Machine Translation from Natural Language to Code Using Long-Short Term Memory

Author:

Rahit K. M. Tahsin Hassan,Nabil Rashidul Hasan,Huq Md Hasibul

Publisher

Springer International Publishing

Reference12 articles.

1. Allamanis, M., Barr, E.T., Devanbu, P., Sutton, C.: A survey of machine learning for big code and naturalness. CoRR abs/1709.0 (2017). http://arxiv.org/abs/1709.06182

2. Birch, A., Osborne, M., Koehn, P.: Predicting success in machine translation. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing - EMNLP 2008, pp. 745–754, October 2008. https://doi.org/10.3115/1613715.1613809

3. George, D., Priyanka Girase, N., Mahesh Gupta, N., Prachi Gupta, N., Aakanksha Sharma, N., Navi, V.: Programming language inter-conversion. Int. J. Comput. Appl. 1(20), 975–8887 (2010). https://doi.org/10.5120/419-619

4. Gvero, T., Kuncak, V., Gvero, T., Kuncak, V.: Synthesizing Java expressions from free-form queries. In: Proceedings of the 2015 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications - OOPSLA 2015, vol. 50, pp. 416–432. ACM Press, New York (2015). http://dl.acm.org/citation.cfm?doid=2814270.2814295

5. Klein, G., Kim, Y., Deng, Y., Senellart, J., Rush, A.M., Seas, H.: OpenNMT: open-source toolkit for neural machine translation. In: Proceedings of the ACL, pp. 67–72 (2017). https://doi.org/10.18653/v1/P17-4012

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