Profile-guided static typing for dynamic scripting languages

94 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Do Machine Learning Models Produce TypeScript Types that Type Check? (2023, neutral): “However, there are tools that use dynamic profiles to infer types for these type systems [1, 19, 45].”
Julia: A Fast Dynamic Language for Technical Computing (2012, background): “…on optimizing dynamic languages, researchers have observed that programs are not as dynamic as their authors might think: “We found that dynamic features are pervasive throughout the benchmarks and the libraries they include, but that most uses of these features are highly constrained...” [16].”
The ruby type checker (2013, background): “Several researchers have proposed adding static types and static type inference to various dynamically typed languages, including Ruby [9, 8], Python [5, 11, 3], and JavaScript [4, 14] among others.”
Dynamic inference of static types for ruby (2011, unknown): “We experienced this firsthand in our development of DRuby, a static type inference system for Ruby [3, 10, 12].”
Python probabilistic type inference with natural language support (2016, methodology): “DRuby [28] statically infers types for a subset of Ruby.”
The ins and outs of gradual type inference (2012, background): “Dynamic Inference of Static Types for Ruby.”
Solver-based gradual type migration (2021, methodology): “Some work uses run-time profiling to guide type inference [An et al. 2011; Furr et al. 2009; Saftoiu 2010].”