A Multilanguage Static Analysis of Python Programs with Native C Extensions
| Autor: | Antoine Miné, Abdelraouf Ouadjaout, Raphaël Monat |
|---|---|
| Přispěvatelé: | Monat, Raphaël, Modular Open Platform for Static Analysis - MOPSA - - H20202016-06-01 - 2021-05-31 - 681393 - VALID, Algorithmes, Programmes et Résolution (APR), LIP6, Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut Universitaire de France (IUF), Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche (M.E.N.E.S.R.), European Project: 681393,H2020,ERC-2015-CoG,MOPSA(2016) |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Source code
Computer science Interface (Java) media_common.quotation_subject Abstract Interpretation 02 engineering and technology computer.software_genre Formal Methods 020204 information systems Multilanguage Analysis 0202 electrical engineering electronic engineering information engineering media_common computer.programming_language Soundness [INFO.INFO-PL]Computer Science [cs]/Programming Languages [cs.PL] business.industry Programming language Static Analysis 020207 software engineering Modular design Static analysis Python (programming language) Formal methods Abstract interpretation [INFO.INFO-PL] Computer Science [cs]/Programming Languages [cs.PL] Dynamic Programming Language business computer |
| Zdroj: | Static Analysis Symposium (SAS) Static Analysis Symposium (SAS), Oct 2021, Chicago, Illinois, United States Static Analysis ISBN: 9783030888053 SAS Static Analysis-28th International Symposium, SAS 2021 Lecture Notes in Computer Science Lecture Notes in Computer Science-Static Analysis |
| ISSN: | 0302-9743 1611-3349 |
| Popis: | International audience; Modern programs are increasingly multilanguage, to benefit from each programming language's advantages and to reuse libraries. For example, developers may want to combine high-level Python code with low-level, performance-oriented C code. In fact, one in five of the 200 most downloaded Python libraries available on GitHub contains C code. Static analyzers tend to focus on a single language and may use stubs to model the behavior of foreign function calls. However, stubs are costly to implement and undermine the soundness of analyzers. In this work, we design a static analyzer by abstract interpretation that can handle Python programs calling C extensions. It analyses directly and fully automatically both the Python and the C source codes. It reports runtime errors that may happen in Python, in C, and at the interface. We implemented our analysis in a modular fashion: it reuses off-the-shelf C and Python analyses written in the same analyzer. This approach allows sharing between abstract domains of different languages. Our analyzer can tackle tests of real-world libraries a few thousand lines of C and Python long in a few minutes. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|