Sentence examples for best case execution from inspiring English sources

Conversely, the best case execution of ApproMap occurs with equivalent datasets containing bnodes with varying numbers of connections and without any directly connected bnodes.

The worst and best case execution time (WCET and BCET) often play an integral role in this relation especially the former, which has applications in traditional methods for verification of schedulability such as response time analysis [1].

The complete timing model is a network of timed automata which directly facilitates safe estimates of worst and best case execution time to be determined using the Uppaal model checker.

Figure 1 illustrates the aim of a time-predictable architecture, showing the distribution of the different execution times for a task: they are best-case execution time (BCET), average-case execution time (ACET), worst-case execution time (WCET), and the bound of the WCET that an analysis tool can provide.

First, for each strategy A, B, C, we compute the best case and worst-case execution time of k instances of repeated consensus, based on two parameters α and β: The parameter α is the one used in Algorithm 5.

With the use of custom instructions, an improvement was reached of 23%, on average, but close to a 55% improvement, in the best case, which supposes a great amount of savings in time spent for execution.

This is the best case scenario since the data owner has as much control of the execution machine as possible, so our framework proposal can be applied in its full capacity.

The simulation Execution times ranged from 8 minutes for the 18GB simulation (best case) to 144 minutes for the 200GB simulation (worst case).

The proposed distributed PF achieves a total execution time of (2M/K + K + 2 + TL) in the best case to (2M/K + K + M + 2 + TL) in the worst case.

Execution time and response time can be further classified into worst case (wc), best case (bc), and average case (ac) times.

The lower bound is trivial to compute as the best case is when all n tasks are equally distributed among the k available resources and require approximately the same execution time.