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arXiv:1510.07211cs.SE

On End-to-End Program Generation from User Intention by Deep Neural Networks

Lili Mou, Rui Men, Ge Li, Lu Zhang, Zhi Jin

Early discovery. Linked by one identifiable commenter. This paper is outside the main ranking; a mention is not an endorsement.

Abstract

This paper envisions an end-to-end program generation scenario using recurrent neural networks (RNNs): Users can express their intention in natural language; an RNN then automatically generates corresponding code in a characterby-by-character fashion. We demonstrate its feasibility through a case study and empirical analysis. To fully make such technique useful in practice, we also point out several cross-disciplinary challenges, including modeling user intention, providing datasets, improving model architectures, etc. Although much long-term research shall be addressed in this new field, we believe end-to-end program generation would become a reality in future decades, and we are looking forward to its practice.

arXiv comments
Submitted to 2016 International Conference of Software Engineering "Vision of 2025 and Beyond" track
Journal reference
DOI
Subjects
cs.SESoftware Engineering cs.LGMachine Learning

On Hacker News

Linked by 1 identifiable commenter in 4 comments across 2 threads, from Jul 2016 to Jul 2016. Found in 2 HN submissions from Oct 2015 to Oct 2015. Open submission discussions.

Comments linking this paper, per year.

Discussed in comments2 threads

  1. How AI based programming could work 2 comments

    • The author proposes a lot of vague ideas in this article (for example "I believe one of the biggest problems is the use of Error Propagation and Gradient Descent") without references or any solid proofs why they are necessary to solve the proposed program (Automate programming…

      sapphireblueView on HNParent context

    • The corpus can be acquired from companies that host coding competitions. In this paper http://arxiv.org/pdf/1510.07211v1.pdf (I already mentioned it many times, but it is very relevant) researchers took the data from a similar source >To accomplish this goal, we leverage a…

      sapphireblueView on HNParent context

  2. The future is fewer people writing code? 2 comments

    • Seems like a gross overestimation of time needed for said advances and complexity of such systems. There is already a research-grade approach to learn to generate short programming-challenge-like programs from natural language description: http://arxiv.org/abs/1510.07211 >This…

      sapphireblueView on HNParent context

    • There are signs, if you know were to look for them: http://arxiv.org/abs/1510.07211 https://arxiv.org/abs/1410.4615 http://arxiv.org/abs/1605.06640 https://arxiv.org/abs/1410.5401

      sapphireblueView on HNParent context

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