GSoC 2014
This page lists project proposals for Google Summer of Code 2014.
These ideas were contributed by our developers. They are sometimes vague or incomplete. If you wish to submit a proposal based on these ideas, you may wish to contact the developers and find out more about the particular suggestion you're looking at.
Being accepted as a Google Summer of Code student is quite competitive. Accepted students typically have thoroughly researched the technologies of their proposed project and have been in frequent contact with potential mentors. Simply copying and pasting an idea here will not work. On the other hand, creating a completely new idea without first consulting potential mentors is unlikely to work out.
When writing your proposal or asking for help from the general MegaGlest community don't assume people are familiar with the ideas here.
If there is no specific contact given you can ask questions on our IRC channel on freenode at #megaglest. For more context see the MegaGlest development web page and contact the developers on the projects' forums and mailing lists.
Brief explanation:
Expected results:
Knowledge Prerequisite:
Mentor:
When adding an idea to this section, please try to include the following data:
- a brief explanation
- the expected results
- pre-requisites for working on your project
- if applicable, links to more information or discussions
- mailing list or IRC channel for your demo/library/module
- your name and email address for contact (if you're willing to be a mentor)
How to find ideas?
Obvious sources of projects are
- bug reports: on the forums, on sourceforge (legacy), on GitHub (new - game engine and assets)
- feature requests: on the forums, on sourceforge (legacy)
- discussions on the general forum
- your personal experiences while playing the game.
Currently MegaGlest uses an A* (a-star) implementation for its pathfinding algorithm. During times in game where many units need to be moving and pathfinding, this can cause performance problems (or lagging). We would like someone to investigate plugging in an accurate / fast performing (possibly an AI pathfinding technique called flocking or swarm AI) alternative and possible replacement.
An idea that looks promising:
Website - This is a link with some explanation as to how Blizzard software handles pathfinding in SC2.
Expected results:
A pathfinder in game that performs well under a load of 1000 -> 1500 concurrent units of different sizes on a complex map with various obstacles.
Knowledge prerequisite:
C++ is the main language of MegaGlest, therefore the code should be in C++. The more you know about C++, OpenGL, and Pathfinding techniques the better.
This idea encompasses so much different stuff the student is not expected to know everything before he starts coding (but will certainly get to know a lot in the process!).
Skill level: medium to advanced
Mentor: Mark Vejvoda (SoftCoder) as general mentor and someone to ask for directions.
Unless noted otherwise, all MegaGlest documentation is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
