… When trained, DeepTyper can infer types for identifiers that the compiler’s type inference …
real-world type annotations in a large body of code. DeepTyper suggests type annotations with …

… information in type dependency graphs (TDGs). Based on TDGs, we can easily integrate
type inference rules in the nodes to conduct static inference and type rejection rules to inspect …

… to train a deep neural network, which ranks each type with probabilities effectively. … deep
learning with static analysis to infer type annotations is promising. By combining deep learning …

… high developer productivity, types need to be inferred. In this paper, we present DLTPy: a
deep learning type inference solution for the prediction of types in function signatures based on …

… a deep learning type inference technique, namely DLInfer, to automatically infer the type
infor… recurrent unit model to learn the type propagation information for inference. To validate the …

… Therefore, in this study, we investigate the deep learning-based type inference system … as
dataset shifts, influence the results of the type inference system. Cross-domain means that the …

… As retrofitting types to existing codebases is error-prone and laborious, machine learning
(ML)-based approaches have been proposed to enable automatic type inference based on …

… few-shot generative type inference approach that incorporates … (COT) prompts by translating
the type inference steps of static … Supervised type inference approaches utilizing deep learn…

… inference in other scenarios [3… type inference from the bytecode of smart contracts because
they target the source code. In this paper, we present DeepInfer, a novel deep learning-…

… models for Javascript and Python, but their approaches do not take advantage of deep
learning and are limited to a very restricted prediction space. Hellendoorn et al. (2018) and …