We thus propose that assumptions about dependability improvement, namely those brought upon by techniques of replication and rejuvenation, should be justified, rather than implicitly assumed.
We emphasize that, consistently with the enunciated goals of this paper, this is an objective way of measuring a dependability improvement brought upon by intrusion-tolerant replication in our system model.
By dependability improvement, we mean higher reliability ((mathcal{R})) or availability ((mathcal{A})), both dependability attributes, with (mathcal{R}) measuring the probability of never failing to maintain a certain property during a certain mission time, and with (mathcal{A}) measuring the probability of correctness at a random instant within an intended mission time.
Using a novel methodology we develop to benchmark human-assisted recovery processes, we also find that undo-based recovery has a net positive effect on dependability, providing significant improvements in correctness while only slightly degrading availability.
All but one of these measurements (dependability) showed significant improvement (p ≤ 0.05) as mentors rated themselves progressing from 12 weeks in the NE STEM 4U program to 24 weeks, n = 27.
Though the number of problems has continued to fall across the industry, the rate of improvement in dependability has slowed somewhat, Mr. Sargent said.
In particular, one could naively believe that the increase of the threshold of faulty components that a system can withstand always leads to the improvement of dependability of the overall system.
In doing so, we identify thresholds that make the difference between improvement and degradation of dependability.
In doing so, we identify thresholds that distinguish between improvement and degradation of dependability, with a focus on security.
One of our contributions here is in highlighting the MT thresholds that make a difference between improvement and degradation of dependability, while having a security perspective in mind.
