| Coconut: combining context-aware neural translation models using ensemble for program repair T Lutellier, HV Pham, L Pang, Y Li, M Wei, L Tan Proceedings of the 29th ACM SIGSOFT international symposium on software …, 2020 | 399 | 2020 |
| Cure: Code-aware neural machine translation for automatic program repair N Jiang, T Lutellier, L Tan 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE …, 2021 | 384 | 2021 |
| Impact of code language models on automated program repair N Jiang, K Liu, T Lutellier, L Tan 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE …, 2023 | 194 | 2023 |
| CRADLE: cross-backend validation to detect and localize bugs in deep learning libraries HV Pham, T Lutellier, W Qi, L Tan 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE …, 2019 | 186 | 2019 |
| Problems and opportunities in training deep learning software systems: An analysis of variance HV Pham, S Qian, J Wang, T Lutellier, J Rosenthal, L Tan, Y Yu, ... Proceedings of the 35th IEEE/ACM international conference on automated …, 2020 | 162 | 2020 |
| Comparing software architecture recovery techniques using accurate dependencies T Lutellier, D Chollak, J Garcia, L Tan, D Rayside, N Medvidovic, ... 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering 2 …, 2015 | 127 | 2015 |
| How effective are neural networks for fixing security vulnerabilities Y Wu, N Jiang, HV Pham, T Lutellier, J Davis, L Tan, P Babkin, S Shah Proceedings of the 32nd ACM SIGSOFT International Symposium on Software …, 2023 | 96 | 2023 |
| Measuring the impact of code dependencies on software architecture recovery techniques T Lutellier, D Chollak, J Garcia, L Tan, D Rayside, N Medvidović, ... IEEE Transactions on Software Engineering 44 (2), 159-181, 2017 | 93 | 2017 |
| Are my deep learning systems fair? An empirical study of fixed-seed training S Qian, VH Pham, T Lutellier, Z Hu, J Kim, L Tan, Y Yu, J Chen, S Shah Advances in Neural Information Processing Systems 34, 30211-30227, 2021 | 59 | 2021 |
| Knod: Domain knowledge distilled tree decoder for automated program repair N Jiang, T Lutellier, Y Lou, L Tan, D Goldwasser, X Zhang 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE …, 2023 | 56 | 2023 |
| Effective detection of vulnerable and malicious browser extensions H Shahriar, K Weldemariam, M Zulkernine, T Lutellier Computers & Security 47, 66-84, 2014 | 42 | 2014 |
| Impact of code language models on automated program repair. In 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE) N Jiang, K Liu, T Lutellier, L Tan IEEE Computer Society, Los Alamitos, CA, USA, 1430-1442, 2023 | 35 | 2023 |
| EAGLE: creating equivalent graphs to test deep learning libraries J Wang, T Lutellier, S Qian, HV Pham, L Tan Proceedings of the 44th International Conference on Software Engineering …, 2022 | 31 | 2022 |
| On the correctness of electronic documents: studying, finding, and localizing inconsistency bugs in PDF readers and files T Kuchta, T Lutellier, E Wong, L Tan, C Cadar Empirical Software Engineering 23, 3187-3220, 2018 | 30 | 2018 |
| Encore: Ensemble learning using convolution neural machine translation for automatic program repair T Lutellier, L Pang, VH Pham, M Wei, L Tan arXiv preprint arXiv:1906.08691, 2019 | 26 | 2019 |
| A model-based detection of vulnerable and malicious browser extensions H Shahriar, K Weldemariam, T Lutellier, M Zulkernine 2013 IEEE 7th International Conference on Software Security and Reliability …, 2013 | 12 | 2013 |
| Machine Learning for Software Dependability T Lutellier University of Waterloo, 2020 | 1 | 2020 |
Lin TanMary J. Elmore New Frontiers Professor, Computer Science, Purdue UniversityVerificeret mail på purdue.edu