Multiple error diagnosis based on Xlists

In this paper, we present multiple error diagnosis algorithms to overcome two significant problems associated with current error diagnosis techniques targeting large circuits: their use of limited error models and a lack of solutions that scale well for multiple errors. Our solution is based on a non-enumerative analysis technique, based on logic simulation (3-valued and symbolic), for simultaneously analyzing all possible errors at sets of nodes in the circuit. Error models are introduced in order to address the “locality” aspect of error location and to identify sets of nodes that are “local” with respect to each other. Theoretical results are provided to guarantee the diagnosis of modeled errors and robust diagnosis approaches are shown to address the cases when errors do not correspond to the modeled types. Experimental results on benchmark circuits demonstrate accurate and extremely rapid location of errors of large multiplicity