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PyPy's Python Interpreter Architecture and its Applications
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Introduction
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 - some kind of intro about Python
   - object-oriented imperative language 
   - rich library of builtin-types
   - complex dispatching rules for operations

 - and PyPy:
   - Python implementation in RPython
   - translate RPython to other languages
   - try to reach extremely good compatibility
   - also try to get a simple and flexible interpreter architecture


The Object Space Architecture
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 - PyPy Python-interpreter architecture
   - interpreter split into two parts:
     - normal bytecode interpreter
       - responsible for control flow
       - treats all objects as black boxes
       - only way to gain information: typed unwraps, particularly is_true
     - object space
       - is responsible for object implementation and operation semantics
       - knows nothing about execution

Applications
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 - flow object space
   - goal: derive control flow of functions
   - abstract interpretation
   - flow object space is a new value domain: Variables and Constants

 - compile-time meta-programming, comprehensive changes
   - thunk object space
   - reflective object space

Prior Work
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 - interpreter architecture
   - compare to CPython, Jython and IronPython?
   - parallels to the typical eval/apply model of Scheme interpreters

 - flow graph construction
   - usually through parsing

 - lazy computation
   - XXX find some papers

 - reflective object space
   - reflective towers