machines.zip contains the set of state machines in GraphViz dot format. Some of these have had to be converted from other formats. Inference_Classification_Result_Data.zip contains the raw data returned by the Mint inference tool for each subject system. For each machine this produces six files: One file with the suffix _inference, which contains the raw data. The heading for this file is: Model, Data_inference_algorithm, random_seed, k-tails, infer_data, merging_algorithm, alpha, belief, disbelief, uncertainty, predicted, actual, num_states, num_transitions These are defined as follows: * Model - name of the model from which traces have been sampled. * Data_inference_algorithm - remains constant at J48 and is ignored * random_seed - the random seed used to infer the model. * k-tails - remains constant at 0. * infer_data - remains constant (false) - there are no data variables in the traces. * merging_algorithm - remains constant at 'redblue'. * alpha - the uncertainty threshold set - either 250, 500, 1000, or 2000. * belief - the belief for the prediction for the given row. * disbelief - the disbelief for the prediction for the given row. * uncertainty - the uncertainty for the prediction for the given row. * predicted - does the inferred model predict an accept or reject * actual - is the correct response an accept or reject * num_states - number of states in the inferred model * num transitions - number of transitions in the inferred model The file with the suffix "inference stats" contains some stats for the target model. The heading (which is quite self-explanatory) is: num_states, num_transitions, alphabet_size The remaining four files are for the prioritisation experiment. These have the following suffixes: _prioritise_coverage.csv _prioritise_gower.csv _prioritise_prioritised.csv _prioritise_random.csv These contain the APFD results for the prioritisation experiments for coverage, information distance (Gower), our uncertainty based coverage, and random selection respectively. These all share the same format: seed, iteration, mutation score. the file SOSMScripts.rmd is an R Markdown language, which contains the various analyses that were used to derive the statistics and charts for the paper from the classification results. mint.jar is included for completeness - this is the version of MINT that was used.