Abstract: Examples herein disclose via use of a physical processor, detecting a specific application programming interface (API) call to interact with an application running on a production server. Based on the detection of the specific API call, die examples assist, using the physical processor, a scanning session based on the specific API call Using the physical processor, the examples identify a modification to the application based on the scanning session.

Abstract: According to examples, an apparatus may include a processor that may automatically restore a backup copy from a remote backup storage system to a user device without a user request to do so. For example, the apparatus may, at various times without user intervention, determine whether a restoration of a backup copy of local data is to be performed based on various criteria for automatically restoring the backup copy without a user request to do so. Based on satisfaction of the criterion, the apparatus may restore the backup copy to the original location of the local data (to immediately replace the local data) and/or to a temporary location accessible to the apparatus (such as via onboard storage) from which the backup copy may replace the local data at a later time (such as on-demand).

Abstract: An apparatus may include a processor that may be caused to receive an authentication request to authenticate a user. The authentication request may include a one-time username associated with an identity of the user and a secret credential of the user. The processor may further identify, in a user registry, a unique user identifier based on the one-time username, and authenticate the user based on the unique user identifier and the secret credential. The apparatus may update the user registry to prevent the one-time username from being used again to identify the user for authentication.

Abstract: To write forgettable data to a blockchain, the forgettable data is transmitted to a server, from which encrypted data corresponding to the forgettable data are received. A hash of the forgettable data is generated. A data block including the encrypted data and control data including the hash is added to the blockchain.

Abstract: Example implementations relate to comparable UI object identifications. Some implementations may include a data capture engine to capture data points during test executions of the application under test. The data points may include, for example, test action data and application action data. Additionally, some implementations may include a data correlation engine to correlate each of the data points with a particular test execution of the test executions, and each of the data points may be correlated based on a sequence of events that occurred during the particular test execution. Furthermore, some implementations may also automatically identify, based on the correlated data points, a set of comparable UI objects.

Abstract: In some examples, an alert relating to an issue in a computing arrangement is received. Contextual information is determined for the alert, the determined contextual information comprising spatial and temporal distributions of previous instances of the alert or similar alerts. The contextual information is communicated for use in addressing the issue in the computing arrangement.

Abstract: A token generating organization may include distributed tokenization systems for generating tokens corresponding to sensitive information. Sensitive information may include sensitive numbers such as social security numbers, credit card numbers or other private numbers. A tokenization system may include multiple physically distinct hardware platforms each having a tokenization server and a database. A tokenization server may run portions of a sensitive number through a predetermined number of rounds of a Feistel network. Each round of the Feistel network may include tokenizing portions of the sensitive number using a fractional token table stored an associated database and modifying the tokenized portions by reversibly adding portions of the sensitive number to the tokenized portions. The fractional token table may include partial sensitive numbers and corresponding partial tokens.

Abstract: In examples, a system adaptively orders a set of regular expressions based on frequencies that respective regular expressions of the set of regular expressions match a set of messages, the adaptive ordering to produce an adaptively ordered set of regular expressions. The system determines, for a first message of the set of messages, whether a plurality of regular expressions of the adaptively ordered set of regular expressions match the first message. The system constructs a bi-directional graph representing the plurality of regular expressions that match the first message, and classifies a second message based on the adaptively ordered set of regular expressions and the bi-directional graph.

Abstract: A system and method for a text search of a database, including converting a text search expression to a query plan and implementing the text search as the query plan on the database. The implementing of the text search includes a one-pass indexing as a single scan of an inverse index table associated with the database.

Abstract: A technique includes performing optimistic concurrency control to process a request associated with a transaction to change a schema of an object. Performing the optimistic concurrency control includes locally modifying the object to change the schema of the object based on the request; after locally modifying the object, locking a global catalog to block the object from being globally modified; validating the locally modified object based on the global catalog; and committing the modified object to a globally shared storage in response to the modified object being validated.

Abstract: This document describes debugging multiple instances of code by detecting a variance in thread patterns of threads of execution relative to the multiple instances of executing code. A first instance of the code is executed and a first thread pattern is identified indicative of a first plurality of threads of execution of the first instance of the code. A second instance of the code is executed, the second instance of the code beginning executing prior to the first instance of the code completing executing, and a second thread pattern is identified indicative of a second plurality of threads of execution of the second instance of the code. A comparative representation of the first thread pattern and the second thread pattern is generated relative to each other. A variance between the first thread pattern and the second thread pattern relative to the comparative representation is identified, the variance typically being indicative of a bug in the code.

Abstract: Information technology service management records in a service level target database table may include aggregating, at a predetermined elapsed time, a plurality of actions performed on each of a plurality of ITSM records since a prior update of an SLT database. Service level target tracking may further include identifying a portion of the plurality of aggregated actions that are applicable to an SLT database table entry corresponding to an ITSM record of the plurality of ITSM records. Service level target tracking may also include compressing, in a single operation, the portion of the plurality of aggregated actions.

Abstract: In some examples, a system executes a program that generates a user interface (UI) screen, provides a user input event to the program during execution, and captures images of the UI screen before and after the user input event. The system determines, based on the captured images, whether a first region of the UI screen changed in response to the user input event, and indicates the first region as a user interactive region and adds an element representing the user interactive region to a representation of user interactive regions of a UI of the program.

Abstract: A log event cluster analytics management method may involve storing a first portion of an entire cluster dictionary in a transient memory, storing at least a second portion of the entire cluster dictionary in a persistent database and comparing a new log event message to the first portion of the overall cluster dictionary. In response to not assigning the new log event message to any cluster in the first portion of the entire cluster dictionary in the transient memory, selecting a subset of clusters of the at least second portion of the cluster dictionary in the persistent database, comparing the new log event message to a cluster of the selected subset of clusters and assigning the new log event message to the cluster of the selected subset of clusters based upon the comparison.

Abstract: In some examples, device debugging connection control and maintenance may include receiving, from a debug tool, a connection request to connect to a device to be debugged. Based on the connection request, a primary socket connection may be implemented via a Universal Serial Bus (USB) channel to the device. Based on the connection request, a backup socket connection may be implemented via a Wi-Fi channel to the device. Based on the implementation of the primary socket connection and the backup socket connection, maintenance of a debugging session may be controlled during performance of a debugging operation.

Abstract: This document describes techniques and apparatuses for supporting web components associated with a document object model (DOM) corresponding to a data file in a web testing environment. A user interaction, relative to a web page or web application from which the DOM is rendered, is monitored in the web testing environment. The monitoring identifies a target element selected by the user that is referenced in a shadow DOM associated with the DOM. One or more parent shadow host elements of the DOM are identified relative to the target element. The one or more shadow host elements define a reduced path, with respect to a tree data structure representing the DOM and the shadow DOM, for linking a document object of the DOM to the target element. Indicia identifying the one or more shadow host elements as linking the document object of the DOM to the target element are recorded.

Abstract: Semantic consolidation of data is disclosed. One example is a system including a data processor, a semantic relations module, and a consolidation module. The data processor identifies at least two data objects, each data object including a plurality of data elements. The semantic relations module identifies, via a processor, semantically similar data elements of the plurality of data elements. The consolidation module merges the identified semantically similar data elements via the processor, and generates a consolidated data object based on the merged data elements.

Abstract: An application managed by a provider is configured to run according to a selected usage scenario of a group of usage scenarios. The group of usage scenarios include a hard-partitioned usage scenario in which instances of the application are hard partitioned in correspondence with tenants of the provider. The group of usage scenarios include a soft-partitioned usage scenario in which the instances of the application are soft partitioned in correspondence with the tenants of the provider. The configured application is executed.

Abstract: According to examples, an apparatus may include a processor and a memory on which are stored machine-readable instructions that when executed by the processor cause the processor to receive resource information correlated to a virtual private cloud (VPC). The resource information may be for discovery of resources in an instance in the VPC. The processor may upload the resource information to a cloud storage connected to the VPC. The resource information may be downloaded to an agent on the instance in the VPC to perform the discovery of resources in the instance to generate discovery information. The processor may receive the generated discovery information from the cloud storage. The generated discovery information may be uploaded to the cloud storage from the agent.

Abstract: A graphical user interface (GUI) of an application under test (AUT) is rendered. A GUI test object of the AUT is identified within the GUI. Test information regarding the GUI test object of the AUT is retrieved. The GUI test object of the AUT is rendered within the GUI to reflect the test information.