One of the workhorse techniques for implementing bottom-up Datalog engines is seminaïve evaluation. This optimization improves the performance of Datalog's most distinctive feature: recursively defined predicates. These are computed iteratively, and under a naïve evaluation strategy, each iteration recomputes all previous values. Seminaïve evaluation computes a safe approximation of the difference between iterations. This can asymptotically improve the performance of Datalog queries. Seminaïve evaluation is defined partly as a program transformation and partly as a modified iteration strategy, and takes advantage of the first-order nature of Datalog code. This paper extends the seminaïve transformation to higher-order programs written in the Datafun language, which extends Datalog with features like first-class relations, higher-order functions, and datatypes like sum types.

@article{paperbot565,
  title = {Seminaïve evaluation for a higher-order functional language},
  author = {Michael Arntzenius and Neel Krishnaswami},
  journal = {Proceedings of the ACM on Programming Languages},
  volume = {4},
  number = {POPL},
  year = {2019},
  doi = {10.1145/3371090}
}