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.

Systems and methods provide techniques for more effective and efficient predictive monitoring of a software application framework. In response, embodiments of the present invention provide methods, apparatuses, systems, computing devices, and/or the like that are configured to enable effective and efficient predictive monitoring of a software application framework using incident signatures for the software application that are generated by using a natural language processing machine learning framework, a structured data processing machine learning model, and an incident severity level detection machine learning model.

Systems and methods are described herein for logging system events within an electronic machine using an event log structured as a collection of tree-like cause and effect graphs. An event to be logged may be received. A new event node may be created within the event log for the received event. One or more existing event nodes within the event log may be identified as having possibly caused the received event. One or more causal links may be created within the event log between the new event node and the one or more identified existing event nodes. The new event node may be stored as an unattached root node in response to not identifying an existing event node that may have caused the received event.

A method, system, and apparatus for fault detection in a microprocessor-based system uses a serial data communication protocol for communications between a peripheral device and a controller. Peripheral device interface circuitry is adapted to intermittently receive input serial data frames from the controller using the serial communication protocol and to intermittently send output serial data frames to the controller using the serial communication protocol. Each output serial data frame includes one or more status bits representing communication status data and one or more data bits representing peripheral device data. The status bits and the data bits are serially followed by at least one fault bit that indicates whether a fault is detected during sending of the output serial data frame.

The present disclosure relates to processing operations that assess the impact of data invalidations and manage remediation of the data invalidations based on results of an assessment of the impact of the data invalidation on operation of an application/service. Identified data invalidations may be aggregated and analyzed. In one non-limiting example, types of data invalidations are aggregated over a temporal count to identify recent data invalidations. Analysis of aggregated types of data invalidations comprises evaluating an intensity of the types of data invalidations identified within the temporal count. Identified data invalidations may be ranked based on intensity analysis identifying impact on presentation of content through an application/service during the temporal count. Remediation of data invalidations may be managed based on the ranking processing. For example, one or more data invalidations may be prioritized for remediation processing to correct an underlying data structure associated with an error.

Examples include aggregating logs, where each of the logs is associated with a workflow instance. Each log includes information indicative of an event occurring during the workflow instance. Further, examples include assigning, based on user intent of the workflow instance, a workflow name to each log, where the user intent is indicative of an outcome of execution of the workflow instance and assigning an instance identifier to each log, where the instance identifier corresponds to the workflow instance. Further, identifying a subset of the plurality of logs having an identical workflow name and an identical instance identifier, associating a tracking identifier to the subset, and creating an index of processed logs, wherein each processed log in the index includes the tracking identifier. Further, analyzing the index of processed logs based on a set of rules and identifying, based on the analysis, an error in execution of each the workflow instance.

A method of error logging includes: receiving from a user interface a first input from a user indicating that they have seen a visible error in a displayed graphical output of a computer application, tracking the gaze of the user to estimate the position, on at least a first display showing at least part of the displayed graphical output, at which the user's gaze is directed, receiving from the user interface a second input from the user indicating that they have identified the visible error with their gaze, capturing data relating to the displayed graphical output of the computer application, the data including a capture of at least part of the displayed graphical output including the identified visible error, and the estimated positon of the user's gaze with respect to the displayed graphical output, and generating an error report including the captured data.

Decentralized cloud service assessment includes using a self-executing data structure, an error confirmation capsule (ECC) generated in response to a cloud service failure experienced by a cloud service client (CSC). One or more technical performance indicia corresponding to the cloud service failure are extracted from the ECC in response to the validating. The one or more technical performance indicia are compared to one or more electronically stored predefined performance norms of a cloud service provider (CSP) associated with the cloud service failure. Based on the comparing, a comparative ranking of the CSP is determined. A graphical user interface display is generated based on comparative rankings of the CSP and one or more other CSPs.

Disclosed embodiments provide techniques for generating and using a Global Error-Code Sequence (GECS), with the role of generating, at request, a unique error identification number (ID). The scope of the unique identification number can include worldwide, company-wide, or a certain application ecosystem, such as eCommerce applications, etc. The GECS forms a strong correlation between an error condition and a known solution. While other logging signatures such as line numbers, stack traces, and addresses can change with new releases or invocations, the GECS enables a tighter coupling between an error condition and a knowledgebase document, which enables faster resolution of computer application problems and reduced downtime.

A method for locating a fault information is provided. The method includes: parsing error information of a target application to obtain version information and an error attribute of the target application; determining, based on the version information, a target mapping file corresponding to the error information; and determining a target location by utilizing the error attribute and the target mapping file, where the target location is used to determine a location of fault description content.