This is a complete rewrite of the PEG.js code generator. Its goals are:
1. Allow optimizing the generated parser code for code size as well as
for parsing speed.
2. Prepare ground for future optimizations and big features (like
incremental parsing).
2. Replace the old template-based code-generation system with
something more lightweight and flexible.
4. General code cleanup (structure, style, variable names, ...).
New Architecture
----------------
The new code generator consists of two steps:
* Bytecode generator -- produces bytecode for an abstract virtual
machine
* JavaScript generator -- produces JavaScript code based on the
bytecode
The abstract virtual machine is stack-based. Originally I wanted to make
it register-based, but it turned out that all the code related to it
would be more complex and the bytecode itself would be longer (because
of explicit register specifications in instructions). The only downsides
of the stack-based approach seem to be few small inefficiencies (see
e.g. the |NIP| instruction), which seem to be insignificant.
The new generator allows optimizing for parsing speed or code size (you
can choose using the |optimize| option of the |PEG.buildParser| method
or the --optimize/-o option on the command-line).
When optimizing for size, the JavaScript generator emits the bytecode
together with its constant table and a generic bytecode interpreter.
Because the interpreter is small and the bytecode and constant table
grow only slowly with size of the grammar, the resulting parser is also
small.
When optimizing for speed, the JavaScript generator just compiles the
bytecode into JavaScript. The generated code is relatively efficient, so
the resulting parser is fast.
Internal Identifiers
--------------------
As a small bonus, all internal identifiers visible to user code in the
initializer, actions and predicates are prefixed by |peg$|. This lowers
the chance that identifiers in user code will conflict with the ones
from PEG.js. It also makes using any internals in user code ugly, which
is a good thing. This solves GH-92.
Performance
-----------
The new code generator improved parsing speed and parser code size
significantly. The generated parsers are now:
* 39% faster when optimizing for speed
* 69% smaller when optimizing for size (without minification)
* 31% smaller when optimizing for size (with minification)
(Parsing speed was measured using the |benchmark/run| script. Code size
was measured by generating parsers for examples in the |examples|
directory and adding up the file sizes. Minification was done by |uglify
--ascii| in version 1.3.4.)
Final Note
----------
This is just a beginning! The new code generator lays a foundation upon
which many optimizations and improvements can (and will) be made.
Stay tuned :-)
Includes:
* Moving the source code from /src to /lib.
* Adding an explicit file list to package.json
* Updating the Makefile.
* Updating the spec and benchmark suites and their READMEs.
Part of a fix for GH-32.
PEG.js source code becomes a set of Node.js modules that include each
other as needed. The distribution version is built by bundling these
modules together, wrapping them inside a bit of boilerplate code that
makes |module.exports| and |require| work.
Part of a fix for GH-32.
When the Git repository will be a npm package, there will be no
preprocessing step and thus no @VERSION substitution. Let's get rid of
it.
Part of a fix for GH-32.
Before this commit, package.json in the project root directory was
preprocessed in order to insert correct version into it. This made it
invalid JSON and thus unusable for npm purposes.
This commit makes package.json a valid JSON by hardcoding the version
into it. I think that introducing this small duplicity is outweighted by
being able to use npm in project root directory. For example, it is now
possible to make the "npm test" command work and introduce Travis CI
integration.
This is the first of many commits that gradually convert PEG.js's test
suite from QUnit to Jasmine, cleaning it up on the way.
Main reason for the change is that Jasmine allows nested contexts,
allowing to structure the tests in a better way than QUnit. Moreover,
the tests needed to be cleaned up a bit.
David Majda