Abstract: A model-based reasoning system for diagnosing faults in a computer network has an information base that stores information about the computer network. This information includes the topology of the network, a class hierarchy containing a component library and diagnostic expertise, and a diagnosis episode. A diagnosis engine receives a pointer to a situation. Each situation includes a focus role and a most general class for the focus role. Based upon this situation, the diagnosis engine creates a diagnosis episode, using the information stored in the information base.

Abstract: A fault diagnosis system which detects possible faulty components in a complex system. The complex system is represented by a representation comprising a plurality of nodes interconnected by links defining a flow among nodes corresponding to flows in the complex system. At least one of the nodes is a checkpoint node, which generates a report if the flow received by it is not correct. A fault diagnosis processor performing upstream search operation to repeatedly (such as by recursion of iteration) step in upstream path, that is, opposite to the direction of flow in the complex system, from node to node starting with the reporting checkpoint node. At each step, the fault diagnosis processor indicts components represented by both nodes and links in the representation.