  The adoption of differential privacy is growing but the complexity of
designing private, efficient and accurate algorithms is still high. We propose
a novel programming framework and system, Ektelo, for implementing both
existing and new privacy algorithms. For the task of answering linear counting
queries, we show that nearly all existing algorithms can be composed from
operators, each conforming to one of a small number of operator classes. While
past programming frameworks have helped to ensure the privacy of programs, the
novelty of our framework is its significant support for authoring accurate and
efficient (as well as private) programs.
  After describing the design and architecture of the Ektelo system, we show
that Ektelo is expressive, allows for safer implementations through code reuse,
and that it allows both privacy novices and experts to easily design
algorithms. We demonstrate the use of Ektelo by designing several new
state-of-the-art algorithms.
