Authors: Chetan Giridhar, Rahul Verma
image: http://freedigitalphotos.net/
“Man! It’s taking ages to boot-up!”
“Why does it take so long to boot-up, that wasn’t the case when I bought it!”
“Has it really slowed down, or I feel so?”
“Should I remove the XYZ tool from start-up to improve boot-up time? I would miss it if I have to.”
These and a bunch of other questions pop-up when it comes to quantitatively measuring the boot-up time. There are situations, especially in the professional testing world, where saying “I feel it is slower” wouldn’t suffice. First challenge is to measure boot time with a tool, the subsequent challenge is being able to develop automation around it so that multiple iteration data is taken for analysis.
Keeping a low boot time is imperative and a product development team wouldn’t want its application to be responsible for slowing down a desktop bootup time. One of the critical performance tests is measuring the impact of your application on the bootup time of the user computer. The measurement of bootup time helps to:
- check health of your computer/laptop in terms of booting time. This would be especially of use after you have installed a new application.
- compare the bootup time with your product versus the competitor product
- compare the bootup time with a product by choosing certain options that add to boot time activities (e.g. certain application would give an option to be started at boot time)
- set up a baseline via a given build and comparing against it for subsequent builds…
