Why this analysis?
For example: Moving around bitmaps, as shown in Gavrilov’s Bubblemark benchmark, may sound simple but heavily relies on multiple aspects of a RIA runtime: First, to display images, a graphic-buffer needs to be filled with the bitmap data. Then it needs to be drawn to a canvas-like component and finally shown on the screen. To move around the images, mathematical calculations are required to let the balls bounce from the walls. Furthermore, some kind of data structure like (dynamic) lists or arrays must be used in order store each ball-object in. While running the test, one never knows what was the cause for performance decreases. Was it the »physics engine«, the image processing calls, the array/list operations or something else?
This lead to the idea of developing a series of tests to drill down to the core of performance issues, which leads to two benefits: One is that developers who already know their requirements for their applications can choose the RIA technology that fits best for their needs, based on the result of these test series. The other one is that RIA manufacturers can optimize their virtual machines and browser plug-ins based on the conclusions of this thesis.
Run the tests, download the source and view the results here.
Feel free to download everything and play around with it. Most of the sources are released under the MIT license. Some others use GPL or BSD so make sure to check the license agreement in the header sections of each project/file but in general you don’t really have to worry about them since they’re all open source licenses. Just watch out for the copyleft agreement in GPL.