  We introduce a new application for inductive logic programming: learning the
semantics of programming languages from example evaluations. In this short
paper, we explored a simplified task in this domain using the Metagol
meta-interpretive learning system. We highlighted the challenging aspects of
this scenario, including abstracting over function symbols, nonterminating
examples, and learning non-observed predicates, and proposed extensions to
Metagol helpful for overcoming these challenges, which may prove useful in
other domains.
