Dynamic inference of static types for ruby

There have been several efforts to bring static type inference to object-oriented dynamic languages such as Ruby, Python, and Perl. In our experience, however, such type inference systems are extremely difficult to develop, because dynamic languages are typically complex, poorly specified, and include features, such as eval and reflection, that are hard to analyze. In this paper, we introduce constraint-based dynamic type inference, a technique that infers static types based on dynamic program executions. In our approach, we wrap each run-time value to associate it with a type variable, and the wrapper generates constraints on this type variable when the wrapped value is used. This technique avoids many of the often overly conservative approximations of static tools, as constraints are generated based on how values are used during actual program runs. Using wrappers is also easy to implement, since we need only write a constraint resolution algorithm and a transformation to introdu...

• Type: Journal
• Year: 2011
• Where: POPL
• Authors: Jong-hoon (David) An, Avik Chaudhuri, Jeffrey S. Foster, Michael Hicks
• Keywords: Inference Systems, POPL 2011, Programming Languages, Ruby Python, Static Type Inference