[pypy-svn] r61117 - in pypy/extradoc/talk/ecoop2009: . tutorial

[antocuni at codespeak.net]

Author: antocuni
Date: Mon Jan 19 15:26:43 2009
New Revision: 61117

Modified:
   pypy/extradoc/talk/ecoop2009/intro.tex
   pypy/extradoc/talk/ecoop2009/tutorial/proposal.tex
Log:
(antocuni, cfbolz) minor fixes



Modified: pypy/extradoc/talk/ecoop2009/intro.tex
==============================================================================
--- pypy/extradoc/talk/ecoop2009/intro.tex	(original)
+++ pypy/extradoc/talk/ecoop2009/intro.tex	Mon Jan 19 15:26:43 2009
@@ -4,7 +4,7 @@
 
 The alternative is to write a compiler; writing a compiler that targets a high
 level virtual machine like CLI or JVM is easier than targeting a real CPU, but
-it still require a lot of work, as IronPython, Jython, JRuby demonstrate.
+it still requires a lot of work, as IronPython, Jython, JRuby demonstrate.
 
 Moreover, writing a static compiler is often not enough to get high
 performance; IronPython and JRuby are going in the direction of JIT compiling

Modified: pypy/extradoc/talk/ecoop2009/tutorial/proposal.tex
==============================================================================
--- pypy/extradoc/talk/ecoop2009/tutorial/proposal.tex	(original)
+++ pypy/extradoc/talk/ecoop2009/tutorial/proposal.tex	Mon Jan 19 15:26:43 2009
@@ -86,7 +86,7 @@
 to write an interpreter for it; however, interpreters are slow. An alternative
 is to write a compiler; writing a compiler that targets a high level virtual
 machine like CLI or JVM is easier than targeting a real CPU, but it still
-require a lot of work, as demonstrated by the IronPython, Jython, JRuby
+requires a lot of work, as demonstrated by the IronPython, Jython, JRuby
 projects. Moreover, the various platforms (either VM or real hardware) have to
 be targeted independently.
 
@@ -95,7 +95,7 @@
 aims to make the implementation of dynamic
 languages easier by providing a toolchain that allows to compile an
 interpreter to various target platforms, including the JVM, .NET and C/Posix. 
-In addition, we are working on automatically transforming the
+In addition, we are working on being able to automatically transform the
 interpreter into a specializing JIT-compiler to vastly increase performance.
 The goal is to minimize the effort required to get a fast implementation for a
 dynamic language.
@@ -104,7 +104,7 @@
 toolchain by giving a step-by-step introduction. The topics covered are how to
 write an interpreter for a dynamic language with PyPy and make it possible to
 automatically generate a JIT for it.  We will showcase a typical interpreter for a
-small dynamic language as a running example.
+small object-oriented dynamic language as a running example.
 
 
 Outline of the tutorial:
@@ -116,7 +116,7 @@
  \item \textbf{Translation:} Show how to compile the interpreter to various
  platforms, including .NET and C/Posix.
  \item \textbf{JIT-Generation:} Show how to apply the JIT-generator to the
- interpreter to automatically get a JIT for the language.
+ interpreter by placing a few hints to automatically get a JIT for the language.
 \end{itemize}