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The Recurrent Neural Network for Program Synthesis

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Digital Technologies and Applications (ICDTA 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 211))

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Abstract

The program synthesis is a new and ambitious field consists of generating from short and natural descriptions a source code. The program synthesis is rapidly becoming a popular research problem, interesting potential has been offered by using artificial intelligence to support new tools in almost all areas of program analysis and software engineering. The goal of our long-term research project is to enable and facilitate any user to create an application from a description written in natural language by specifying the need for a complete system. This involves carrying out a study of the user's needs, the design and implementation of an intelligent system allowing the automatic realization of an Informatic project (architecture, initialization scripts, configuration, etc.) expressed in natural language. We propose a recurrent neural network with LSTM cells and we publish a dataset of more than 145 765 questions and their best answer, especially in Java. The performance of the proposed model is very interesting such that the success rate is 94%.

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Author information

Authors and Affiliations

  1. INSA Euro-Mediterranean UEMF, Fez, Morocco

    Achraf Berrajaa

  2. Novelis Lab, Paris, France

    El Hassane Ettifouri

Authors
  1. Achraf Berrajaa
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  2. El Hassane Ettifouri
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Corresponding author

Correspondence to Achraf Berrajaa .

Editor information

Editors and Affiliations

  1. ENSA, Sidi Mohamed Ben Abdellah University, Fez, Morocco

    Saad Motahhir

  2. Faculty of Sciences, Sidi Mohamed Ben Abdellah University, Fez, Morocco

    Badre Bossoufi

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Berrajaa, A., Ettifouri, E.H. (2021). The Recurrent Neural Network for Program Synthesis. In: Motahhir, S., Bossoufi, B. (eds) Digital Technologies and Applications. ICDTA 2021. Lecture Notes in Networks and Systems, vol 211. Springer, Cham. https://doi.org/10.1007/978-3-030-73882-2_8

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