2026-09-19T00:21:39Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/166882022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Jonathan Bachrach.
Salib, Michael, 1978-
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2005-05-17T14:56:21Z
2005-05-17T14:56:21Z
2004
2004
http://hdl.handle.net/1721.1/16688
57175336
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.
Includes bibliographical references (leaves 93-96).
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Starkiller is a type inferencer and compiler for the dynamic language Python designed to generate fast native code. It analyzes Python source programs and converts them into equivalent C++ programs. Starkiller's type inference algorithm is based on the Cartesian Product Algorithm but has been significantly modified to support a radically different language. It includes an External Type Description Language that enables extension authors to document how their foreign code extensions interact with Python. This enables Starkiller to analyze Python code that interacts with foreign code written in C, C++, or Fortran. The type inference algorithm also handles data polymorphism in addition to parametric polymorphism, thus improving precision. Starkiller supports the entire Python language except for dynamic code insertion features such as eval and dynamic module loading. While the system is not yet complete, early numeric benchmarks show that Starkiller compiled code performs almost as well as hand made C code and substantially better than alternative Python compilers.
by Michael Salib.
M.Eng.
96 leaves
436696 bytes
435331 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Starkiller : a static type inferencer and compiler for Python
Static type inferencer for dynamic languages
Thesis
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<Abstract>Starkiller is a type inferencer and compiler for the dynamic language Python designed to generate fast native code. It analyzes Python source programs and converts them into equivalent C++ programs. Starkiller's type inference algorithm is based on the Cartesian Product Algorithm but has been significantly modified to support a radically different language. It includes an External Type Description Language that enables extension authors to document how their foreign code extensions interact with Python. This enables Starkiller to analyze Python code that interacts with foreign code written in C, C++, or Fortran. The type inference algorithm also handles data polymorphism in addition to parametric polymorphism, thus improving precision. Starkiller supports the entire Python language except for dynamic code insertion features such as eval and dynamic module loading. While the system is not yet complete, early numeric benchmarks show that Starkiller compiled code performs almost as well as hand made C code and substantially better than alternative Python compilers.</Abstract>
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