Project Guidelines

Final report: Each group will submit one report. 

Limitations on the final report: There is a "soft" maximum limit of 10 pages to present your main report and analysis/explanation of your paper.(Title page or bibliography do not count towards this limit.) If you feel you require beyond 10 pages to do your paper full justice, then you are allowed to create a separate appendix or supplementary section which we shall look through, probably not thoroughly. If you do this, you MUST clearly indicate the main body or 10 pages of your report, and include the most relevant part there.

There is no minimum page limit, beyond what common sense should mandate. You can get full credit within the 10 page limit or less as long as your report is well done.

Expectations during evaluation:

1. You demonstrate understanding of the results, and any model of computation/approximation that give context to them.
2. You demonstrate understanding of the actual algorithms.
3. You demonstrate understanding of the proofs involved, and what are the key ideas. You don't need to reproduce every lemma, or each and every proof unless it's a very short paper. But you should give a technical overview of how the main theorems in your paper are derived, and present enough details (you may give a judicious sampling depending on the length of your paper and importance of each proof you expand on) to illustrate how the proofs work.
4. You can decipher how best to cleanly present and explain your paper. You may choose to follow a similar heading/section breakup as the paper itself, or choose to structure your report in an entirely different manner.
5. You can give the context of related work, both prior and succeeding. (Although you don't need to go in too much technical details or proofs here.) This is especially important for those of you who are dealing with an algorithm/data structure which is a mild modification of prior work - in this case , you may need to give some explanation of work from previous papers so that the readers can understand the prior work.
6. You may assume your readers are familiar with general algorithms and theory, but not that they are well acquainted with your topic.
7. Note that you don't have to explain the entire paper. It's perfectly fine to explain a piece of it that is at the core of the work or that really appealed to you. 

Here's a template (LaTeX Download LaTeX