  Fully Homomorphic Encryption (FHE) allows a third party to perform arbitrary
computations on encrypted data, learning neither the inputs nor the computation
results. Hence, it provides resilience in situations where computations are
carried out by an untrusted or potentially compromised party. This powerful
concept was first conceived by Rivest et al. in the 1970s. However, it remained
unrealized until Craig Gentry presented the first feasible FHE scheme in 2009.
  The advent of the massive collection of sensitive data in cloud services,
coupled with a plague of data breaches, moved highly regulated businesses to
increasingly demand confidential and secure computing solutions. This demand,
in turn, has led to a recent surge in the development of FHE tools. To
understand the landscape of recent FHE tool developments, we conduct an
extensive survey and experimental evaluation to explore the current state of
the art and identify areas for future development.
  In this paper, we survey, evaluate, and systematize FHE tools and compilers.
We perform experiments to evaluate these tools' performance and usability
aspects on a variety of applications. We conclude with recommendations for
developers intending to develop FHE-based applications and a discussion on
future directions for FHE tools development.
