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Volume 14, No. 12

Interactive Demonstration of SQLCHECK

Authors:
Arthita Ghosh (Georgia Institute Of Technology), Deven Bansod (Georgia Institute of Technology), Arpit Narechania (Georgia Institute of Technology), Visweswara Sai Prashanth Dintyala (Georgia Institute of Technology), Su Timurturkan (Georgia Institute of Technology), Joy Arulraj (Georgia Tech)

Abstract

We will demonstrate a prototype of SQLCHECK, a holistic toolchain for automatically finding and fixing anti-patterns in database applications. The advent of modern database-as-a-service platforms has made it easy for developers to quickly create scalable applications.However, it is still challenging for developers to design performant, maintainable, and accurate applications. This is because developers may unknowingly introduce anti-patterns in the application’s SQL statements. These anti-patterns are design decisions that are intended to solve a problem, but often lead to other problems by violating fundamental design principles. SQLCHECK leverages techniques for automatically: (1) detecting anti-patterns with high accuracy, (2) ranking them based on their impact on performance, maintainability, and accuracy of applications, and (3) suggesting alternative queries and changes to the data-base design to fix these anti-patterns. We will show how SQLCHECK suggests fixes for high-impact anti-patterns using rule-based query refactoring techniques. We will demonstrate that SQLCHECK enables developers to create more performant, maintainable, and accurate applications. We will show the prevalence of these anti-patterns in a large collection of queries and databases collected from open-source repositories.

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