Using Text Classification Techniques to identify anti-patterns in SQL queries
| Author(s) | : | Dibyanshu Chatterjee, Niveditha CA |
| Institution | : | Department of computer science and engineering, Ms Ramaiah University of Applied Sciences, Bangalore |
| Published In | : | Vol. 7, Issue 11 — November 2020 |
| Page No. | : | 32-36 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
A significant issue with utilizing social information bases, is formulating and writing proficient SQLqueries. Some basic blunders known as anti-patterns are quite common in SQL queries and can genuinely affect itsexecution time and at times, the database's general execution. This paper manifests machine learning methods andidentifies anti-patterns by approaching the issue as a text classification issue. Our outcome is a model dependent on aconvolutional neural network that can be utilized to order a SQL query into zero, one or numerous anti-pattern classes.
Dibyanshu Chatterjee, Niveditha CA, “Using Text Classification Techniques to identify anti-patterns in SQL queries”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 7, Issue 11, pp. 32-36, November 2020.
