Methods and systems are described herein for improvements for cybersecurity of telecommunication devices. For example, cybersecurity for telecommunication devices may be improved by analyzing activity log data of telecommunication devices for a candidate event (e.g., the uploading of malware) and disabling one or more services of a telecommunication device. By doing so, cybersecurity for telecommunication devices may be improved by detecting a possible malware intrusion attempt and disabling one or more services of the telecommunication devices. For example, activity log data of telecommunication devices may be obtained. A candidate event indicating malware may be detected in the activity log data. A number of proximate telecommunication devices satisfying a proximity threshold condition may be determined. The number of proximate telecommunication devices that satisfy a density threshold condition may be determined. Responsive to the number of telecommunication devices satisfying a density threshold condition, services of telecommunication devices may be disabled.

Technologies for providing shared memory for accelerator sleds includes an accelerator sled to receive, with a memory controller, a memory access request from an accelerator device to access a region of memory. The request is to identify the region of memory with a logical address. Additionally, the accelerator sled is to determine from a map of logical addresses and associated physical address, the physical address associated with the region of memory. In addition, the accelerator sled is to route the memory access request to a memory device associated with the determined physical address.

Described herein are example systems and computer-implemented methods for monitoring changes to an application. For example, information regarding a change made to an aspect of an application may be received by a processor. It, may be determined if a similarity of the change to a cluster of changes related to the aspect is within a change threshold. Further, the change may be associated with the cluster of changes when the similarity of the change is within the change threshold. It may be further determined if a metric based on a number of changes associated with the cluster of changes is within a cluster range. When the metric within the cluster range, a prototype change may be extracted from the cluster of changes. The application may be updated based on the prototype change when the metric is within the cluster range.

A technology is disclosed for the efficient capturing of monitoring data capable to reconstruct the experience of a user during the interaction with an application on a mobile device. The proposed approach uses instrumentation to detect the occurrence of events that change the user interface of the monitored application and that, in response to such an event, identifies the fraction of the user interface that was altered by the event and then captures only the changed portion of the user interface display. Additionally, privacy configuration data is evaluated during the capturing process to identify portions of the user interface that contain data that is protected due to privacy policy settings. In case an event changes such a privacy protected user interface portion, only the occurrence of the event and the affected screen area are captured, but no actual display data.

Techniques described herein relate to a method for deploying workflows with data management services. The method may include identifying, by a warranty measuring model associated with an information handling system, a first change event associated with the information handling system; obtaining first change information associated with the first change event; making a first determination that the first change event is not associated with an entry of a warranty audit table (WAT); generating a new WAT entry in the WAT using the first change information and an initial timestamp; identifying, by a warranty measuring model, a second change event associated with the information handling system; obtaining second change information associated with the second change event; making a second determination that the second change event is associated with an existing WAT entry of the WAT; updating the existing WAT entry using the second change information and a final timestamp.

A system and method for determining automated uptime of internet-based software may include one or more memories storing check suites, each check suite including an ordered sequence of a plurality of checks corresponding to an execution flow of an ordered sequence of functions of the internet-based software; and one or more processors configured to determine a total amount of down time for a monitoring period by: during each time interval of the monitoring period, performing each of the plurality of check suites on the internet-based software, and applying at least one weighing factor to results of performing each of the plurality of check suites.

A first device executing an application determines data indicative of conditions associated with the first device during use of the application. Based on correspondence between this data and threshold data that indicates conditions in which frames representing a display output of the first device should be stored, the first device is caused to send data indicative of these frames to a second device. The second device generates user interface data based in part on the received frames and may send the user interface data to other devices. To reduce the amount of data sent and the computational resources used, the first device may store only changed frames of display output, and may send data to the second device at times when a communication interface of the first device is active for other purposes.

Methods, systems, and computer-readable media for analysis of code coverage differences across environments are disclosed. A code coverage profiling system determines a first code coverage profile associated with execution of program code in a first environment. The first code coverage profile indicates one or more portions of the program code that were executed in the first environment. The code coverage profiling system determines a second code coverage profile associated with execution of the program code in a second environment. The second code coverage profile indicates one or more portions of the program code that were executed in the second environment. The code coverage profiling system performs a comparison of the first code coverage profile and the second code coverage profile. The comparison determines a difference between the portions of the program code that were executed in the first and second environments.

An example software patch difference device includes a processor to: receive current software version indicators of software installed at monitored devices; generate, using a cryptographic function, respective identifiers of the current software version indicators for the monitored devices; retrieve, from storage, respective previous identifiers of previous software version indicators of the software installed at the monitored devices, the respective previous identifiers generated using the cryptographic function; compare, for the current software version indicators, a respective identifier with a respective previous identifier; when a difference is determined therebetween for a given device: replace, at the storage, respective previous software version indicators for the given device with respective current software version indicators; and transmit, to an analytics device, a respective software change indicator of the given device, to trigger the analytics device to generate a report indicating statistics for respective software versions installed at the monitored devices.

Techniques for filtering telemetry data to allocate system resources among system components are disclosed. A system filters a data set of telemetry data prior to allocating or re-allocating system resources to system components. A filtered data set includes data points that include the highest resource-utilization values for the system components. The system compares resource-usage for each component managed by a computing machine in one time period to the resource-usage for the component in another time period. The system omits from a filtered data set any time period in which the resource-usage value for each system component is subsumed by the resource-usage values of the same system components in another time period. The system generates resource-reallocation candidate models for the computing machines in the system based on the filtered data set. The system reallocates system resources among system components using a selected resource-reallocation candidate.