Abstract: Described are various embodiments of a system and computer-implemented method for error reproduction in web-based applications. In some embodiments, method comprises the steps of categorizing, by a processor, error information associated with the reported application error experienced by a plurality of users in a plurality of user sessions to determine a plurality of associated grouped events. In some embodiment, the error information comprises, for each user session, one or more user events and associated application information. The method further comprises the step of isolating from the plurality of associated grouped events, one or more designated grouped events causing the reported application error; and identifying, by the processor, from the one or more designated grouped events, a direct path causing the reported application error. In some embodiments, clustering analysis is performed by doing semantics clustering analysis via one or more machine learning models.

Abstract: Systems and methods for tracking and ranking errors in computer systems may be used in e-commerce applications in order to identify errors that occur in e-commerce user sessions along with an estimate of potential lost revenues resulting from the error. The errors and associated lost revenues may allow prioritizing of which errors to address.

Abstract: Systems and methods for tracking and ranking errors in computer systems may be used in e-commerce applications in order to identify errors that occur in e-commerce user sessions along with an estimate of potential lost revenues resulting from the error. The errors and associated lost revenues may allow prioritizing of which errors to address.