SHF: Small: Collaborative Research: Preserving Test Coverage While Achieving Data Anonymity for Database-Centric Applications

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Software engineers often do not get access to confidential data because of internal security rules that are put in place by organizations that own these data and because of several laws that regulate data protection and privacy. This situation complicates basic software engineering tasks such as testing. To give some access to required data, data owners typically use a commercial tool to anonymize or "sanitize" the data. Unfortunately, none of the existing tools takes into account basic software engineering tasks such as testing, which leads to situations where the anonymized data is of little to no value for software engineers. Currently, software engineers operate with little or no meaningful data, which is a great obstacle to creating high quality software. This research program addresses a fundamental question of software engineering: how can a data owner protect private information so that the data subjects (e.g., persons, equipment) cannot be re-identified while the data retains their efficacy for software engineering tasks? To preserve the usefulness of data for software engineering tasks, algorithms are needed that take into account the structures of the applications. This work will lay a foundation for a new direction of research on interactions between software engineering and data privacy, and the PIs will support it with a set of tools for low-cost software development and evolution.