Privacy Preserving Data Generation for Database Application Performance Testing

نویسندگان

  • Yongge Wang
  • Xintao Wu
  • Yuliang Zheng
چکیده

Synthetic data plays an important role in software testing. In this paper, we initiate the study of synthetic data generation models for the purpose of application software performance testing. In particular, we will discuss models for protecting privacy in synthetic data generations. Within this model, we investigate the feasibility and techniques for privacy preserving synthetic database generation that can be used for database application performance testing. The methodologies that we will present will be useful for general privacy preserving software performance testing.

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تاریخ انتشار 2004