Python is dynamically typed interpreted programming language. Thanks to its dynamic type system, it is difficult to compile it into statically typed source code. The kind of source code, where it is exactly specified what types exist and what their structure is. Multiple approaches exist how to achieve this and one of the primary ones is type inference. This approach is attempting to infer the type structure from the source code. In case of Python language, this approach is difficult, because resulting type system is quite complex and language itself is not designed for type inference. In this work, I have focused on identifying subset of this language, so that type inference is possible while keeping the natural way the language is used. Then I implemented a compiler, which will compile this subset into statically typed language, which can be translated into native code.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:236025 |
| Date | January 2014 |
| Creators | Falhar, Radek |
| Contributors | Křivka, Zbyněk, Kolář, Dušan |
| Publisher | Vysoké učení technické v Brně. Fakulta informačních technologií |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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