Searched for: subject%3A%22Type%255C%2BInference%22
(1 - 7 of 7)
document
feng, lang (author)
Type inference plays a pivotal role in modern software development as it aids in understanding code, detecting errors, and facilitating code completion. Two main approaches, static analysis, and machine learning, contribute to this process. Each approach has its own benefits and limitations. This thesis investigates the potential of combining...
master thesis 2023
document
Jakovonis, Saulius (author)
The success of dynamically typed languages such as Python has resulted in an increased interest in supporting type inference in statically typed lan- guages. Type inference refers to automatic type detection based on surrounding context and allows retaining the type safety (and other advantages) of static types, while matching the ease of use of...
bachelor thesis 2023
document
Stallenberg, Dimitri (author)
Traditional software testing is a labor-intensive and expensive manual process. To mitigate the high cost of manual test case generation, researchers have developed various techniques for automated test case generation over the last few decades. These techniques make use of static type information to determine which data types should be used in...
master thesis 2022
document
Al Haydar, Anhar (author)
Dynamic programming languages (DPLs), such as Python and Ruby, are often used for their flexibility and fast development. The absence of static typing can lead to runtime exceptions and reduced program understandability. To overcome these problems, some DPLs have introduced optional static typing. Because of the tedious effort of adding type...
bachelor thesis 2022
document
Mac Gillavry, Merlijn (author)
Researchers at the Delft University of Technology have developed Type4Py: a tool that uses Machine Learning to predict types for Python code. These predictions can be applied by developers to their python code to increase readability and can later be tested by a type-checker for possible type-errors. If a prediction does not return a type-error...
bachelor thesis 2022
document
Mir, S.A.M. (author), Latoskinas, Evaldas (author), Proksch, S. (author), Gousios, G. (author)
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...
conference paper 2022
document
Mir, S.A.M. (author), Latoskinas, Evaldas (author), Gousios, G. (author)
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...
conference paper 2021
Searched for: subject%3A%22Type%255C%2BInference%22
(1 - 7 of 7)