Testing software in age of data privacy

Abstract

Database-centric applications (DCAs) are common in enterprise computing, and they use nontrivial databases. Testing of DCAs is increasingly outsourced to test centers in order to achieve lower cost and higher quality. When proprietary DCAs are released, their databases should also be made available to test engineers. However, different data privacy laws prevent organizations from sharing this data with test centers because databases contain sensitive information. Currently, testing is performed with anonymized data, which often leads to worse test coverage (such as code coverage) and fewer uncovered faults, thereby reducing the quality of DCAs and obliterating benefits of test outsourcing. To address this issue, we offer a novel approach that combines program analysis with a new data privacy framework that we design to address constraints of software testing. With our approach, organizations can balance the level of privacy with needs of testing. We have built a tool for our approach and applied it to nontrivial Java DCAs. Our results show that test coverage can be preserved at a higher level by anonymizing data based on their effect on corresponding DCAs.