| 3.10 | Computer Science Dissertation |
A dissertation presupposes some innovations. And where if not in computer science dissertation your insights and new theories can find themselves at home? If you are a technology freak with a clear vision of who is going to live in Bill Gate’s house (and it will be you, if you do a good job), than roll up your sleeves, make a weekly dose of coffee and get prepared to glue yourself to the monitor, for a computer science dissertation has never been easy enough.
When talking about writing a computer science dissertation we are talking about understanding of primary goals. Dissertation is an extended academic paper aimed at discovering, unfolding and proving a certain original idea. The best variant is if your computer science dissertation becomes applicable not only to theory, but to practice as well.
As for the general requirements of a computer science dissertation, they are quite specific and easy to understand.
Computer science dissertation requirements:
1.Computer science dissertations are all about evidence. And it doesn’t boil down to simple statement. It is your sophisticated analysis that gives your readers the understanding of why your problem is worth paying attention to. Who knows maybe you are the one to, finally, stop the process of aging with the help of the special computer chip. Maybe. But you will have to prove it in your computer science dissertation.
2.Computer science dissertation is also all about Methodology. Even though computerization today has reached its highest point, most of regular readers are experts at playing Pinball, but are absolutely useless to some technological innovations. As a researcher you will have to give a description of your steps detailed enough for it to be available and understandable to everyone (almost everyone).
3.Finally, any dissertation, and a computer science dissertation is no exception here, is absolutely nothing without strong results. Start with the most important of your findings, point out what was done right (pay attention to it) and where you made mistakes (try not to concentrate on it too much).
