Towards Hybrid and Reusable Type Inference for Dynamically-Typed Languages - Safina, Larisa (Anais do Congresso Ibero-Americano em Engenharia de Software (CIbSE), 2026)
Type inference is a technique for automatically reconstructing types before program execution in the absence of explicit type annotations. While it has been adopted in many statically typed languages, applying type inference to dynamically-typed languages, poses challenges due to their runtime-oriented typing mechanisms. In this paper, we present HYPHE, a Hybrid Type Inference and Validation Framework for dynamically-typed languages, designed to combine within a single environment various approaches to type inference to leverage the strengths of each. HYPHE infers, stores, compares, and refines type information in a continuous loop integrated with developers. A preliminary evaluation in the Pharo Smalltalk environment indicates that combining multiple inference sources, as established in prior works, achieves broad type coverage while shifting computationally intensive analyses to offline processing and reusing accumulated inference data.