Detecting DBMS bugs with context-sensitive instantiation and multi-plan execution

Abstract

DBMS (Database Management System) bugs can cause serious consequences, posing severe security and privacy concerns. This paper works towards the detection of crash-related bugs and logic bugs in DBMSs, and aims at solving the two innate challenges, including how to generate semantically correct SQL queries in a test case, and how to propose effective oracles to capture logic bugs. To this end, our system proposes two key techniques. The first key technique is called context-sensitive instantiation, which can obtain all static semantic requirements to guide query generation. The second key technique is called multi-plan execution, which can effectively capture logic bugs. Given a test case, multi-plan execution makes the DBMS execute all query plans instead of the default optimal one, and compares the results. A logic bug is detected if a difference is found among the execution results of the executed query plans. We have implemented a prototype system called Kangaroo and applied it to three widely used and well-tested DBMSs, including SQLite, PostgreSQL, and MySQL. Our system successfully detected 54 previously unknown bugs, including 41 crash-related bugs and 13 logic bugs. The comparison between our system with the state-of-the-art systems shows that our system outperforms them in terms of the number of generated semantically valid SQL queries, the explored code paths during testing, and the detected bugs.