Abstract: In order to diagnose applications, a specialized knowledge base may be created that is static upon creation but may become dynamic when traversed. The knowledge base may be defined as a decision tree having one or more diagnosis nodes, one or more analysis nodes, and one or more symptom branches. The diagnosis nodes are leaf nodes and indicate proposed diagnoses and/or proposed remedies for an application. The symptom branches may connect analysis nodes to other analysis nodes or analysis nodes to diagnosis nodes, and may indicate possible symptoms of the application. The analysis nodes may be non-leaf nodes and indicate information required to determine which symptom branches to follow during traversal. Additionally, the analysis nodes may indicate additional information required from a collector agent before traversal can be continued. This allows the knowledge base to be utilized dynamically, improving performance and reliability.

Abstract: A server has a memory and an analyzer. The memory stores a library of symptom descriptions, a library of corresponding diagnoses, a library of corresponding remedies, and a library of corresponding probes. The analyzer is coupled to the memory and has an identifier, a comparator, and a reiterater. The identifier identifies at least one symptom of an application to be probed based on an input. That input can either be a user input describing the symptoms of the application or symptoms previously already identified. The comparator compares the symptoms of the application with the library of symptom descriptions. The reiterator reiteravely operates the identifier on the comparator until the symptoms correspond with a diagnosis from the library of corresponding diagnoses.