1 |
YAO Z, PEDDAMAIL J R, SUN H. CoaCor: code annotation for code retrieval with reinforcement learning [C]// Proceedings of the 2019 World Wide Web Conference. Republic and Canton of Geneva: International World Wide Web Conferences Steering Committee, 2019: 2203-2214. 10.1145/3308558.3313632
|
2 |
WAN Y, SHU J, SUI Y, et al. Multi-modal attention network learning for semantic source code retrieval [C]// Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering. Piscataway: IEEE, 2019: 13-25. 10.1109/ase.2019.00012
|
3 |
GU X, ZHANG H, KIM S. Deep code search [C]// Proceedings of the ACM/IEEE 40th International Conference on Software Engineering. New York: ACM, 2018: 933-944. 10.1145/3180155.3180167
|
4 |
YU Z, YU J, XIANG C, et al. Beyond bilinear: generalized multimodal factorized high-order pooling for visual question answering [J]. IEEE Transactions on Neural Networks and Learning Systems, 2018, 29(12): 5947-5959. 10.1109/tnnls.2018.2817340
|
5 |
LI L, DONG R, CHEN L. Context-aware co-attention neural network for service recommendations [C]// Proceedings of the IEEE 35th International Conference on Data Engineering Workshops. Piscataway: IEEE, 2019: 201-208. 10.1109/icdew.2019.00-11
|
6 |
LI B, SUN Z, LI Q, et al. Group-wise deep object co-segmentation with co-attention recurrent neural network [C]// Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision. Piscataway: IEEE, 2019: 8518-8527. 10.1109/iccv.2019.00861
|
7 |
HE K, ZHANG X, REN S, et al. Deep residual learning for image recognition[C]// Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2016: 770-778. 10.1109/cvpr.2016.90
|
8 |
HUSAIN H, WU HH, GAZIT T, et al. CodeSearchNet challenge: evaluating the state of semantic code search [EB/OL]. [2022-09-12]..
|
9 |
CAMBRONERO J, LI H, KIM S, et al. When deep learning met code search[C]// Proceedings of the 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering. New York: ACM, 2019: 964-974. 10.1145/3338906.3340458
|
10 |
XU L, YANG H, LIU C, et al. Two-stage attention-based model for code search with textual and structural features[C]// Proceedings of the 2021 IEEE International Conference on Software Analysis, Evolution and Reengineering. Piscataway: IEEE, 2021: 342-353. 10.1109/saner50967.2021.00039
|
11 |
GU J, CHEN Z, MONPERRUS M. Multimodal representation for neural code search[C]// Proceedings of the 2021 IEEE International Conference on Software Maintenance and Evolution. Piscataway: IEEE, 2021: 483-494. 10.1109/icsme52107.2021.00049
|
12 |
LV F, ZHANG H, LOU J G, et al. CodeHow: effective code search based on API understanding and extended Boolean model (E)[C]// Proceedings of the 30th IEEE/ACM International Conference on Automated Software Engineering. Piscataway: IEEE, 2015: 260-270. 10.1109/ase.2015.42
|
13 |
LU M, SUN X, WANG S, et al. Query expansion via WordNet for effective code search[C]// Proceedings of the IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering. Piscataway: IEEE, 2015: 545-549. 10.1109/saner.2015.7081874
|
14 |
LEMOS O A L, DE PAULA A C, ZANICHELLI F C, et al. Thesaurus-based automatic query expansion for interface-driven code search [C]// Proceedings of the 11th Working Conference on Mining Software Repositories. New York: ACM, 2014: 212-221. 10.1145/2597073.2597087
|
15 |
LIU J, KIM S, MURALI V, et al. Neural query expansion for code search[C]// Proceedings of the 3rd ACM SIGPLAN International Workshop on Machine Learning and Programming Languages. New York: ACM, 2019: 29-37. 10.1145/3315508.3329975
|
16 |
WANG C, NONG Z, GAO C, et al. Enriching query semantics for code search with reinforcement learning[J]. Neural Networks, 2022, 145: 22-32. 10.1016/j.neunet.2021.09.025
|
17 |
ZOU Q, ZHANG C. Query expansion via learning change sequences[J]. International Journal of Knowledge-based and Intelligent Engineering Systems, 2020, 24(2): 95-105. 10.3233/kes-200033
|
18 |
HU G, PENG M, ZHANG Y, et al. Unsupervised software repositories mining and its application to code search[J]. Software: Practice and Experience, 2020, 50(3): 299-322. 10.1002/spe.2760
|
19 |
WU H, YANG Y. Code search based on alteration intent[J]. IEEE Access, 2019, 7: 56796-56802. 10.1109/access.2019.2913560
|
20 |
WANG H, ZHANG J, XIA Y, et al. COSEA: convolutional code search with layer-wise attention [EB/OL]. [2022-09-12].. 10.48550/arXiv.2010.09520
|
21 |
LING X, WU L, WANG S, et al. Deep graph matching and searching for semantic code retrieval[J]. ACM Transactions on Knowledge Discovery from Data, 2021, 15(5): No.88. 10.1145/3447571
|
22 |
WANG W, LI G, MA B, et al. Detecting code clones with graph neural network and flow-augmented abstract syntax tree[C]// Proceedings of the IEEE 27th International Conference on Software Analysis, Evolution and Reengineering. Piscataway: IEEE, 2020: 261-271. 10.1109/saner48275.2020.9054857
|
23 |
夏冰,庞建民,周鑫,等.二进制代码相似性搜索研究进展[J]. 计算机应用, 2022, 42(4):985-998. 10.11772/j.issn.1001-9081.2021071267
|
|
XIA B, PANG J M, ZHOU X, et al. Research progress on binary code similarity search[J]. Journal of Computer Applications, 2022, 42(4):985-998. 10.11772/j.issn.1001-9081.2021071267
|
24 |
ZHANG J, WANG X, ZHANG H, et al. A novel neural source code representation based on abstract syntax tree [C]// Proceedings of the IEEE/ACM 41st International Conference on Software Engineering. Piscataway: IEEE, 2019: 783-794. 10.1109/icse.2019.00086
|
25 |
LING C, LIN Z, ZOU Y, et al. Adaptive deep code search [C]// Proceedings of the 28th International Conference on Program Comprehension. New York: ACM, 2020: 48-59. 10.1145/3387904.3389278
|
26 |
MA H, LI Y, JI X, et al. MsCoa: multi-step co-attention model for multi-label classification [J]. IEEE Access, 2019, 7: 109635-109645. 10.1109/access.2019.2933042
|
27 |
ZHANG P, ZHU H, XIONG T, et al. Co-attention network and low-rank bilinear pooling for aspect based sentiment analysis [C]// Proceedings of the 2019 IEEE International Conference on Acoustics, Speech and Signal Processing. Piscataway: IEEE, 2019: 6725-6729. 10.1109/icassp.2019.8682248
|
28 |
SHUAI J, XU L, LIU C, et al. Improving code search with co-attentive representation learning[C]// Proceedings of the 28th International Conference on Program Comprehension. New York: ACM, 2020: 196-207. 10.1145/3387904.3389269
|
29 |
SHWARTZ-ZIV R, TISHBY N. Opening the black box of deep neural networks via information [EB/OL]. [2022-09-12]..
|
30 |
BELGHAZI M I, BARATIN A, RAJESWAR S, et al. Mutual information neural estimation[C]// Proceedings of the 35th International Conference on Machine Learning. New York: JMLR.org, 2018: 531-540.
|