The present embodiments relate to proactive learning of network software problems. In an embodiment, a method includes receiving, by a detection system, webpage data from a computer system. The computer system can receive the webpage data from a plurality of client devices. The webpage data can be associated with user identifiers identifying each client device of the plurality of client devices. The detection system can then receive assistance data from a user assistance computer. The user assistance computer can receive the assistance data from a plurality of user devices. The assistance data can be associated with user identifiers identifying each user device of the plurality of user devices. The detection system can label the webpage data based on the assistance data including matching user identifiers and then determine at least a pattern based on the labeled webpage data.

A processing device, operatively coupled with the memory device, is configured to determine a first error rate associated a first set of pages of a plurality of pages of a data unit of a memory device, and a second error rate associated with a second set of pages of the plurality of pages of the data unit, determine a first pattern of error rate change for the data unit based on the first error rate and the second error rate, and responsive to determining that the first pattern of error rate change corresponds to a predetermined second pattern of error rate change, perform an action pertaining to defect remediation with respect to the data unit.

Various embodiments include a parallel processing computer system that detects memory errors as a memory client loads data from memory and disables the memory client from storing data to memory, thereby reducing the likelihood that the memory error propagates to other memory clients. The memory client initiates a stall sequence, while other memory clients continue to execute instructions and the memory continues to service memory load and store operations. When a memory error is detected, a specific bit pattern is stored in conjunction with the data associated with the memory error. When the data is copied from one memory to another memory, the specific bit pattern is also copied, in order to identify the data as having a memory error.

Methods and systems are presented for providing a framework to integrate independent fragment modules into an integrated user interface. The fragment modules can be simultaneously rendered on a user interface page or sequentially rendered across multiple user interface pages. The fragment modules are configured to interact with a user via the user interface. The interactions with the user may trigger an event. When an event associated with a fragment module occurs, the fragment module is configured to broadcast the event. An orchestrator is configured to monitor events associated with different fragment modules. The orchestrator may include an event handler for performing one or more action in response to an event. The action may include configuring another fragment module to modify a presentation and/or perform a transaction based on the event.

Root cause identification of a software defect includes identifying, in program code of a software feature, hedge code of the software feature based on errors induced from temporarily substituting program code of the software feature with substitute program code and obtaining an error graph for the hedge code, obtaining error logs of an application that incorporates the software feature, the error logs indicating errors with the software feature of the application, automatically generating an application error graph reflective of the errors with the software feature of the application, mapping the application error graph to the error graph for the hedge code, and based on the mapping aligning one of more errors reflected in the application error graph to error(s) reflected in the error graph for the hedge code, identifying the hedge code as inducing a root error identified in the application error graph.

The methods and systems improve uncorrectable error (UE) and silent data corruption (SDC) rates for memory chips and improve error correction of the memory chips. The systems may include a memory bank with a plurality of memory chips in communication with a memory controller. The memory bank may use one additional memory chip that stores a bitwise parity of the data stored in the remaining memory chips of the memory bank. The parity bits are used to rebuild corrupted data when a UE occurs. The parity bits are also used to detect whether a SDC occurred in the data.

A method of identifying errors or manipulations of data or software, includes receiving a first hash value stored in a first block of the memory, receiving a second hash value from a reference memory, and comparing the hash values. If different, error correction information and the content of the first block is received. The content of the first block is reconstructed by in accordance with the error correction information, generating a hash value and comparing the hash value of the modified content with the received first hash value, until the modified content and the received hash values are identical. The content of the first block received from the reference memory and the content of the reconstructed first block stored in the memory of the device are compared for identifying the differences in the content.

Embodiments may generally be directed to systems and techniques to detect failure events in data pipelines, determine one or more remedial actions to perform, and perform the one or more remedial actions.

Systems and methods for adaptive fault prediction analysis are described. In one embodiment, the system includes one or more computing components, and one or more hardware controllers. In some embodiments, the storage system includes a storage drive. At least one of the one or more hardware controllers is configured to analyze one or more tolerance limits of a first computing component among the plurality of computing components; calculate a failure metric of the first computing component based at least in part on the analysis of the one or more tolerance limits of the first computing component; analyze sensor data from the first computing component in real time; and update the failure metric based at least in part on the analyzing of the sensor data.

Various aspects include methods and devices for implementing the methods for error checking a memory system. Aspects may include receiving, from a row buffer of a memory, access data corresponding to a column address of a memory access, in which the row buffer has data of an activation unit of the memory corresponding to a row address of the memory access, determining multiple error correction codes (ECCs) for the access data using the column address, and checking the access data for an error utilizing at least one of the multiple ECCs. In some aspects, the multiple ECCs may include a first ECC having data from an access unit of the memory corresponding with the column address, and at least one second ECC having data from the access unit and data from the activation unit other than from the access unit.