We present Typpete, a sound type inferencer that automatically infers Python 3 type annotations. Typpete encodes type constraints as a MaxSMT problem and uses optional constraints and specific quantifier instantiation patterns to make the constraint solving process efficient. Our experimental evaluation shows that Typpete scales to real world Python programs and outperforms state-of-the-art tools. This is the artifact accompanying the published paper
We present an O(n^3) time type inference algorithm for a typesystem with a largest type !, a smalles...
Highly dynamic languages like Smalltalk do not have much static type information immediately availab...
Contains fulltext : 83744.pdf (publisher's version ) (Open Access)MSFP'10 : third ...
In this paper, we present ManyTypes4Py, a large Python dataset for machine learning (ML)-based type ...
Check out the file ManyTypes4PyDataset.spec for repositories URL and their commit SHA. The dataset i...
Empirical data and code used in paper *Towards a Large-Scale Empirical Study of Python3 Type Annotat...
In dynamically typed programming languages, values have types, but vari-ables and other constructs i...
The dataset is gathered on Sep. 17th 2020 from GitHub. It has clean and complete versions (from v0....
In this paper, we present ManyTypes4TypeScript, a very large corpus for training and evaluating mach...
Dynamic programming languages (DPLs), such as Python and Ruby, are often used for their flexibility ...
This contains artifacts for the Type4Py paper, which is accepted at the ICSE'22 technical track. ...
This artifact contains the Appendix of the paper, proofs of theorems declared in the paper, and a sa...
This release teaches "from_type()" a neat trick: when resolving an "typing.Annotated" type, if one o...
Type inference is a key component of modern statically typed programming languages. It allows progra...
research.microsoft.com/Users/simonpj/ We present a novel inference algorithm for a type system featu...
We present an O(n^3) time type inference algorithm for a typesystem with a largest type !, a smalles...
Highly dynamic languages like Smalltalk do not have much static type information immediately availab...
Contains fulltext : 83744.pdf (publisher's version ) (Open Access)MSFP'10 : third ...
In this paper, we present ManyTypes4Py, a large Python dataset for machine learning (ML)-based type ...
Check out the file ManyTypes4PyDataset.spec for repositories URL and their commit SHA. The dataset i...
Empirical data and code used in paper *Towards a Large-Scale Empirical Study of Python3 Type Annotat...
In dynamically typed programming languages, values have types, but vari-ables and other constructs i...
The dataset is gathered on Sep. 17th 2020 from GitHub. It has clean and complete versions (from v0....
In this paper, we present ManyTypes4TypeScript, a very large corpus for training and evaluating mach...
Dynamic programming languages (DPLs), such as Python and Ruby, are often used for their flexibility ...
This contains artifacts for the Type4Py paper, which is accepted at the ICSE'22 technical track. ...
This artifact contains the Appendix of the paper, proofs of theorems declared in the paper, and a sa...
This release teaches "from_type()" a neat trick: when resolving an "typing.Annotated" type, if one o...
Type inference is a key component of modern statically typed programming languages. It allows progra...
research.microsoft.com/Users/simonpj/ We present a novel inference algorithm for a type system featu...
We present an O(n^3) time type inference algorithm for a typesystem with a largest type !, a smalles...
Highly dynamic languages like Smalltalk do not have much static type information immediately availab...
Contains fulltext : 83744.pdf (publisher's version ) (Open Access)MSFP'10 : third ...