Types for Grassroots Logic Programs

TL;DR

This paper introduces a type system for Grassroots Logic Programs (GLP), enabling the formal typing of complex, multidirectional communication in concurrent logic programming, with implementation in Dart.

Contribution

It defines a new type system based on regular sets of moded paths, capturing communication directionality, and demonstrates its implementation and potential for AI-assisted programming.

Findings

Defined well-typing criteria for GLP programs.

Proved program correctness iff path semantics satisfy covariance and contravariance.

Implemented the type system in Dart with AI-generated specifications.

Abstract

Grassroots Logic Programs (GLP) is a concurrent logic programming language in which logic variables are partitioned into paired readers and writers. An assignment is produced at most once via a writer and consumed at most once via its paired reader, and may contain additional readers and/or writers. This enables the concise expression of rich multidirectional communication modalities. ``Logic Programs as Types for Logic Programs'' (LICS'91) defined types as regular sets of paths over derivable ground atoms. Here, we define types to be regular sets of moded paths, where a mode captures directionality of communication -- whether a subterm is consumed from or produced to the environment -- enabling the typing of interactive partial computations including those that eventually deadlock or fail, or never terminate. We provide a syntactic definition of well-typing and prove that a program is well-typed iff the path abstraction of its moded-atom semantics satisfies covariance and contravariance conditions with respect to its type. The GLP type system was implemented in Dart by AI, starting from a mathematical specification of Typed GLP (this paper), deriving from it an English spec (written by AI), and from the spec deriving Dart code (by AI). While GLP is naturally untyped, the motivation for Typed GLP comes from programming with AI: Asking AI to program complex communication modalities in GLP (and in general) and hoping for the best is a tenuous strategy. The emerging discipline we advocate and employ is for the human designer and AI to jointly develop and agree upon (1)~GLP types; (2)~GLP procedure type declarations; (3)~informal (English) descriptions of the procedures; and only then let AI attempt to write (4)~GLP code based on those.