015. [pdf]

Technical Reports

  1. Yongqiang Tian, Shiqing Ma, Ming Wen, Yepang Liu, Shing-Chi Cheung, and Xiangyu Zhang. Testing Deep Learning Models for Image Analysis Using Object-Relevant Metamorphic Relations. arxiv:1909.03824. [pdf]

  2. Yepang Liu, Lili Wei, Chang Xu, and Shing-Chi Cheung. DroidLeaks: Benchmarking Resource Leak Bugs for Android Applications. arXiv:1611.08079. [pdf]

  3. Yepang Liu, Chang Xu, Shing-Chi Cheung, and Valerio Terragni. How Do Developers Use Wake Locks in Android Applications? A Large-Scale Empirical Study. Technical Report HKUST-CS15-04. Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, November 2015. [pdf]

  4. Yueqi Li, Shing-Chi Cheung, Xiangyu Zhang, and Yepang Liu. Scaling Up Symbolic Analysis by Removing Z-Equivalent States. Technical Report HKUST-CS13-06. Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, July 2013.

  5. Yepang Liu, Chang Xu, and Shing-Chi Cheung. Verifying Android Applications Using Java PathFinder. Technical Report HKUST-CS12-03. Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, September 2012. [project website]

  6. Yepang Liu. A Survey of Context-Aware Pervasive Applications: From Development Support to Quality Assurance. PhD Qualification Exam Report, Department of Computer Science and Technology, Janurary 2012. [pdf]

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