{'fraction_non_alphanumeric': 0.020858895705521473, 'fraction_numerical': 0.0, 'mean_word_length': 5.181818181818182, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A polynomial algorithm for testing diagnosability of stochastic discrete event systems

Failure diagnosis in large and complex systems is a crucial task. In this paper, we propose a polynomial algorithm for testing A-diagnosability (the idea is that a failure can be diagnosed after a finite delay was not “all-or-nothing” propositions, but had a certain probability) of stochastic discrete event systems. We construct a stochastic diagnoser by appending to each transition a vector that can be used to update the probability of the event occurring. A necessary and sufficient condition for A-diagnosability is obtained by properties of the stochastic diagnoser which is not a stochastic automaton, but possesses a structure superficially similar to one. Moreover, some examples are given to illustrate the results.