This PhD thesis deals with fault diagnosis of discrete-event systems modeled as finite state automata with some extensions to bounded Petri net models. The developed contributions can be classified regarding two pioneering approaches from the literature: the diagnoser-based technique and the twin-plant based technique. Regarding the diagnoser-based technique, we propose a new diagnoser variant with some interesting features that allow us to reformulate a necessary and sufficient condition for diagnosability of permanent faults and propose a systematic procedure for checking such a condition without building any intermediate model. An on-the-fly algorithm, for simultaneously constructing the diagnoser and verifying diagnosability is then developed. The established diagnoser is then extended to deal with fault diagnosis of intermittent faults. A Hybrid version (in the sense of combining enumerative and symbolic representations) of our diagnoser is also established in order to deal with fault diagnosis of labeled bounded Petri nets. The developed approaches are implemented in dedicated tools and evaluated through benchmarks with respect to the reference approaches in the domain.Regarding twin-plant based technique, our contribution consists in elaborating a model-checking framework that extends the Cimatti's work for the actual verification of various diagnosability concepts pertaining to permanent and intermittent failures based on the twin-plant structure. The main idea is to reformulate and express the diagnosability issues as temporal logics and then to tackle them using the model-checking engines.