Extending symbolic execution for automated testing of stored procedures

Stored procedures in database management systems are often used to implement complex business logic. Correctness of these procedures is critical for flawless working of the system. However, testing them remains difficult due to many possible database states and constraints on data. This leads to mostly manual testing. Newer tools offer automated execution for unit testing of stored procedures but the test cases are still written manually. We propose an approach of using dynamic symbolic execution for generating automated test cases and corresponding database states for stored procedures. We model the constraints on data imposed by the schema and the SQL statements, treating values in database tables as symbolic. We use SMT solver to find values that will drive the stored procedure on a particular execution path. We instrument the internal execution plans generated by PostgreSQL to extract constraints. We use Z3 to generate test cases consisting of table data and procedure inputs. Our evaluation using stored procedures from a large business application and various GitHub repositories quantifies the evidence of effectiveness of our technique by generating test cases that lead to schema constraint violations and user-defined exceptions.