Search Results

Documents authored by Monat, Raphaël

Document
Front Matter
DOI: 10.4230/DARTS.10.2.0
Front Matter, Table of Contents, Preface, Conference Organization

Authors: Karine Even-Mendoza and Raphaël Monat

Published in: DARTS, Volume 10, Issue 2, Special Issue of the 38th European Conference on Object-Oriented Programming (ECOOP 2024)

Abstract
Front Matter, Table of Contents, Preface, Conference Organization
Cite as

Special Issue of the 38th European Conference on Object-Oriented Programming (ECOOP 2024). Dagstuhl Artifacts Series (DARTS), Volume 10, Issue 2, pp. 0:i-0:xii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

Copy BibTex To Clipboard

@Article{evenmendoza_et_al:DARTS.10.2.0,
  author =	{Even-Mendoza, Karine and Monat, Rapha\"{e}l},
  title =	{{Front Matter, Table of Contents, Preface, Conference Organization}},
  pages =	{0:i--0:xii},
  journal =	{Dagstuhl Artifacts Series},
  ISBN =	{978-3-95977-342-3},
  ISSN =	{2509-8195},
  year =	{2024},
  volume =	{10},
  number =	{2},
  editor =	{Even-Mendoza, Karine and Monat, Rapha\"{e}l},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DARTS.10.2.0},
  URN =		{urn:nbn:de:0030-drops-208982},
  doi =		{10.4230/DARTS.10.2.0},
  annote =	{Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
Artifact
DOI: 10.4230/DARTS.6.2.11
Static Type Analysis by Abstract Interpretation of Python Programs (Artifact)

Authors: Raphaël Monat, Abdelraouf Ouadjaout, and Antoine Miné

Published in: DARTS, Volume 6, Issue 2, Special Issue of the 34th European Conference on Object-Oriented Programming (ECOOP 2020)

Abstract
Python is an increasingly popular dynamic programming language, particularly used in the scientific community and well-known for its powerful and permissive high-level syntax. Our work aims at detecting statically and automatically type errors. As these type errors are exceptions that can be caught later on, we precisely track all exceptions (raised or caught). We designed a static analysis by abstract interpretation able to infer the possible types of variables, taking into account the full control-flow. It handles both typing paradigms used in Python, nominal and structural, supports Python’s object model, introspection operators allowing dynamic type testing, dynamic attribute addition, as well as exception handling. We present a flow- and context-sensitive analysis with special domains to support containers (such as lists) and infer type equalities (allowing it to express parametric polymorphism). The analysis is soundly derived by abstract interpretation from a concrete semantics of Python developed by Fromherz et al. Our analysis is designed in a modular way as a set of domains abstracting a concrete collecting semantics. It has been implemented into the MOPSA analysis framework, and leverages external type annotations from the Typeshed project to support the vast standard library. We show that it scales to benchmarks a few thousand lines long, and preliminary results show it is able to analyze a small real-life command-line utility called PathPicker. Compared to previous work, it is sound, while it keeps similar efficiency and precision.
Cite as

Raphaël Monat, Abdelraouf Ouadjaout, and Antoine Miné. Static Type Analysis by Abstract Interpretation of Python Programs (Artifact). In Special Issue of the 34th European Conference on Object-Oriented Programming (ECOOP 2020). Dagstuhl Artifacts Series (DARTS), Volume 6, Issue 2, pp. 11:1-11:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

Copy BibTex To Clipboard

@Article{monat_et_al:DARTS.6.2.11,
  author =	{Monat, Rapha\"{e}l and Ouadjaout, Abdelraouf and Min\'{e}, Antoine},
  title =	{{Static Type Analysis by Abstract Interpretation of Python Programs (Artifact)}},
  pages =	{11:1--11:6},
  journal =	{Dagstuhl Artifacts Series},
  ISSN =	{2509-8195},
  year =	{2020},
  volume =	{6},
  number =	{2},
  editor =	{Monat, Rapha\"{e}l and Ouadjaout, Abdelraouf and Min\'{e}, Antoine},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DARTS.6.2.11},
  URN =		{urn:nbn:de:0030-drops-132082},
  doi =		{10.4230/DARTS.6.2.11},
  annote =	{Keywords: Formal Methods, Static Analysis, Abstract Interpretation, Type Analysis, Dynamic Programming Language, Python Semantics}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2020.17
Static Type Analysis by Abstract Interpretation of Python Programs

Authors: Raphaël Monat, Abdelraouf Ouadjaout, and Antoine Miné

Published in: LIPIcs, Volume 166, 34th European Conference on Object-Oriented Programming (ECOOP 2020)

Abstract
Python is an increasingly popular dynamic programming language, particularly used in the scientific community and well-known for its powerful and permissive high-level syntax. Our work aims at detecting statically and automatically type errors. As these type errors are exceptions that can be caught later on, we precisely track all exceptions (raised or caught). We designed a static analysis by abstract interpretation able to infer the possible types of variables, taking into account the full control-flow. It handles both typing paradigms used in Python, nominal and structural, supports Python’s object model, introspection operators allowing dynamic type testing, dynamic attribute addition, as well as exception handling. We present a flow- and context-sensitive analysis with special domains to support containers (such as lists) and infer type equalities (allowing it to express parametric polymorphism). The analysis is soundly derived by abstract interpretation from a concrete semantics of Python developed by Fromherz et al. Our analysis is designed in a modular way as a set of domains abstracting a concrete collecting semantics. It has been implemented into the MOPSA analysis framework, and leverages external type annotations from the Typeshed project to support the vast standard library. We show that it scales to benchmarks a few thousand lines long, and preliminary results show it is able to analyze a small real-life command-line utility called PathPicker. Compared to previous work, it is sound, while it keeps similar efficiency and precision.
Cite as

Raphaël Monat, Abdelraouf Ouadjaout, and Antoine Miné. Static Type Analysis by Abstract Interpretation of Python Programs. In 34th European Conference on Object-Oriented Programming (ECOOP 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 166, pp. 17:1-17:29, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

Copy BibTex To Clipboard

@InProceedings{monat_et_al:LIPIcs.ECOOP.2020.17,
  author =	{Monat, Rapha\"{e}l and Ouadjaout, Abdelraouf and Min\'{e}, Antoine},
  title =	{{Static Type Analysis by Abstract Interpretation of Python Programs}},
  booktitle =	{34th European Conference on Object-Oriented Programming (ECOOP 2020)},
  pages =	{17:1--17:29},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-154-2},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{166},
  editor =	{Hirschfeld, Robert and Pape, Tobias},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2020.17},
  URN =		{urn:nbn:de:0030-drops-131748},
  doi =		{10.4230/LIPIcs.ECOOP.2020.17},
  annote =	{Keywords: Formal Methods, Static Analysis, Abstract Interpretation, Type Analysis, Dynamic Programming Language, Python Semantics}
}
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail
© 2023-2024 Schloss Dagstuhl – LZI GmbH Imprint Privacy Contact