To generate data we simulate models for enough number of steps (see Figure TBA) to sample reaching tSCC of the model {representing number os sucesses}. Each experiment consists of 3500, 1500, and 100 runs respectively {1500, and 100 run experiments are the first 1500 and 100 runs of the 3500 run experiment respectively} for each of parametrisation {point in parameter space} as a random uniform distribution of 5 values in each dimension. As two-param models {asynch,semisynch, and synch} have the same probabilities of reaching each tSCC of the model we only simulate synchr. models.
To generate data we simulate models for enough number of steps (see Figure TBA) to sample reaching tSCC of the model {representing number os sucesses}. Each experiment consists of 3500, 1500, and 100 runs respectively {1500, and 100 run experiments are the first 1500 and 100 runs of the 3500 run experiment respectively} for each of parametrisation {point in parameter space} as a random uniform distribution of 5 values in each dimension. As two-param models {asynch,semisynch, and synch} have the same probabilities of reaching each tSCC of the model we only simulate synchr. models.