Partial Rewriting and Value Interpretation of Logically Constrained Terms (Full Version)
Takahito Aoto, Naoki Nishida, Jonas Sch\"opf

TL;DR
This paper introduces partial constrained rewriting for logically constrained term rewrite systems, compares it with existing methods, and proposes a novel value interpretation to clarify their differences.
Contribution
It presents the concept of partial constrained rewriting, analyzes its relation to existing constrained rewriting, and introduces value interpretation for better understanding.
Findings
Establishes a correspondence between partial and most general constrained rewriting.
Provides characterizations of constrained rewriting using instantiation interpretation.
Introduces a new value interpretation to distinguish subtle differences.
Abstract
Logically constrained term rewrite systems (LCTRSs) are a rewriting formalism that naturally supports built-in data structures, including integers and bit-vectors. The recent framework of existentially constrained terms and most general constrained rewriting on them (Takahata et al., 2025) has many advantages over the original approach of rewriting constrained terms. In this paper, we introduce partial constrained rewriting, a variant of rewriting existentially constrained terms whose underlying idea has already appeared implicitly in previous analyses and applications of LCTRSs. We examine the differences between these two notions of constrained rewriting. First, we establish a direct correspondence between them, leveraging subsumption and equivalence of constrained terms where appropriate. Then we give characterizations of each of them, using the interpretation of existentially…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsLogic, programming, and type systems · Scientific Computing and Data Management · Security and Verification in Computing
