Implement non-functional fitness score about arc HOT 2 CLOSED

Well I had to revamp how the tester.py worked to correctly track the metrics we want. Currently we can get the min/avg/max of real-time and percent CPU. I figured these would be the most applicable as max memory shouldn't vary and wall-time might be inaccurate due to other testing processes.

The problem right now is I am unsure of how to assign the score (including the actual equation). If we just add values together we'll have to minimize the score (should we just try to maximize or does it seem more natural to minimize run-time).

from arc.

We decided to only consider real time (actual time, 'wall time') and the number of voluntary context switches.

The worst score still persists, but we now calculate it using the average values instead of max values (to avoid an edge case, when we have strong outliers).

The actual calculation is performed using the following equation:

score = worst_score / [sig_of_t(1-unc_of_t) + sig_of_c(1-unc_of_c)]

where sig_of{t,c}_ is the significant modifier of real time (t) or voluntary context switches (c). This is calculated using the following:

if t > c; sig_of_t = t/c && sig_of_c = c/t
if c > t; sig_of_t = c/t && sig_of_c = t/c

The unc_of{t,c}_ represents the uncertainty or variability of the measure:

unc_of_t = [max(t) - min(t)] / avg(t)
unc_of_c = [max(c) - min(c)] / avg(c)

from arc.