Automatic Correction of Syntax Errors in SuperSQL Queries

Shunsuke Otawa, Kento Goto, Motomichi Toyama

研究成果: Conference contribution

抄録

SuperSQL is an extended language of SQL. By structuring the output of relational databases, SuperSQL enables the user to generate various types of structured documents with various layouts which are not represented in SQL. There is a problem that the larger and more complicated the SuperSQL query is, the more difficult it is to detect errors and the more time is spent on debugging. In this study, we propose a system that automatically detects and corrects syntax errors in user queries. When a query parsing fails, the system reanalyzes the query and predicts a correction by using deep learning. To modify the query, we use recurrent neural network and attention mechanism. By presenting the predicted modifications to users, the burden of debugging can be reduced and the efficiency of user's work can be improved.

本文言語English
ホスト出版物のタイトル22nd International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2020 - Proceedings
編集者Maria Indrawan-Santiago, Eric Pardede, Ivan Luiz Salvadori, Matthias Steinbauer, Ismail Khalil, Gabriele Kotsis
出版社Association for Computing Machinery
ページ28-33
ページ数6
ISBN(電子版)9781450389228
DOI
出版ステータスPublished - 2020 11 30
イベント22nd International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2020 - Virtual, Online, Thailand
継続期間: 2020 11 302020 12 2

出版物シリーズ

名前ACM International Conference Proceeding Series

Conference

Conference22nd International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2020
CountryThailand
CityVirtual, Online
Period20/11/3020/12/2

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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