This is the development repository for the OpenDSA project. Note that the stable release version is maintained at: https://github.com/cashaffer/OpenDSA-stable.

The goal of the OpenDSA project is to create open-source courseware for use in Data Structures and Algorithms courses, that deeply integrates textbook-quality content with algorithm visualizations and interactive, automatically assessed exercises.

System documentation can be found at http://opendsa.readthedocs.org/.

To check out a read-only copy of this repository:

git clone git://github.com/OpenDSA/OpenDSA.git OpenDSA

To check out a read-write copy of this repository (requires permission to commit to the repo):

git clone https://YOURGITHUBID@github.com/OpenDSA/OpenDSA.git OpenDSA

Once you have cloned this repository, you will need to initialize and update the submodules and compile some of the libraries. Do the following:

git submodule init
make pull

In order to pull a more recent copy of JSAV than what is in the submodule:

cd JSAV
git pull https://github.com/vkaravir/JSAV

A similar command will let you pull the up-to-date version of QBank.

The source files for the documentation can be found in the "Doc" directory. Changes to the documentation source, once pushed back to the repository, will automatically revise the public version at readthedocs.org. You can also re-compile the documentation by going to the "Doc" directory and typing "make". The result will then be in "Doc/manual".

The major components in the directory structure are as follows:

AV: Source code for various algorithm visualizations and associated exercises. Subdirectories divide the content by topical areas.

Books: Created by the build process, this contains compiled versions of "textbooks".

config: This holds configuration files for specific books (whose output will go to the "Books" directory).

Doc: Documentation. Currently includes a template for Khan Academy multiple choice questions, and documentation for using the various Sphinx directives that we have created.

Exercises: Our Khan Academy Infrastructure-based exercises. Subdirectories divide the content by topic.

**Frontend: Experimental interface for allowing instructor selection of modules. Currently not in use, will be replaced at some point.

JSAV: The JavaScript Algorithm Visualization library (JSAV). This is a submodule for the OpenDSA repository, linked to: https://github.com/vkaravir/JSAV. Thus, when you check out OpenDSA, you must get the JSAV submodule by either running the command "make pull" or by doing the following: git submodule init git submodule update More information about JSAV can be found here: http://jsav.io/

lib: System-wide library files

Makefile: Primarily for source file validation and to generate some of the "textbooks" to the Books directory.

MIT-license.txt: The license file. OpenDSA is distributed under an MIT open source license.

**Modules: Tutorial source from an obsolete system for generating content. Will be removed.

ODSAkhan-exercises: Our somewhat modified version of the khan-exercises distribution (the original is also available at GitHub). Note that you can view and run the exercises with just this distribution, however, the files must be hosted by a webserver. If you want to view them from your local machine, you must run your own webserver, such as the "WebServer" Python script included in this distribution. Simply run the script, then navigate to http://127.0.0.1:8000/Exercises/ in your browser. If the pages are accessed without the use of a webserver, they will either be a blank page or some gibberish. Alternatively, you can see the exercises at our mirror site: http://algoviz.org/OpenDSA/dev/OpenDSA/Exercises.

QBank: A question bank system under development. This is a submodule maintained at: https://github.com/cashaffer/QBank.

README.md: This file

RST: Contains our custom Sphinx directives used during the build process and the source for tutorial content written in reStructuredText (RST) format and divided by language and sub-divided by topic area.

SourceCode: The sourcecode for code snippets contained in the tutorials. Ultimately, we hope to support code snippets in Processing (a Java dialect), Python, and JavaScript. In this way, instructors would be able to generate versions of tutorials that support any or all of these three languages.

**Storyboard: Materials related to "storyboarding" designs for tutorials. This concept never gained much traction, and this might be removed at some point.

WebServer: A command for invoking a simple python-based web server that will enable you to run the Khan Academy exercises if your machine is not running a true web server. You only need to have python installed for this to work.