Y. Keneshloo, T. Shi, C. K. Reddy, and N. Ramakrishnan, “Deep reinforcement learning for sequence to sequence models,” arXiv preprint arXiv:1805.09461 , 2018
Original
2018
Later among the works it cites.
Y. Wan, Z. Zhao, M. Yang, G. Xu, H. Ying, J. Wu, and P. S. Yu, “Improving automatic source code summarization via deep reinforcement learning,” in Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering . ACM, 2018, pp. 397–407
2018
Later among the works it cites.
S. Luan, D. Yang, K. Sen, and S. Chandra, “Aroma: Code recommendation via structural code search,” arXiv preprint arXiv:1812.01158 , 2018
Original
2018
Later among the works it cites.
A. LeClair, S. Jiang, and C. McMillan, “A neural model for generating natural language summaries of program subroutines,” in Proceedings of the 41st International Conference on Software Engineering . IEEE Press, 2019, pp. 795–806
2019
Later among the works it cites.
Z. Yao, J. R. Peddamail, and H. Sun, “Coacor: Code annotation for code retrieval with reinforcement learning,” in The World Wide Web Conference . ACM, 2019, pp. 2203–2214
2019
Later among the works it cites.
X. Li, W. Li, Y. Zhang, and L. Zhang, “Deepfl: integrating multiple fault diagnosis dimensions for deep fault localization,” in Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis, ISSTA 2019, Beijing, China, July 15-19, 2019 , 2019, pp. 169–180. [Online]. Available: https://doi.org/10.1145/3293882.3330574
2019
Later among the works it cites.
M. Zhang, Y. Li, X. Li, L. Chen, Y. Zhang, L. Zhang, and S. Khurshid, “An empirical study of boosting spectrum-based fault localization via pagerank,” IEEE Transactions on Software Engineering , pp. 1–1, 2019
2019
Later among the works it cites.
A. Ghanbari, S. Benton, and L. Zhang, “Practical program repair via bytecode mutation,” in Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis, ISSTA 2019, Beijing, China, July 15-19, 2019 , 2019, pp. 19–30. [Online]. Available: https://doi.org/10.1145/3293882.3330559
2019
Later among the works it cites.
Y. Lou, J. Chen, L. Zhang, D. Hao, and L. Zhang, “History-driven build failure fixing: how far are we?” in Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis, ISSTA 2019, Beijing, China, July 15-19, 2019 , 2019, pp. 43–54. [Online]. Available: https://doi.org/10.1145/3293882.3330578
2019
Later among the works it cites.
J. Hua, Y. Zhang, Y. Zhang, and S. Khurshid, “Edsketch: execution-driven sketching for java,” STTT , vol. 21, no. 3, pp. 249–265, 2019. [Online]. Available: https://doi.org/10.1007/s10009-019-00512-8
2019
Later among the works it cites.
M. Wu, L. Zhang, C. Liu, S. H. Tan, and Y. Zhang, “Automating cuda synchronization via program transformation,” in 2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE) , Nov 2019, pp. 748–759
2019
Later among the works it cites.
T. Zheng, X. Zheng, Y. Zhang, Y. Deng, E. Dong, R. Zhang, and X. Liu, “Smartvm: a sla-aware microservice deployment framework,” World Wide Web , vol. 22, no. 1, pp. 275–293, 2019. [Online]. Available: https://doi.org/10.1007/s11280-018-0562-5
2019
Later among the works it cites.
D. Yu, Y. Jin, Y. Zhang, and X. Zheng, “A survey on security issues in services communication of microservices-enabled fog applications,” Concurr. Comput. Pract. Exp. , vol. 31, no. 22, 2019. [Online]. Available: https://doi.org/10.1002/cpe.4436
2019
Later among the works it cites.
S. A. Akbar and A. C. Kak, “Scor: source code retrieval with semantics and order,” in Proceedings of the 16th International Conference on Mining Software Repositories . IEEE Press, 2019, pp. 1–12
2019
Later among the works it cites.
Y. Sun, S. Wang, Y. Li, S. Feng, X. Chen, H. Zhang, X. Tian, D. Zhu, H. Tian, and H. Wu, “Ernie: Enhanced representation through knowledge integration,” arXiv preprint arXiv:1904.09223 , 2019
Original
2019
Later among the works it cites.
Z. Yang, Z. Dai, Y. Yang, J. Carbonell, R. Salakhutdinov, and Q. V. Le, “Xlnet: Generalized autoregressive pretraining for language understanding,” arXiv preprint arXiv:1906.08237 , 2019
Original
2019
Later among the works it cites.
X. Hu, G. Li, X. Xia, D. Lo, and Z. Jin, “Deep code comment generation with hybrid lexical and syntactical information,” Empirical Software Engineering , pp. 1–39, 2019
2019
Later among the works it cites.
A. Sivaraman, T. Zhang, G. Van den Broeck, and M. Kim, “Active inductive logic programming for code search,” in Proceedings of the 41st International Conference on Software Engineering . IEEE Press, 2019, pp. 292–303
2019
Later among the works it cites.
H. Zhou, W. Li, Z. Kong, J. Guo, Y. Zhang, B. Yu, L. Zhang, and C. Liu, “Deepbillboard: Systematic physical-world testing of autonomous driving systems,” in Proceedings of the 42nd International Conference on Software Engineering, ICSE 2020, Seoul, Korea, May 23 - 29, 2020 , 2020
2020
Closest in time.
M. Wu, Y. Ouyang, H. Zhou, L. Zhang, C. Liu, and Y. Zhang, “Simulee: Detecting cuda synchronization bugs via memory-access modeling,” in Proceedings of the 42nd International Conference on Software Engineering, ICSE 2020, Seoul, Korea, May 23 - 29, 2020 , 2020
2020
Closest in time.
W. Wang, Y. Zhang, Y. Sui, Y. Wan, Z. Zhao, J. Wu, P. Yu, and G. Xu, “Reinforcement-learning-guided source code summarization using hierarchical attention,” IEEE Transactions on Software Engineering , pp. 1–1, 2020
2020
Closest in time.
S. Iyer, I. Konstas, A. Cheung, and L. Zettlemoyer, “Summarizing source code using a neural attention model.” in Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (1) , 2016, pp. 2073–2083
2083
Closest in time.
M. Allamanis, H. Peng, and C. Sutton, “A convolutional attention network for extreme summarization of source code,” in International Conference on Machine Learning , 2016, pp. 2091–2100
2091
Closest in time.