[pypy-svn] r28005 - pypy/extradoc/talk/dls2006

[pedronis at codespeak.net]

Author: pedronis
Date: Wed May 31 16:54:20 2006
New Revision: 28005

Modified:
   pypy/extradoc/talk/dls2006/paper.bib
   pypy/extradoc/talk/dls2006/paper.tex
Log:
some more reference and tweaks



Modified: pypy/extradoc/talk/dls2006/paper.bib
==============================================================================
--- pypy/extradoc/talk/dls2006/paper.bib	(original)
+++ pypy/extradoc/talk/dls2006/paper.bib	Wed May 31 16:54:20 2006
@@ -10,7 +10,7 @@
 }
 
 % Hindley-Milner
- at inproceedings{582176,
+ at inproceedings{DaMi,
  author = {Luis Damas and Robin Milner},
  title = {Principal type-schemes for functional programs},
  booktitle = {POPL '82: Proceedings of the 9th ACM SIGPLAN-SIGACT symposium on Principles of programming languages},
@@ -23,7 +23,7 @@
  address = {New York, NY, USA},
  }
 
- at article{DBLP:journals/jcss/Milner78,
+ at article{Miln,
   author    = {Robin Milner},
   title     = {A Theory of Type Polymorphism in Programming.},
   journal   = {J. Comput. Syst. Sci.},
@@ -68,13 +68,13 @@
  address = {New York, NY, USA},
  }
 
- at misc{ kelsey-prescheme,
+ at misc{kelsey-prescheme,
   author = "R. Kelsey",
   title = "Pre-Scheme: A Scheme Dialect for Systems Programming",
   text = "Richard Kelsey. Pre-Scheme: A Scheme Dialect for Systems Programming. ?." }
 
 % Psyco
- at inproceedings{1014010,
+ at inproceedings{psyco,
  author = {Armin Rigo},
  title = {Representation-based just-in-time specialization and the psyco prototype for python},
  booktitle = {PEPM '04: Proceedings of the 2004 ACM SIGPLAN symposium on Partial evaluation and semantics-based program manipulation},
@@ -101,7 +101,7 @@
 }
 
 % old overview paper
- at article{DBLP:journals/ibmsj/AlpernABBCCCFGHHLLMNRSSSSSSW00,
+ at article{jalapeno,
   author    = {Bowen Alpern and
                C. Richard Attanasio and
                John J. Barton and
@@ -220,3 +220,17 @@
   year =        "1993",
   isbn =        "0-13-020249-5",
   note =        ""}
+
+ at article{Dhry20,
+ author = {R. P. Weicker},
+ title = {Dhrystone benchmark: rationale for version 2 and measurement rules},
+ journal = {SIGPLAN Not.},
+ volume = {23},
+ number = {8},
+ year = {1988},
+ issn = {0362-1340},
+ pages = {49--62},
+ doi = {http://doi.acm.org/10.1145/47907.47911},
+ publisher = {ACM Press},
+ address = {New York, NY, USA},
+ }
\ No newline at end of file

Modified: pypy/extradoc/talk/dls2006/paper.tex
==============================================================================
--- pypy/extradoc/talk/dls2006/paper.tex	(original)
+++ pypy/extradoc/talk/dls2006/paper.tex	Wed May 31 16:54:20 2006
@@ -608,18 +608,19 @@
 Python -- like many languages not specifically designed with type
 inference in mind -- does not possess a type system that allows much
 useful information to be derived about variables based on how they are
-\textit{used}; only on how they were \textit{produced}.  For example, a number of very
-different built-in types can be involved in an addition; the meaning of
-the addition and the type of the result depends on the type of the input
-arguments.  Merely knowing that a variable will be used in an addition
-does not give much information per se.  For this reason, our annotator
-works by flowing types forward, operation after operation, i.e.\ by
-performing abstract interpretation of the flow graphs.  In a sense, it
-is a more naive approach than the one taken by type systems specifically
-designed to enable more advanced inference algorithms.  For example,
+\textit{used}; only on how they were \textit{produced}.  For example,
+a number of very different built-in types can be involved in an
+addition; the meaning of the addition and the type of the result
+depends on the type of the input arguments.  Merely knowing that a
+variable will be used in an addition does not give much information
+per se.  For this reason, our annotator works by flowing types
+forward, operation after operation, i.e.\ by performing abstract
+interpretation of the flow graphs.  In a sense, it is a more naive
+approach than the one taken by type systems specifically designed to
+enable more advanced inference algorithms.  For example,
 Hindley-Milner type inference works in an inside-out direction, by
 starting from individual operations and propagating type constraints
-outwards [H-M].
+outwards \cite{DaMi}\cite{Miln}.
 
 Naturally, simply propagating types forward requires the use of a fixed
 point algorithm in the presence of loops in the flow graphs or in the
@@ -909,8 +910,8 @@
 
 The tool-chain has been tested with and can sucessfully apply
 transformations enabling various combinations of features. The
-translated interpreters are benchmarked using pystone (a [Dhrystone] 2.0
-derivative traditionally used by the Python community, although it is
+translated interpreters are benchmarked using pystone (a Dhrystone 2.0
+\cite{dhry20} derivative traditionally used by the Python community, although it is
 a rather poor benchmark) and the classical [Richards] benchmark and
 compared against [CPython] 2.4.3 results and are summarized in table
 \ref{perfsumm}.
@@ -1089,8 +1090,8 @@
 generating extension.  We can currently do this on trivial examples.
 
 The resulting generating extension will be essentially similar to
-[Psyco], which is the only (and hand-written) JIT available for Python so
-far, based on run-time specialization.
+Psyco \cite{psyco}, which is the only (and hand-written) JIT available for Python
+so far, based on run-time specialization.
 
 
 
@@ -1127,7 +1128,7 @@
 portability were the major goals, as opposed to sophisticated manipulation
 and analysis or "weaving" in of features as transformation aspects.
 
-Jikes RVM \cite{DBLP:journals/ibmsj/AlpernABBCCCFGHHLLMNRSSSSSSW00} is a
+Jikes RVM \cite{jalapeno} is a
 Java VM and Just-In-Time compiler written in Java.
 Bootstrapping happens by self-applying the compiler on a host VM, and
 dumping a snapshot from memory of the resulting native code.