Automated SQL query generation for systematic testing of database engines

Abstract

We present a novel approach for generating syntactically and semantically correct SQL queries as inputs for testing relational databases. We leverage the SAT-based Alloy tool-set to reduce the problem of generating valid SQL queries into a SAT problem. Our approach translates SQL query constraints into Alloy models, which enable it to generate valid queries that cannot be automatically generated using conventional grammar-based generators. Given a database schema, our new approach combined with our previous work on ADUSA, automatically generates (1) syntactically and semantically valid SQL queries for testing, (2) input data to populate test databases, and (3) expected result of executing the given query on the generated data. Experimental results show that not only can we automatically generate valid queries which detect bugs in database engines, but also we are able to combine this work with our previous work on ADUSA to automatically generate input queries and tables as well as expected query execution outputs to enable automated testing of database engines.