2024

JoS (软件学报)

Bo Lin, Shangwen Wang, and Xiaoguang Mao. Automated Software Vulnerability Repair Based on Chain-of-Thought (基于思维链的软件漏洞自动修复技术研究) in Journal of Software (软件学报), (JoS, CCF-A). [PDF] [bib]

ICSE’24 A

Mingyang Geng, Shangwen Wang^*, Dezun Dong, Haotian Wang, Ge Li, Zhi Jin, Xiaoguang Mao, and Xiangke Liao (^*Corresponding author). Large Language Models are Few-Shot Summarizers: Multi-Intent Comment Generation via In-Context Learning in Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, Lisbon, Portugal (ICSE’24, CCF-A). [Acceptance rate: 22.3% (234/1051)] [PDF] [bib] [Artifacts]

ICSE’24 B

Zhensu Sun, Xiaoning Du, Fu Song, Shangwen Wang, Li Li. When Neural Code Completion Models Size up the Situation: Attaining Cheaper and Faster Completion through Dynamic Model Inference in Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, Lisbon, Portugal (ICSE’24, CCF-A). [Acceptance rate: 22.3% (234/1051)] [PDF] [bib] [Artifacts]

ICPC’24

Zhang Zhang, Xinjun Mao, Shangwen Wang, Kang Yang, Yao Lu. CAREER: Context-Aware API Recognition with Data Augmentation for API Knowledge Extraction in Proceedings of the 32nd ACM/IEEE International Conference on Program Comprehension, Lisbon, Portugal (ICPC’24, CCF-B). [Acceptance rate: 38% (30/78)] [PDF] [bib] [Artifacts]

2023

OOPSLA’23

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 a Generative Adversarial Network in Proceedings of the ACM Conference on Object-Oriented Programming Systems, Languages, and Applications, Cascais, Portugal (OOPSLA’23, CCF-A). [PDF] [bib] [Artifacts]

ESEC/FSE’23 A

Shangwen Wang, Mingyang Geng, Bo Lin, Zhensu Sun, Ming Wen, Yepang Liu, Li Li, Tegawendé F. Bissyandé, and Xiaoguang Mao. Natural Language to Code: How Far are We? in Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, San Francisco, USA (ESEC/FSE’23, CCF-A). [Acceptance rate: 27% (127/465)] [PDF] [bib] [Artifacts]

ESEC/FSE’23 B

Bo Lin, Shangwen Wang^*, Zhongxin Liu, Yepang Liu, Xin Xia, and Xiaoguang Mao (^*Corresponding author). CCT5: A Code-Change-Oriented Pre-Trained Model in Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, San Francisco, USA (ESEC/FSE’23, CCF-A). [Acceptance rate: 27% (127/465)] [PDF] [bib] [Artifacts]

ESEC/FSE’23 C

Xiaohu Du, Ming Wen, Zichao Wei, Shangwen Wang, and Hai Jin. An Extensive Study on Adversarial Attack against Pre-trained Models of Code in Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, San Francisco, USA (ESEC/FSE’23, CCF-A). [Acceptance rate: 27% (127/465)] [PDF] [bib] [Artifacts]

TOSEM

Shangwen Wang, Ming Wen, Bo Lin, Yepang Liu, Tegawendé F. Bissyandé, and Xiaoguang Mao. Pre-Implementation Method Name Prediction for Object-Oriented Programming in ACM Transactions on Software Engineering and Methodology (CCF-A), 2023. [PDF] [bib] [Artifacts]

JoS (软件学报)

Shangwen Wang, Kui Liu, Bo Lin, Li Li, Jacques Klein, Tegawendé F. Bissyandé, and Xiaoguang Mao. Fine-Grained Fault Localization Based on Pointer Neural Network (基于指针神经网络的细粒度缺陷定位研究) in Journal of Software (软件学报), (JoS, CCF-A). [PDF] [bib]

ICPC’23 A

Mingyang Geng, Shangwen Wang^*, Dezun Dong, Haotian Wang, Shaomeng Cao, Kechi Zhang, and Zhi Jin (^*Corresponding author). Interpretation-based Code Summarization in Proceedings of the 31st ACM/IEEE International Conference on Program Comprehension, Melbourne, Australia (ICPC’23, CCF-B). [Acceptance rate: 32% (22/67)] [PDF] [bib] [Artifacts]

ICPC’23 B

Kang Yang, Xinjun Mao, Shangwen Wang^*, Yihao Qin, Yao Lu, Tanghaoran Zhang, and Kamal Al-Sabahi (^*Corresponding author). An Extensive Study of the Structure Features in Transformer-based Code Semantic Summarization in Proceedings of the 31st ACM/IEEE International Conference on Program Comprehension, Melbourne, Australia (ICPC’23, CCF-B). [Acceptance rate: 32% (22/67)] [PDF] [bib] [Artifacts]

2022

ASE’22 A

Haoye Tian, Xunzhu Tang, Andrew Habib, Shangwen Wang, Kui Liu, Xin Xia, Jacques Klein, and Tegawendé F. Bissyandé. Is this Change the Answer to that Problem? Correlating Descriptions of Bug and Code Changes for Evaluating Patch Correctness in Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering, Michigan, United States (ASE’22, CCF-A). [Acceptance rate: 22.0% (116/527)] [PDF] [bib]

ASE’22 B

Zhuo Zhang, Yan Lei, Meng Yan, Yue Yu, Jiachi Chen, Shangwen Wang, and Xiaoguang Mao. Reentrancy Vulnerability Detection and Localization: A Deep Learning Based Two-phase Approach in Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering, Michigan, United States (ASE’22, CCF-A). [Acceptance rate: 22.0% (116/527)] [PDF] [bib]

TSE (Presented as a journal-first paper at ICSE'23)

Bo Lin, Shangwen Wang^*, Zhongxin Liu, Xin Xia, and Xiaoguang Mao (^*Corresponding author). Predictive Comment Updating with Heuristics and AST-Path-Based Neural Learning: A Two-Phase Approach in IEEE Transactions on Software Engineering (CCF-A), 2022. [PDF] [bib] [Artifacts]

ICSME’22 🏆(IEEE TCSE Distinguished Paper Award!)

Yihao Qin, Shangwen Wang^*, Kui Liu, Bo Lin, Hongjun Wu, Li Li, Xiaoguang Mao and Tegawendé F. Bissyandé (^*Corresponding author). Peeler: Learning to Effectively Predict Flakiness without Running Tests in Proceedings of the 38th IEEE International Conference on Software Maintenance and Evolution, Limassol, Cyprus (ICSME’22, CCF-B). [Acceptance rate: 23.5% (32/136)] [PDF] [bib] [Artifacts]

ICPC’22

Mingyang Geng, Shangwen Wang^*, Dezun Dong, Shanzhi Gu, Fang Peng, Weijian Ruan, and Xiangke Liao (^*Corresponding author). Fine-Grained Code-Comment Semantic Interaction Analysis in Proceedings of the 30th ACM/IEEE International Conference on Program Comprehension, Virtual (ICPC’22, CCF-B). [Acceptance rate: 47% (48/102)] [PDF] [bib] [Artifacts]

SANER’22 A 🏆(IEEE TCSE Distinguished Paper Award!)

Menghan Wu, Yang Zhang, Jiakun Liu, Shangwen Wang, Zhang Zhang, Xin Xia, and Xinjun Mao. On the Way to Microservices: Exploring Problems and Solutions from Online Q&A Community in Proceedings of the 29th IEEE International Conference on Software Analysis, Evolution and Reengineering, Honolulu, Hawaii (SANER’22, CCF-B). [Acceptance rate: 24% (48/199)] [PDF] [bib] [Artifacts]

SANER’22 B

Yinyuan Zhang, Yang Zhang, Xinjun Mao, Yiwen Wu, Bo Lin, Shangwen Wang. Recommending Base Image for Docker Containers based on Deep Configuration Comprehension in Proceedings of the 29th IEEE International Conference on Software Analysis, Evolution and Reengineering, ERA Track, Honolulu, Hawaii (SANER’22, CCF-B). [PDF] [bib]

2021

TOSEM (Presented as a journal-first paper at ESEC/FSE'22)

Bo Lin, Shangwen Wang^*, Ming Wen, and Xiaoguang Mao (^*Corresponding author). Context-Aware Code Change Embedding for Better Patch Correctness Assessment in ACM Transactions on Software Engineering and Methodology (CCF-A), 2021. [PDF] [bib] [Artifacts]

EMSE (Presented as a journal-first paper at ICSE'22)

Steffen Herbold et al. A Fine-grained Data Set and Analysis of Tangling in Bug Fixing Commits in Empirical Software Engineering (CCF-B), 2021. [PDF] [bib]

ISSRE’21

Hongjun Wu, Zhuo Zhang, Shangwen Wang^*, Yan Lei, Bo Lin, Yihao Qin, Haoyu Zhang, and Xiaoguang Mao (^*Corresponding author). Peculiar: Smart Contract Vulnerability Detection Based on Crucial Data Flow Graph and Pre-training Techniques in Proceedings of the 32nd IEEE International Symposium on Software Reliability Engineering, Wuhan, China (ISSRE’21, CCF-B). [Acceptance rate: 27.5% (52/189)] [PDF] [bib] [Artifacts]

ESEC/FSE’21

Shangwen Wang, Ming Wen, Bo Lin, and Xiaoguang Mao. Lightweight Global and Local Contexts Guided Method Name Recommendation with Prior Knowledge in Proceedings of the 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, Athens, Greece (ESEC/FSE’21, CCF-A). [Acceptance rate: 24.2% (96/396)] [PDF] [bib] [Artifacts]

ICPC’21

Bo Lin, Shangwen Wang^*, Kui Liu, Xiaoguang Mao, and Tegawendé F. Bissyandé (^*Corresponding author). Automated Comment Update: How Far are We? in Proceedings of the 29th ACM/IEEE International Conference on Program Comprehension, Virtual (ICPC’21, CCF-B). [Acceptance rate: 31% (33/105)] [PDF] [bib] [Artifacts]

SANER’21

Yihao Qin, Shangwen Wang^*, Kui Liu, Xiaoguang Mao, and Tegawendé F. Bissyandé (^*Corresponding author). On the Impact of Flaky Tests in Automated Program Repair in Proceedings of the 28th IEEE International Conference on Software Analysis, Evolution and Reengineering, Virtual (SANER’21, CCF-B). [Acceptance rate: 25% (42/165)] [PDF] [bib] [Artifacts]

2020

APSEC’20 A

Bo Lin, Shangwen Wang^*, Ming Wen, Zhang Zhang, Hongjun Wu, Yihao Qin, and Xiaoguang Mao (^*Corresponding author). Understanding the Non-Repairability Factors of Automated Program Repair Techniques in Proceedings of the 27th Asia-Pacific Software Engineering Conference, Singapore (APSEC’20, CCF-C). [PDF] [bib]

APSEC’20 B

Zhang Zhang, Xinjun Mao, Yao Lu, Shangwen Wang, and Jinyu Lu. An Empirical Study on the Influence of Social Interactions for the Acceptance of Answers in Stack Overflow in Proceedings of the 27th Asia-Pacific Software Engineering Conference, Singapore (APSEC’20, CCF-C). [PDF] [bib]

ASE’20

Shangwen Wang, Ming Wen, Bo Lin, Hongjun Wu, Yihao Qin, Deqing Zou, Xiaoguang Mao, and Hai Jin. Automated Patch Correctness Assessment: How Far are We? in Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering, Melbourne, Australia (ASE’20, CCF-A). [Acceptance rate: 22.5% (93/414)] [PDF] [bib] [Artifacts]

ICSE’20

Kui Liu, Shangwen Wang^*, Anil Koyuncu, Kisub Kim, Tegawendé F. Bissyandé, Dongsun Kim, Peng Wu, Jacques Klein, Xiaoguang Mao, and Yves Le Traon (^*Co-first author and Corresponding author). On the efficiency of Test Suite based Program Repair: A Systematic Assessment of 16 Automated Repair Systems for Java Programs in Proceedings of the 42nd IEEE/ACM International Conference on Software Engineering, Seoul, South Korea (ICSE’20, CCF-A). [Acceptance rate: 20.9% (129/617)] [PDF] [bib] [Artifacts]

2019

ESEM’19

Shangwen Wang, Ming Wen, Liqian Chen, Xin Yi, and Xiaoguang Mao. How Different Is It Between Machine-Generated and Developer-Provided Patches? An Empirical Study on the Correct Patches Generated by Automated Program Repair Techniques in Proceedings of the 13th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, Porto de Galinhas, Brazil (ESEM’19, CCF-B). [Acceptance rate: 19.8% (23/116)] [PDF] [bib]

SEKE’19

Shangwen Wang, Xiaoguang Mao, Nan Niu, Xin Yi, and Anbang Guo. Multi-Location Program Repair Strategies Learned from Successful Experience in Proceedings of the 31st International Conference on Software Engineering and Knowledge Engineering, Short Paper, Lisbon, Portugal (SEKE’19, CCF-C). [PDF] [bib]

EASE’19

Shangwen Wang, Ming Wen, Xiaoguang Mao, and Deheng Yang. Attention Please: Consider Mockito when Evaluating Newly Proposed Automtaed Program Repair Techniques in Proceedings of the 23rd Evaluation and Assessment in Software Engineering, Short Paper, Copenhagen, Denmark (EASE’19, CCF-C). [PDF] [bib]

2018

ICSME’18

Anbang Guo, Xiaoguang Mao, Deheng Yang, and Shangwen Wang. An Empirical Study on the Effect of Dynamic Slicing on Automated Program Repair Efficiency in Proceedings of the 34th IEEE International Conference on Software Maintainess and Evolution, Short Paper, Madrid, Spain (ICSME’18, CCF-B) [PDF] [bib]

ICSR’18

Shangwen Wang, Tao Wang, Xiaoguang Mao, Yue Yu, and Gang Yin. A Hybrid Approach for Tag Hierarchy Construction in Proceedings of the 17th International Conference on Software Reuse, Madrid, Spain (ICSR’18, CCF-C). [PDF] [bib]