ReSym: Harnessing LLMs to Recover Variable and Data Structure Symbols from Stripped Binaries. Danning Xie, Zhuo Zhang, Nan Jiang, Xiangzhe Xu, Lin Tan, and Xiangyu Zhang. In the proceedings of the ACM Conference on Computer and Communications Security, October 2024. Salt Lake City, USA.

CEDAR: Continuous Testing of Deep Learning Libraries. Danning Xie, Jiannan Wang, Hung Viet Pham, Lin Tan, Yu Guo, Adnan Aziz, and Erik Meijer. In the proceedings of the IEEE International Conference on Software Analysis, Evolution, and Reengineering, March 2024. Rovaniemi, Finland.

Vicious Cycles in Distributed Software Systems. Shangshu Qian, Wen Fan, Lin Tan, and Yongle Zhang. In the proceedings of the IEEE/ACM International Conference on Automated Software Engineering, September, 2023. Kirchberg, Luxembourg. Acceptance Rate: 21%

How Effective are Neural Networks for Fixing Security Vulnerabilities? Yi Wu, Nan Jiang, Hung Viet Pham, Thibaud Lutellier, Jordan Davis, Lin Tan, Petr Babkin, and Sameena Shah. In the proceedings of ACM SIGSOFT International Symposium on Software Testing and Analysis. July 2023. Seattle, USA. Acceptance Rate: 23% (49/215)

Impact of Code Language Models on Automated Program Repair. Nan Jiang, Kevin Liu, Thibaud Lutellier, and Lin Tan. In the proceedings of the International Conference on Software Engineering. May 2023. Melbourne, Australia. Acceptance Rate: 26% (208/796)

KNOD: Domain Knowledge Distilled Tree Decoder for Automated Program Repair. Nan Jiang, Thibaud Lutellier, Yiling Lou, Lin Tan, Dan Goldwasser, and Xiangyu Zhang. In the proceedings of the International Conference on Software Engineering. May 2023. Melbourne, Australia. Acceptance Rate: 26% (208/796)

Revisiting Learning-based Commit Message Generation. Jinhao Dong, Yiling Lou, Dan Hao, and Lin Tan. In the proceedings of the International Conference on Software Engineering. May 2023. Melbourne, Australia. Acceptance Rate: 26% (208/796)

DisGUIDE: Disagreement-Guided Data-Free Model Extraction. (Oral Presentation) Jonathan Rosenthal, Eric Enouen, Hung Viet Pham, and Lin Tan. In the proceedings of AAAI Conference on Artificial Intelligence. February, 2023. Washington D.C., USA. Acceptance Rate: 19.6%

DocTer: Documentation-Guided Fuzzing for Testing Deep Learning API Functions. Danning Xie, Yitong Li, Mijung Kim, Hung Viet Pham, Lin Tan, Xiangyu Zhang, Mike Godfrey. In the proceedings of ACM SIGSOFT International Symposium on Software Testing and Analysis. July 2022. Virtual. Acceptance Rate: 24% (61/250) [Code & Data]

EAGLE: Creating Equivalent Graphs to Test Deep Learning Libraries. Jiannan Wang, Thibaud Lutellier, Shangshu Qian, Hung Viet Pham, and Lin Tan. In the proceedings of the International Conference on Software Engineering. May 2022. Pittsburgh, USA. Acceptance Rate: 26% (197/751) [Code & Data]

Are My Deep Learning Systems Fair? An Empirical Study of Fixed-Seed Training. Shangshu Qian, Hung Viet Pham, Thibaud Lutellier, Zeou Hu, Jungwon Kim, Lin Tan, Yaoliang Yu, Jiahao Chen, and Sameena Shah. In the proceedings of the Conference on Neural Information Processing Systems, December 2021. Virtual. Acceptance Rate: 26% [Code & Data]

Exposing Numerical Bugs in Deep Learning via Gradient Back-propagation. Ming Yan, Junjie Chen, Xiangyu Zhang, Lin Tan, Gan Wang, and Zan Wang. In the proceedings of the ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, August, 2021. Virtual/Athens, Greece. Acceptance Rate: 24.5% (97/396) Nominated for ACM SIGSOFT Distinguished Paper Award!

DEVIATE: A Deep Learning Variance Testing Framework. Hung Viet Pham, Mijung Kim, Lin Tan, Yaoliang Yu, and Nachiappan Nagappan. In the proceedings of the IEEE/ACM International Conference on Automated Software Engineering, November, 2021. Virtual/Melbourne, Australia. [Code & Data]

CURE: Code-Aware Neural Machine Translation for Automatic Program Repair. Nan Jiang, Thibaud Lutellier, and Lin Tan. In the proceedings of the International Conference on Software Engineering. May 2021. Virtual/Madrid, Spain. Acceptance Rate: 22% (138/615) [Data]

Problems and Opportunities in Training Deep Learning Software Systems: An Analysis of Variance. Hung Viet Pham, Shangshu Qian, Jiannan Wang, Thibaud Lutellier, Jonathan Rosenthal, Lin Tan, Yaoliang Yu, and Nachiappan Nagappan. In the proceedings of the IEEE/ACM International Conference on Automated Software Engineering, September, 2020. Virtual/Melbourne, Australia. Acceptance Rate: 22.5% (93/414) Won ACM SIGSOFT Distinguished Paper Award!

CoCoNuT: Combining Context-Aware Neural Translation Models using Ensemble for Program Repair. Thibaud Lutellier, Hung Viet Pham, Lawrence Pang, Yitong Li, Moshi Wei and Lin Tan. In the proceedings of ACM SIGSOFT International Symposium on Software Testing and Analysis. July 2020. Virtual/Los Angeles, United States. Acceptance Rate: 26.5% (43/162) [Code & Data]

C2S: Translating Natural Language Comments to Formal Program Specifications. Juan Zhai, Yu Shi, Minxue Pan, Guian Zhou, Yongxiang Liu, Chunrong Fang, Shiqing Ma, Lin Tan, and Xiangyu Zhang. In the proceedings of the ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, November, 2020. Virtual/Sacramento, United States. Acceptance Rate: 28% (101/360)

CPC: Automatically Classifying and Propagating Natural Language Comments via Program Analysis. Juan Zhai, Xiangzhe Xu, Yu Shi, Guanhong Tao, Minxue Pan, Shiqing Ma, Lei Xu, Weifeng Zhang, Lin Tan, and Xiangyu Zhang. In the proceedings of the International Conference on Software Engineering. July 2020. Virtual/Seoul, South Korea. Acceptance Rate: 21% (129/617)

Deep Semantic Feature Learning for Software Defect Prediction. Song Wang, Taiyue Liu, Jaechang Nam, and Lin Tan. In IEEE Transactions on Software Engineering.

CRADLE: Cross-Backend Validation to Detect and Localize Bugs in Deep Learning Libraries. Hung Viet Pham, Thibaud Lutellier, Weizhen Qi, and Lin Tan. In the proceedings of the International Conference on Software Engineering. Montreal, Canada. Acceptance Rate: 21% (109/529)

Towards Better Utilizing Static Application Security Testing. Jinqiu Yang, Lin Tan, John Peyton, and Kristofer A Duer. In the proceedings of the International Conference on Software Engineering, Software Engineering In Practice. Acceptance Rate: 25% (30/118)

A Bug Finder Refined by a Large Set of Open-Source Projects. Jaechang Nam, Song Wang, Xi Yuan, and Lin Tan, In Information and Software Technology. [DOI]

On the Correctness of Electronic Documents: Studying, Finding, and Localizing Inconsistency Bugs in PDF Readers and Files. (Open Access) Tomasz Kuchta*, Thibaud Lutellier*, Edmund Wong, Lin Tan, and Cristian Cadar. (* The first two authors contributed equally to this paper) Springer Empirical Software Engineering. (34 pages) [Data]

Towards Extracting Web API Specifications from Documentation. Jinqiu Yang, Erik Wittern, Annie T.T. Ying, Julian Dolby, and Lin Tan. In the proceedings of the Working Conference on Mining Software Repositories. Acceptance Rate: 33% (37/113) Won ACM SIGSOFT Distinguished Paper Award!

Designing Bug Detection Rules for Fewer False Alarms. Jaechang Nam, Song Wang, Xi Yuan, and Lin Tan. In the proceedings of the International Conference on Software Engineering, Poster Track.

Heterogeneous Defect Prediction. Jaechang Nam, Wei Fu, Sunghun Kim, Tim Menzies, and Lin Tan. In IEEE Transactions on Software Engineering.

Better Test Cases for Better Automated Program Repair. Jinqiu Yang, Alexey Zhikhartsev, Yuefei Liu and Lin Tan. In the proceedings of the Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT International Symposium on the Foundations of Software Engineering. Acceptance Rate: 24% (72/295)

QTEP: Quality-aware Test Case Prioritization. Song Wang, Jaechang Nam and Lin Tan. In the proceedings of the Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT International Symposium on the Foundations of Software Engineering. Acceptance Rate: 24% (72/295) [Data]

Measuring the Impact of Code Dependencies on Software Architecture Recovery Techniques. Thibaud Lutellier, Devin Chollak, Joshua Garcia, Lin Tan, Derek Rayside, Nenad Medvidovic and Robert Kroeger. In IEEE Transactions on Software Engineering. [Data]

Detecting Sensitive Data Disclosure via Bi-directional Text Correlation Analysis. Jianjun Huang, Xiangyu Zhang and Lin Tan. In the proceedings of the ACM SIGSOFT International Symposium on the Foundations of Software Engineering. Acceptance Rate: 27% (74/273) Won ACM SIGSOFT Distinguished Paper Award!

Bugram: Bug Detection with N-gram Language Models. Song Wang, Devin Chollak, Dana Movshovitz-Attias, and Lin Tan. In the proceedings of the IEEE/ACM International Conference on Automated Software Engineering. Acceptance Rate: 19% (57/298)

Automatically Learning Semantic Features for Defect Prediction. Song Wang, Taiyue Liu, and Lin Tan. In the proceedings of the International Conference on Software Engineering. Acceptance Rate: 19% (101/530)

Automatic Model Generation from Documentation for Java API Functions. Juan Zhai, Jianjun Huang, Shiqing Ma, Xiangyu Zhang, Lin Tan, Jianhua Zhao, and Feng Qin. In the proceedings of the International Conference on Software Engineering. Acceptance Rate: 19% (101/530)

DASE: Document-Assisted Symbolic Execution for Improving Automated Software Testing. Edmund Wong, Lei Zhang, Song Wang, Taiyue Liu and Lin Tan. In the proceedings of the International Conference on Software Engineering. Acceptance Rate: 18.5% (84/452)

Online Defect Prediction for Imbalanced Data. Ming Tan, Lin Tan, Sashank Dara and Caleb Mayeux. In the proceedings of the International Conference on Software Engineering, Software Engineering In Practice. Acceptance Rate: 22.5% (23/102)

Comparing Software Architecture Recovery Techniques Using Accurate Dependencies. Thibaud Lutellier, Devin Chollak, Joshua Garcia, Lin Tan, Derek Rayside, Nenad Medvidovic and Robert Kroeger. In the proceedings of the International Conference on Software Engineering, Software Engineering In Practice. Acceptance Rate: 22.5% (23/102) [Data]

Comment Analysis for Improving Software Quality. Lin Tan. Book chapter in The Art and Science of Analyzing Software Data. Eds. Chris Bird, Tim Menzies, and Thomas Zimmermann. 2015.

CloCom: Mining Existing Source Code for Automatic Comment Generation. Edmund Wong, Taiyue Liu and Lin Tan. In the proceedings of the IEEE International Conference on Software Analysis, Evolution, and Reengineering. (10 pages) Acceptance Rate: 31.9% (46/144) [Code & Data]

AsDroid: Detecting Stealthy Behaviors in Android Applications by User Interface and Program Behavior Contradiction. Jianjun Huang, Xiangyu Zhang, Lin Tan, Peng Wang, and Bin Liang. In the proceedings of the International Conference on Software Engineering. May-June, 2014. Hyderbad, India. (11 pages) Acceptance Rate: 20% (99/495) [BIBTEX]

Finding Patterns in Static Analysis Alerts. Quinn Hanam, Lin Tan, Reid Holmes, and Patrick Lam. In the proceedings of the Working Conference on Mining Software Repositories. May-June, 2014. Hyderabad, India. (10 pages) Acceptance Rate: 34% (29/85) [BIBTEX]

em-SPADE: A Compiler Extension for Checking Rules Extracted from Processor Specifications. Sandeep Chaudhary, Sebastian Fischmeister, and Lin Tan. In the proceedings of the ACM SIGPLAN Conference on Languages, Compilers, and Tools for Embedded Systems. June, 2014. Edinburgh, UK. (10 pages)

SWordNet: Inferring Semantically Related Words from Software Context. Jinqiu Yang and Lin Tan. Accepted to the Springer Empirical Software Engineering. (28 pages) [DOI] [BIBTEX] [Data]

Bug Characteristics in Open Source Software. Lin Tan, Chen Liu, Zhenmin Li, Xuanhui Wang, Yuanyuan Zhou, and Chengxiang Zhai. In the Springer Empirical Software Engineering. (46 pages) [DOI] [BIBTEX]

Correlations between Bugginess and Time-Based Commit Characteristics. Jon Eyolfson, Lin Tan and Patrick Lam. In the Springer Empirical Software Engineering. (33 pages) [DOI] [BIBTEX]

Personalized Defect Prediction. Tian Jiang, Lin Tan, and Sunghun Kim. In the proceedings of the IEEE/ACM International Conference on Automated Software Engineering. (11 pages) Acceptance Rate: 17% (43/253) [BIBTEX] Nominated for ACM SIGSOFT Distinguished Paper Award!

AutoComment: Mining Question and Answer Sites for Automatic Comment Generation. Edmund Wong, Jinqiu Yang, and Lin Tan. In the proceedings of the IEEE/ACM International Conference on Automated Software Engineering, New Idea Papers. (6 pages) Acceptance Rate: 23% (74/317) [BIBTEX] [Data]

Discovering, Reporting, and Fixing Performance Bugs. Adrian Nistor, Tian Jiang, and Lin Tan. In the proceedings of the Working Conference on Mining Software Repositories. May, 2013. San Francisco, California. (10 pages) Acceptance Rate: 38% (31/81) [BIBTEX]

Generating Precise Dependencies For Large Software. Pei Wang, Jinqiu Yang, Lin Tan, Robert Kroeger and David Morgenthaler. (4 pages) In the Proceedings of the Fourth International Workshop on Managing Technical Debt in conjunction with ICSE 2013. [BIBTEX]

R2Fix: Automatically Generating Bug Fixes from Bug Reports. Chen Liu, Jinqiu Yang, Lin Tan, and Munawar Hafiz. In the proceedings of the International Conference on Software Testing, Verification and Validation. March, 2013. Luxembourg. (10 pages) Acceptance Rate: 25% (38/152) [BIBTEX]

Inferring Semantically Related Words from Software Context. Jinqiu Yang and Lin Tan. In the proceedings of the Working Conference on Mining Software Repositories. June, 2012. Zurich, Switherland. (10 pages) Acceptance Rate: 28.1% (18/64).

@tComment: Testing Javadoc Comments to Detect Comment-Code Inconsistencies. Shin Hwei Tan, Darko Marinov, Lin Tan and Gary T. Leavens. In the proceedings of the 5th International Conference on Software Testing, Verification and Validation. April, 2012. Montreal, Quebec. (10 pages) Acceptance Rate: 26.9% (39/145). [BIBTEX] [Code]

Do Time of Day and Developer Experience Affect Commit Bugginess? Jon Eyolfson, Lin Tan and Patrick Lam. In the proceedings of the 8th Working Conference on Mining Software Repositories. May, 2011. Waikiki, Honolulu, Hawaii. (10 pages) Acceptance Rate: 32.8% (20/61). [BIBTEX]

aComment: Mining Annotations from Comments and Code to Detect Interrupt-Related Concurrency Bugs. Lin Tan, Yuanyuan Zhou and Yoann Padioleau. In the proceedings of the International Conference on Software Engineering. May, 2011. Waikiki, Honolulu, Hawaii. (10 pages) Acceptance Rate: 14.1% (62/441). [BIBTEX]

SherLog: Error Diagnosis by Connecting Clues from Run-time Logs. Ding Yuan, Haohui Mai, Weiwei Xiong, Lin Tan, Yuanyuan Zhou and Shankar Pasupathy. In the proceedings of the 15th International Conference on Architecture Support for Programming Languages and Operating Systems, March 2010. Pittsburgh, PA. (12 pages) Acceptance Rate: 17.7% (32/181). [BIBTEX] Nominated for Best Paper Award!

Listening to Programmers - Taxonomies and Characteristics of Comments in Operating System Code. (Alphabetic order) Yoann Padioleau, Lin Tan and Yuanyuan Zhou. In the proceedings of the International Conference on Software Engineering. May, 2009. Vancouver, BC. (11 pages) Acceptance Rate: 12.3% (50/405). [BIBTEX] [Code & Data]

AutoISES: Automatically Inferring Security Specifications and Detecting Violations. Lin Tan, Xiaolan (Catherine) Zhang, Xiao Ma, Weiwei Xiong and Yuanyuan Zhou. In the Proceedings of the 17th USENIX Security Symposium, July-August, 2008. San Jose, California. (16 pages) Acceptance Rate: 15.9% (27/170). [BIBTEX]

/* iComment: Bugs or Bad Comments? */ Lin Tan, Ding Yuan, Gopal Krishna and Yuanyuan Zhou. In the Proceedings of the 21st ACM Symposium on Operating Systems Principles, October 2007. Stevenson, Washington. (14 pages) Acceptance Rate: 19.1% (25/131). [BIBTEX] [In other people's words].

iKernel: Isolating Buggy and Malicious Device Drivers Using Hardware Virtualization Support. Lin Tan, Ellick M. Chan, Reza Farivar, Nevedita Mallick, Jeffrey C. Carlyle, Francis M. David and Roy H. Campbell. In the Proceedings of the 3rd IEEE International Symposium on Dependable, Autonomic and Secure Computing, September 2007. Columbia, Maryland. (9 pages) [BIBTEX]

HotComments: How to Make Program Comments More Useful? Lin Tan, Ding Yuan and Yuanyuan Zhou. In the Proceedings of the 11th Workshop on Hot Topics in Operating Systems, May 2007. San Diego, California. (6 pages) Acceptance Rate: 20.0% (21/105). [BIBTEX]

Architectures for Bit-Split String Scanning in Intrusion Detection. Lin Tan and Timothy Sherwood. IEEE Micro: Top Picks from Computer Architecture Conferences, January-February 2006. (8 pages) Acceptance Rate: 16.3% (13/80). [BIBTEX]

Bit-Split String Matching Engines for Intrusion Detection and Prevention. Lin Tan, Brett Brotherton and Timothy Sherwood. ACM Transactions on Architecture and Code Generation, 2006. (32 pages) [BIBTEX]

Have Things Changed Now? - An Empirical Study of Bug Characteristics in Modern Open Source Software. Zhenmin Li, Lin Tan, Xuanhui Wang, Shan Lu, Yuanyuan Zhou and Chengxiang Zhai. In the proceedings of the First Workshop on Architectural and System Support for Improving Software Dependability held together with ASPLOS, October 2006. San Jose, California. (9 pages) [BIBTEX]

Hibernator: Helping Disk Arrays Sleep Through the Winter. Qingbo Zhu, Zhifeng Chen, Lin Tan, Yuanyuan Zhou, Kimberly Keeton and John Wilkes. In the proceedings of the 20th ACM Symposium on Operating Systems Principles, October 2005. Brighton, United Kingdom. (14 pages) Acceptance Rate: 12.9% (20/155). [BIBTEX]

BugBench: A Benchmark for Evaluating Bug Detection Tools. Shan Lu, Zhenmin Li, Feng Qin, Lin Tan, Pin Zhou and Yuanyuan Zhou. In Workshop on the Evaluation of Software Defect Detection Tools Co-located with PLDI, June 2005. Chicago, Illinois. (5 pages) [BIBTEX]