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Predicting the runtime complexity of a programming code is an arduous task.
Chen, Z., Monperrus, M.: A literature study of embeddings on source code. CoRR abs/1904.03061
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Le, Q.V., Mikolov, T.: Distributed representations of sentences and documents (2014)
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Srikant, S., Aggarwal, V.: A system to grade computer programming skills using machine learning. In: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. pp. 1887–1896. KDD ’14, ACM, New York, NY, USA (2014). https://doi.org/10.1145/2623330.2623377, http://doi.acm.org/10.1145/2623330.2623377
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Allamanis, M., Peng, H., Sutton, C.: A convolutional attention network for extreme summarization of source code. In: Balcan, M.F., Weinberger, K.Q. (eds.) Proceedings of The 33rd International Conference on Machine Learning. Proceedings of Machine Learning Research, vol. 48, pp. 2091–2100. PMLR, New York, New York, USA (20–22 Jun 2016), http://proceedings.mlr.press/v48/allamanis16.html
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Li, J., He, P., Zhu, J., Lyu, M.R.: Software defect prediction via convolutional neural network. 2017 IEEE International Conference on Software Quality, Reliability and Security (QRS) pp. 318–328 (2017)
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Markovtsev, V., Long, W.: Public git archive: a big code dataset for all. CoRR abs/1803.10144
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Yin, P., Deng, B., Chen, E., Vasilescu, B., Neubig, G.: Learning to mine aligned code and natural language pairs from stack overflow. In: International Conference on Mining Software Repositories. pp. 476–486. MSR, ACM (2018). https://doi.org/https://doi.org/10.1145/3196398.3196408
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Alon, U., Zilberstein, M., Levy, O., Yahav, E.: Code2vec: Learning distributed representations of code. Proc. ACM Program. Lang. 3
2019
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2017
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2018
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Are runtime bounds in p decidable? (answer: no) https://cstheory.stackexchange.com/questions/5004/are-runtime-bounds-in-p-decidable-answer-no
Cited in the paper.
Graph2vec implementation https://github.com/MLDroid/graph2vec_tf
Cited in the paper.
More additional results at https://github.com/midas-research/corcod-dataset
Cited in the paper.
Sun, Z., Zhu, Q., Mou, L., Xiong, Y., Li, G., Zhang, L.: A grammar-based structural cnn decoder for code generation. Proceedings of the AAAI Conference on Artificial Intelligence 33
2019
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