Hi,
my name is Patrick Gottschaemmer and I'm a computer science student at the Darmstadt University of Technology. Besides that, I work for the Code Recommenders project as a Eclipse contributor since October 2012. I'd like to participate in the Google Summer of Code 2013 and this is my GSOC Proposal about an integration of Code Recommenders statistics into Javadoc. Any feedback would be welcome! |  |
Abstract
The
Eclipse Code Recommenders project [1] provides a smart Code Completion
for the Eclipse IDE in Java, based on the context where code completion
is triggered and gained knowledge by analyzing source code of open
source projects. These machine learned statistics of API and framework
usages (e.g. JFace or the JDK itself) can be summarized and made
abstract from the current code context. This way, typical usage patterns
of API calls or code snippets (lines of code which are usually appear
together) can be identified.
These gained informations can be a great advantage when learning how to use a new API or a framework.
Furthermore,
a directly integration into the standard documentation platform of the
programming language would be useful, because that is normally the
starting point for developers which want to learn something about core
classes, package usages and interfaces in frameworks or APIs. In this
GSoC Proposal, I’d like to implement the following additional features
for the Javadoc generation tool [2]:
- Integration of Code Recommenders statistics for packages, classes and methods on Javadoc
- A little helper utility which fetches source code from a repository, runs javadoc on it, integrates the Code Recommenders statstics and uploads the updated documentation back to the repository
- Enable developers to directly edit, comment or rate on API documentation and new code snippets, which are provided by the Snipmatch subproject of Code Recommenders or posted by developers themselves
Introduction
The
standard Code Completion of the Eclipse IDE (or Code Completion in
general) is a great feature to speed-up your workflow in programming.
Not only saving you a dozens of keystrokes per day by complete your not
yet finished lines of code, it can also be used to show you
syntactically correct proposals for your method calls or your overrides.
While
this is a great way to learn how to use new APIs and frameworks, it can
quickly get confusing if you trigger code completion for example on a
bloated ui class and get flooded by hundreds of method call proposals:
(all permissions granted by codetrails.com)
But actually, only a few methods are interesting, depending on your current code context:
(all permissions granted by codetrails.com)
This
is exactly what Code Recommenders does. The knowledge, which methods
are relevant for a programmer at a certain point in his code context are
gained from machine learning and analyzing of source code from open
source projects at the Eclipse Foundation.
Unfortunately,
if you’re completely new to an API or a framework, your first step
wouldn’t be to trigger code completion on some unfamiliar classes.
Usually, you start paying attention on some documentation, whether it be
a book, an online web page or a demo talk. For a specific problem,
you’d lookup a forum or something like stackoverflow.com
But
unfortunately, the machine learned source code statstics of Code
Recommenders are only available in your Eclipse IDE. At least until now!
Javadoc & Code Recommenders - What will it look like?
There
are several questions and statistics from Code Recommenders which you
could insert in a Javadoc HTML generated website, e.g.
- When selecting a package:
'What are the most frequently overwritten (used) classes in package org.eclipse.xyz*?' - When selecting a method:
'Which methods are frequently called together with m()?' - When selecting a type:
'Which methods of type X frequently used by clients?' - and many more...
While
these are just some basic ideas, I’d like to prioritize them (and
others) for the implementation with a Google Docs poll for the Eclipse
GSoC mentors.
An integration of the Code Recommenders statistic to the generated HTML output of Javadoc could look like this:
I’ve created some more Javadoc examples in HTML with the Javadoc framework, check them out at
The following elements are annotated with some statistics from Code Recommenders:
- The package org.eclipse.jface.viewers (at the bottom)
- The class org.eclipse.jface.viewers.TableViewer(right beneath the class description)
- The method getTable() in class TableViewer
Javadoc & Code Recommenders - How are they working together?
For
this generation part, I plan to extend the Javadoc Tool framework by
one or more 'Doclets' (see [2]) that allow different extdoc providers
(based on the extdoc providers of Code Recommenders) to contribute
directly to the generated HTML output via the Javadoc api.
In
contrast to the normal way how the javadoc command is used, I'd like to
develop a little helper utility that fetches and unzips the sources
directly from a maven repository, runs the normal javadoc tool and adds
the recommenders documentation to the standard javadoc output, and
finally uploads the updated javadocs to the repository or deploys them
on a website.
Going further - Let’s get social!
In
addition (when there is still some timet), I'd like to enable users to
directly edit, comment or rate on API documentation and new code
snippets, which are provided by the Snipmatch subproject of Code
Recommenders. Alternatively, these code snippets could also be posted
directly by developers through the webinterface or even via a REST API
(so you could implement an additional IDE plugin for this afterwards).
The code snippets shall be grouped by java classes and/or packages,
which then can be tagged, commented and rated by other developers. Top
rated code snippets ('favorites') shall appear at the top of the list,
indeed similar to stackoverflow.com.
Here are two mock-ups for a first impression:
API Commentation feature for developers
Social Code Snippets Integation
Server Backend
For
these social features, an additional backend (a RESTful api) will be needed, which
stores and organizes the code snippets, including tags and comments by
users.
The
snippets shall be inserted dynamically in the (so far static generated)
Javadoc website. For the server-side part I'm thinking of using the
OData [3] protocol backed up by a SQL database like MySQL.
Milestones and Timeline
Milestone #
|
Description
|
Duration
|
1 -
Javadoc Generation Utility
|
Provide a little helper utility which
|
~3 Weeks
|
2 -
Extend Javadoc with CoRe statistics
|
Extend
the Javadoc Tool framework by one or more 'Doclets' which allow
different extdoc providers (based on the extdoc providers of Code
Recommenders) to contribute directly to the generated HTML output via
the Javadoc API
|
~7 Weeks
|
3 -
Server Backend für Social Javadoc
|
RESTful API Server backend, which stores and organizes the code snippets, tags and documentation comments by users.
Implementation with the OData protocol backed up by a SQL database like MySQL.
|
~4-5 Weeks
|
4 -
Webpage Frontend for API Documenation
|
Enable
users to directly edit, comment or rate on API documentation through a
webpage or the REST API (maybe an Eclipse IDE plugin afterwards)
|
Remaining Time
|
5 -
Webpage Frontend for Code Snippets
|
Integration
of code snippets, which are provided by the Snipmatch subproject of
Code Recommenders. Alternatively, the code snippets could also be posted
directly by developers through the webinterface or via the REST API
(maybe an Eclipse IDE plugin afterwards)
|
Remaining Time
|
18 Weeks GSoC
|
About my work and contact information
Until
now, I’ve done some various bugfixes and corrections in the frontend of
the Code Recommenders Eclipse Plug-in, improved the drag’n’drop
provider ranking in the Extdoc View and worked out a documentation for
the different code completion scenarios (method calls, overrides,
annotations etc.) in Java and how we want to treat them in the future at
Code Recommenders.
Please feel free to contact me for further informations on my work or my GSoC proposal:
email
|
mail@gottschaemmer.net
|
mailing lists
|
recommenders-dev@eclipse.org,
soc-dev@eclipse.org
|
gtalk/jabber
|
patrick@gottschaemmer.net
|
icq
|
216653447
|
skype
|
paddyg89
|
astra
|
paddyg89
|
Links
[3] http://www.odata.org/
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