Given a partially observable dynamic system and a diagnoser observing its evolution over time, diagnosability analysis formally verifies (at design time) if the diagnosis system will be able to infer (at runtime) the required information on the hidden part of the dynamic state. Diagnosability directly depends on the availability of observations, and can be guaranteed by different sets of sensors, possibly associated with different costs. In this paper, we tackle the problem of synthesizing observability requirements, i.e. automatically discovering a set of observations that is sufficient to guarantee diagnosability. We propose a novel approach with the following characterizing features. First, it fully covers a comprehensive formal framework for diagnosability analysis, and enables ranking configurations of observables in terms of cost, minimality, and diagnosability delay. Second, we propose two complementary algorithms for the synthesis of observables. Third, we describe an efficient implementation that takes full advantage of mature symbolic model checking techniques. The proposed approach is thoroughly evaluated over a comprehensive suite of benchmarks taken from the aerospace domain.

Lehnert's Plot Units (Lehnert 1981) or Rumelhart's Story Grammars (Rumelhart 1980), and naturally, one would like We give semiformal We aim at capturing the informal human notion of equivalence definitions in § 2 and then give a few examples (without any of stories in a formal system in such a way that formal details) in § 3. two stories are perceived as equivalent when their formal representations are isomorphic (cf. There is no unique "human Comparing the adequacy of frameworks is not a formal task, notion of equivalence of stories" as the research on analogical but deals with the degree of representation of the informal reasoning shows (Rattermann and Gentner 1987; notions in the formal setting.