Fast type reconstruction for dynamically typed programming languages

Abstract

Type inference and type reconstruction derive static types for program elements that have no static type associated with them. They have a wide range of usage, such as helping to eliminate the burden of manually specifying types, verifying whether a program is type-safe, helping to produce more optimized code or helping to understand programs. While type inference and type reconstruction is an active field of research, most existing techniques are interested foremost in the precision of their approaches, at the expense of execution speed. As a result, existing approaches are not suited to give direct feedback in development environments, where interactivity dictates very fast approaches. This paper presents a type reconstruction algorithm for variables that is extremely fast (in the order of milliseconds) and reasonably precise (75 percent). The system is implemented as a byte-code evaluator in several Smalltalk environments, and its execution speed and precision are validated on a number of concrete case studies.

Mining the Ecosystem to Improve Type Inference for Dynamically Typed Languages

“…To better understand the contributions of this paper, we take a look at an existing three-step approach to type inference [20]. We start from this approach because it is simple to understand and implement, is reasonably fast and is representative of its field.…”

“…Merging the results from phases one and two into the final type results for the variable. Several different ways exist to do the merge [20], but we focus on the one that gives priority to the assignment type, and moves to interface types if an assignment type does not exist .…”

“…Obviously in cases like this, the information provided to the developer is not helpful. Pluquet et al show that on average less than 40% of instance variables from their evaluation receive enough messages and initializations to successfully infer one possible type [20].…”

Challenges to support automated random testing for dynamically typed languages

“…To know the argument type, one possibility is to use type inference. Different approaches are possible: lightweight with low precision [PMW09] or heavy computation (and with the problem of the availability of the approach) [SS04]. We believe that a lightweight approach is a first step to be used.…”

“…One of the first actions to be done is to use type inference to get some type information. The minimum is to use a simple static analysis as proposed by RoelTyper [PMW09].…”