We present batch-based consistency, a new approach for consistency optimization that allows programmers to specialize consistency with application-level integrity properties. We implement the approach with a two-step process: we statically infer optimal consistency requirements for executions of bounded sets of operations, and then, use the inferred requirements to parameterize a new distributed protocol to relax operation reordering at run time when it is safe to do so. Our approach supports standard notions of consistency. We implement batch-based consistency in Peepco , demonstrate its expressiveness for partial data replication, and examine Peepco’s run-time performance impact in different settings.

@article{paperbot3164,
  title = {Peepco: Batch-Based Consistency Optimization},
  author = {Ivan Kuraj and John Feser and Nadia Polikarpova and Armando Solar-Lezama},
  journal = {Proceedings of the ACM on Programming Languages},
  volume = {9},
  number = {OOPSLA1},
  year = {2025},
  doi = {10.1145/3720513}
}