Type4Py: Practical Deep Similarity Learning-Based Type Inference for Python

Dynamic languages, such as Python and Javascript, trade static typing for developer flexibility and productivity. Lack of static typing can cause run-time exceptions and is a major factor for weak IDE support. To alleviate these issues, PEP 484 introduced optional type annotations for Python. As retrofitting types to existing code-bases is...

ManyTypes4Py: A benchmark python dataset for machine learning-based type inference

In this paper, we present ManyTypes4Py, a large Python dataset for machine learning (ML)-based type inference. The dataset contains a total of 5, 382 Python projects with more than 869K type annotations. Duplicate source code files were removed to eliminate the negative effect of the duplication bias. To facilitate training and evaluation of...

Shape based classification of seismic building structural types

This paper investigates automatic prediction of seismic building structural types described by the Global Earthquake Model (GEM) taxonomy, by combining remote sensing, cadastral and inspection data in a supervised machine learning approach. Our focus lies on the extraction of detailed geometric information from a point cloud gained by aerial...