May 7-10, 2017 Asilomar, California
When people write programs in conventional programming languages, they over-specify how to solve the problem they have in mind. Over-specification prevents the language's implementation from making many optimization decisions, leaving programmers with this burden. In more declarative languages, programmers over-specify less, enabling the implementation to make more choices for them. As these decisions improve, programmers shift more attention from the implementation to their real problems. This process easily overshoots. When under-specified programs almost always work well enough, programmers rarely need to think about implementation details. As their understanding of implementation's choices atrophies, the controls provided so they can override these decisions become obscure.
Our declarative language project, Yedalog, is in the midst of this dilemma. The improvements in question make our users more productive, so we cannot simply retreat back towards over-specification. To proceed forward instead, we must meet some of the expectations we prematurely provoked, and our implementation's behavior must help users learn expectations more aligned with our intended semantics.
These are general issues. Discussing their concrete manifestation in Yedalog should help other declarative systems that come to face these issues.