Abstract: A method of analyzing problem data from a computer application is disclosed. The method evaluates a memory dump, identifying call stacks within the memory dump that are related to application failures, creates a hash of the identified call stack and adds the hash to a database. The database may then be evaluated to look for trends in the error data such as whether the same call stack is causing problems.

Abstract: In embodiments of the invention, selected aspects of a process' call stacks are hashed, and the hash is used to capture the execution state of the process in a concise form and with minimal impact on the performance of the process and with no modification to the process code. The hash allows vendors and developers to classify failures in order to associate them with their known root causes to support rapid customer feedback and to maximize efficiency of correction. Further, the hash provides a metric usable to prioritize diagnosis of failures. In an embodiment of the invention, the identities of modules on the call stack are hashed in combination with some but not all offset information to minimize the affect of patches and minor changes to the code, and improve the ability to discriminate different execution paths.

Abstract: A method of analyzing problem data from a computer application is disclosed. The method evaluates a memory dump, identifying call stacks within the memory dump that are related to application failures, creates a hash of the identified call stack and adds the hash to a database. The database may then be evaluated to look for trends in the error data such as whether the same call stack is causing problems.