Modernizing SMT-Based Type Error Localization

Abstract

Traditional implementations of strongly-typed functional programming languages often miss the root cause of type errors. As a consequence, type error messages are often misleading and confusing - particularly for students learning such a language. We describe Tyro, a type error localization tool which determines the optimal source of an error for ill-typed programs following fundamental ideas by Pavlinovic et al. : we first translate typing constraints into SMT (Satisfiability Modulo Theories) using an intermediate representation which is more readable than the actual SMT encoding; during this phase we apply a new encoding for polymorphic types. Second, we translate our intermediate representation into an actual SMT encoding and take advantage of recent advancements in off-the-shelf SMT solvers to effectively find optimal error sources for ill-typed programs. Our design maintains the separation of heuristic and search also present in prior and similar work. In addition, our architecture design increases modularity, re-usability, and trust in the overall architecture using an intermediate representation to facilitate the safe generation of the SMT encoding. We believe this design principle will apply to many other tools that leverage SMT solvers. Our experimental evaluation reinforces that the SMT approach finds accurate error sources using both expert-labeled programs and an automated method for larger-scale analysis. Compared to prior work, Tyro lays the basis for large-scale evaluation of error localization techniques, which can be integrated into programming environments and enable us to understand the impact of precise error messages for students in practice.