[pypy-svn] r3814 - pypy/trunk/doc/funding

hpk at codespeak.net hpk at codespeak.net
Tue Apr 6 12:36:35 CEST 2004


Author: hpk
Date: Tue Apr  6 12:36:34 2004
New Revision: 3814

Modified:
   pypy/trunk/doc/funding/B1.0_objectives.txt
Log:
fixed a couple of typos 



Modified: pypy/trunk/doc/funding/B1.0_objectives.txt
==============================================================================
--- pypy/trunk/doc/funding/B1.0_objectives.txt	(original)
+++ pypy/trunk/doc/funding/B1.0_objectives.txt	Tue Apr  6 12:36:34 2004
@@ -10,7 +10,7 @@
 Even the implementations of Open Source dynamic languages have
 non-flexible designs crafted by a small group of developers.
 (This has always been a 'given'.  The language designer, or designers,
-make certain tradeoffs in their language implementation, and the
+make certain trade-offs in their language implementation, and the
 language users are stuck with what was decided, even if it does not
 suit their particular needs.)
 
@@ -64,7 +64,7 @@
 
 * choice of memory and threading model 
 * choice of speed vs. memory trade-offs
-* plugable adaptive implementations of various HL types, e.g. dictionaries
+* pluggable adaptive implementations of various VHLL types, e.g. dictionaries
 * distributed/parallel execution (SMP or Networked)
 * orthogonal persistence
 * pervasive security support
@@ -192,7 +192,7 @@
 variable*, which allows the matching of data through unification or
 constraint processing, and non-deterministic control structures. Work
 initiated at the DFKI has examined ways to combine these constructs with
-those from other languages[Sch02]_. A key concept here is *encapulated
+those from other languages[Sch02]_. A key concept here is *encapsulated
 search*, which hives off these features from the more mainstream
 programming constructs.
 
@@ -201,7 +201,7 @@
 constraint programming in Python [Log]_, and one of most popular text books
 in Artificial Intelligence has Python code for the examples
 [RN02]_. Moreover, the main inventor of the world wide web developed the
-first inference engine for the sematic web in Python [Cwm]_. However, none of
+first inference engine for the semantic web in Python [Cwm]_. However, none of
 these projects has realised code that can be used in production
 environments. It is simply too slow.
 
@@ -312,7 +312,7 @@
 +++++++++++++++++++
 
 Within PyPy, we will be the first to provide usable constraint programming
-techniques within a popular VHLL. We will take advatntage of the
+techniques within a popular VHLL. We will take advantage of the
 light-weight multithreading that we will introduce to Python to handle the
 constraint processing efficiently and we will examine the use of object
 spaces to develop implementations of Python that are specialised for search
@@ -339,8 +339,8 @@
 We believe that ours is a practical and scalable approach to interpreter
 modularity, applicable to any language, from general to domain-specific ones.
 The PyPy implementation should quickly reach the large user base of the
-current, industrial-strength Python, and could eventually form the fundation
-of the "next generation" Python implemention commonly refered to as
+current, industrial-strength Python, and could eventually form the foundation
+of the "next generation" Python implementation commonly referred to as
 Python3000.  The efforts will be focused on actively reaching out non-Python
 communities, based on:
 
@@ -364,7 +364,7 @@
 
 
 .. [AFGHS00] Matthew Arnold, Stephen J. Fink, David Grove, Michael Hind, and Peter F. Sweeney,
-   "Adaptive Optimization in the Jalapeno JVM", In Conference on Object-Oriented Prorgramming and Systems, pp. 47-65, 2000.
+   "Adaptive Optimization in the Jalapeno JVM", In Conference on Object-Oriented Programming and Systems, pp. 47-65, 2000.
    http://citeseer.nj.nec.com/arnold00adaptive.html
 
 


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