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

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

Sun, 31 Jul 2016 20:27:19 GMT

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 dataset from a pedagogical programming online judge (OJ) system,2 intended for the undergraduate course, Introduction to Computing. The OJ system comprises different programming problems. Students submit their source code to a specific problem, and the OJ system judges its validity automatically (via running). And trained…

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

Sun, 31 Jul 2016 16:55:11 GMT

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 using ML?). In fact there is already a lot of solid work just on this subject: * Learning algorithms from examples http://arxiv.org/abs/1511.07275 https://arxiv.org/abs/1410.5401 * Generating source code from natural language description http://arxiv.org/abs/1510.07211 * And, the most closest work to what author…

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

Fri, 22 Jul 2016 20:12:54 GMT

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

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

Fri, 22 Jul 2016 20:00:44 GMT

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 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…

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

Thu, 29 Oct 2015 01:01:32 GMT

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

20 points; 1 discussion reply on HN. Paper and source history. A submission is not an endorsement.

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

Wed, 28 Oct 2015 11:23:39 GMT

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

1 point; 0 discussion replies on HN. Paper and source history. A submission is not an endorsement.