Two Approximate-Programmability Birds, One Statistical-Inference Stone

We describe two central problems in the programmability of approximate systems—assisted approximate programming and dynamic check generation—and argue that they are, in fact, different views on the same underlying challenge. The common underpinning is the problem of statistical inference over probabilistic programs. We suggest research avenues borrowing from probabilistic programming that can help address the general problem.