FLAT: Formal Languages as Types
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arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866916574395367424 |
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| author | Zhu, Fengmin Zeller, Andreas |
| author_facet | Zhu, Fengmin Zeller, Andreas |
| contents | Programmers regularly use strings to encode many types of data, such as Unix file paths, URLs, and email addresses, that are conceptually different. However, existing mainstream programming languages use a unified string type to represent them all. As a result, their type systems will keep quiet when a function requiring an email address is instead fed an HTML text, which may cause unexceptional failures or vulnerabilities.
To let the type system distinguish such conceptually different string types, in this paper, we propose to regard \emph{formal languages as types} (FLAT), thereby restricting the set of valid strings by context-free grammars and semantic constraints if needed. To this end, email addresses and HTML text are treated as different types. We realize this idea in Python as a testing framework FLAT-PY. It contains user annotations, all directly attached to the user's code, to (1) define such \emph{language types}, (2) specify pre-/post-conditions serving as \emph{semantic oracles} or contracts for functions, and (3) fuzz functions via random string inputs generated from a \emph{language-based fuzzer}. From these annotations, FLAY-PY \emph{automatically} checks type correctness at runtime via \emph{code instrumentation}, and reports any detected type error as soon as possible, preventing bugs from flowing deeply into other parts of the code. Case studies on real Python code fragments show that FLAT-PY is enable to catch logical bugs from random inputs, requiring a reasonable amount of user annotations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_11501 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | FLAT: Formal Languages as Types Zhu, Fengmin Zeller, Andreas Software Engineering Programming Languages Programmers regularly use strings to encode many types of data, such as Unix file paths, URLs, and email addresses, that are conceptually different. However, existing mainstream programming languages use a unified string type to represent them all. As a result, their type systems will keep quiet when a function requiring an email address is instead fed an HTML text, which may cause unexceptional failures or vulnerabilities. To let the type system distinguish such conceptually different string types, in this paper, we propose to regard \emph{formal languages as types} (FLAT), thereby restricting the set of valid strings by context-free grammars and semantic constraints if needed. To this end, email addresses and HTML text are treated as different types. We realize this idea in Python as a testing framework FLAT-PY. It contains user annotations, all directly attached to the user's code, to (1) define such \emph{language types}, (2) specify pre-/post-conditions serving as \emph{semantic oracles} or contracts for functions, and (3) fuzz functions via random string inputs generated from a \emph{language-based fuzzer}. From these annotations, FLAY-PY \emph{automatically} checks type correctness at runtime via \emph{code instrumentation}, and reports any detected type error as soon as possible, preventing bugs from flowing deeply into other parts of the code. Case studies on real Python code fragments show that FLAT-PY is enable to catch logical bugs from random inputs, requiring a reasonable amount of user annotations. |
| title | FLAT: Formal Languages as Types |
| topic | Software Engineering Programming Languages |
| url | https://arxiv.org/abs/2501.11501 |