STICCER: Fast and Effective Database Test Suite Reduction Through Merging of Similar Test Cases

Abstract

Since relational databases support many software applications, industry professionals recommend testing both database queries and the underlying database schema that contains complex integrity constraints. These constraints, which include primary and foreign keys, NOT NULL, and arbitrary CHECK constraints, are important because they protect the consistency and coherency of data in the relational database. Since testing integrity constraints is potentially an arduous task, human testers can use new tools to automatically generate test suites that effectively find schema faults. However, these tool-generated test suites often contain many lengthy tests that may both increase the time overhead of regression testing and limit the ability of human testers to understand them. Aiming to reduce the size of automatically generated test suites for database schemas, this paper introduces STICCER, a technique that finds overlaps between test cases, merging database interactions from similar tests and removing others. By systematically discarding and merging redundant tests, STICCER creates a reduced test suite that is guaranteed to have the same coverage as the original one. Using thirty-four relational database schemas, we experimentally compared STICCER to two greedy test suite reduction techniques and a random method. The results show that, compared to the greedy and random methods, STICCER is the most effective at reducing the number of test cases and database interactions while maintaining test effectiveness as measured by the mutation score.