Abstract: According to examples, an apparatus may include a processor that may generate a migration assessment for resources of a computer system. In particular, the apparatus may logically divide topological information to facilitate identification of a resource, components used by the resource, and dependencies. The system further enables users to specify user-defined migration parameters that specify the migration. For instance, the parameters may specify a cost associated with the migration of the component, a license model of the component, a security requirement of the component, a performance of the component, a customization of the component, or requirement of the component. Migration assessments and decisions may be stored to train machine-learned models. For instance, the model may assess whether a parameter will be satisfied by using a certain cloud service and whether substitutes have sufficiently satisfied dependencies based on observed migration assessments and actual migrations.

Abstract: A primary blockchain for a software application is created that comprises a first block associated with a software component of the software application. An event is received that is associated with the software component. In response to receiving the event, a component blockchain is created that is associated with the software component. The component blockchain comprises a second block associated with the event. The component blockchain links to the primary blockchain. This provides a structure for managing supply chains of software components. As new software components are received, the new software components can be managed and tracked for quality/security.

Abstract: A copy of a blockchain is stored. The stored copy of the blockchain is copied from a blockchain in a distributed blockchain ledger. An event associated with the blockchain in the distributed ledger is identified. In response identifying the event associated with the blockchain in the distributed ledger, a compromise of the blockchain in the distributed ledger is identified, such as, identifying one or more blocks of the blockchain that have been compromised. In a second embodiment, a request to add a new block to a blockchain is identified. In response identifying the request to add the new block to the blockchain, a consensus vote to add the new block to the blockchain is monitored. A determination is made to determine if the consensus vote is below a threshold. In response to the consensus vote being below the threshold, an audit of the blockchain is completed.

Abstract: A first application name is received. For example, the first application name may be the name of the application, a Universal Resource Locator (URL) of a web site (e.g., microfocus.com), and/or the like. The first application name represents a computer application of a plurality of computer applications that the user logs into. A global password is received from the user. The global password is used as a seed to login to the plurality of computer applications. The global password is converted to a phonetic password. A first application password is generated for the first computer application based on the first application name and the phonetic password. For example, the first application name and the phonetic password are used as an input to a key deviation function. The first application password is then displayed to the user. The user can then use the displayed password to login to the first application.

Abstract: According to examples, an apparatus may include a processor that may schedule virtual users in a load test of a system under test. An apparatus may access user-specified or prestored points. Each point may represent a number of virtual users that is to place a load on the system under test at a given time. The apparatus may apply curve fitting, such as Bézier curve fitting, to generate a curve on a graph in which one axis represents time and another axis represents a number of virtual users at a given time. In some examples, the apparatus may use a smoothing factor to adjust the contours of the generated curve. The apparatus may use the curve to determine curve-fitted points to schedule virtual users at times corresponding to the curve-fitted points. To instantiate the virtual users, the system may use coroutines to reduce computational requirements for instantiating the virtual users.

Abstract: In some examples, test relevancy prediction for code changes may include ascertaining files for a commit for a build, and for each test of a plurality of tests, determining a score based on a weight assigned to a file of the ascertained files. Test relevancy prediction for code changes may further include ordering each test of the plurality of tests according to the determined score, and identifying, based on the ordering of each test of the plurality of tests, tests from the plurality of tests for which the score exceeds a specified threshold. The identified tests may represent tests that are to be applied to the build.

Abstract: A non-transitory computer readable medium can store machine readable instructions that when accessed and executed by a processing resource cause a computing device to perform operations. The operations can include establishing a connection between data stores (such as a relational data store and a graph engine), wherein the connection includes a shared memory buffer storing data in a data format according to internal structures of the graph engine. The connection between the data stores is bi-directional. The connection enables data that is stored in the shared memory to be processed by either of the graph engine and the relational database. Upon receiving a query, the graph engine or the relational database can be selected to process the data based on a query. The data can be processed by the selected one of the graph engine or the relational database.

Abstract: In one example, a system for gesture buttons can include a processing resource and a non-transitory computer readable medium having stored thereon instructions to cause the processing resource to perform a first function in response to a gesture provided to the user interface, display a gesture button on the user interface, and perform a second function that is different than the first function in response to the gesture provided on the gesture button displayed on the user interface.

Abstract: A hierarchical representation of entities relate to development of at least one product. A portion of a document is selected. For the selected portion of the document, an indication associated with at least one of the entities in the hierarchical representation is received. Based on the received indication, a link is created between the selected portion of the document and the at least one of the entities in the hierarchical representation.

Abstract: According to examples, an apparatus may include a processor and a non-transitory computer readable medium on which is stored machine readable instructions that may cause the processor to identify Internet protocol (IP) addresses and connection attributes associated with the IP addresses. The instructions may also cause the processor to train a machine learning model using the IP addresses as inputs to the machine learning model and connection contexts as outputs of the machine learning model. The machine learning model may learn a first weight matrix corresponding to the IP addresses and a second weight matrix corresponding to the connection contexts. In addition, the connection contexts may be concatenations of the connection attributes associated with a corresponding IP address.

Abstract: Network communication events are filtered to remove the network communication events having a predicted unrelatedness to beaconing. Each network communication event has a timestamp, a source entity, and a destination entity. The filtered network communication events are aggregated by unique source entity-destination entity pairs. For each unique source entity-destination entity pair, the network communication events are timestamp-sorted, time differentials between the timestamps of adjacent network communication events are calculated, and a beacon likelihood metric is calculated from the calculated time differentials. Which of the unique source entity-destination entity pairs are indicative of beaconing are identified based on the beacon likelihood metric calculated for each unique source entity-destination entity pair.

Abstract: According to examples, an apparatus may include a memory on which is stored instructions that when executed by a processor, cause the processor to cluster a set of data points into a hierarchy of a plurality of clusters, in which each level of the hierarchy includes a different number of the plurality of clusters. The processor may also select a number of the plurality of clusters to be used in modeling behaviors of the plurality of clusters and for each cluster of the selected number of the plurality of clusters, determine a distribution type of the cluster. The processor may further merge the distribution types of the clusters to generate a mixture model, identify an event, evaluate the event based on the generated mixture model to determine whether the event is likely anomalous, and based on a determination that the event is likely anomalous, execute a response action.

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, may cause the processor to track traffic events and user interface (UI) events in parallel and record a first event of a hybrid test script. The first event may be recorded in a traffic mode to record one or more of the traffic events. The processor may transition from the traffic mode to a UI mode and, responsive to the transition from the traffic mode to the UI mode, may share session data between the traffic events and the UI events. Based on the session data, the processor may record a second event of the hybrid test script in the UI mode.

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: An example method comprises performing for each class from a plurality of classes: constructing binary training set for the class, the binary training set including labeled cases for that class from the main training set other labeled cases from the main training set; training classifier for the class on the binary training set; computing a local calibration threshold using scores of the labeled cases in the binary training set; and adjusting all scores of the label cases in the binary training set with the local calibration threshold to meet a global decision threshold. The method also comprises determining, with the processor, a global hierarchical calibration threshold by using the adjusted scores for all classes to optimize a performance measurement of all trained classifiers. The method further comprises classifying, with the processor, a new case by using a previously trained classifier, a local calibration threshold, and the global hierarchical calibration threshold.

Abstract: A first device nonce and a first Hash based Message Authentication Code (HMAC) of the first device nonce using an old password as a key is received. The received first HMAC is compared to a computed second HMAC of the received first device nonce using a stored old password as the key for a match. In response to the match, a third HMAC of a second device nonce using the stored old password as the key is computed. A change password acknowledgement message is sent to the first device that comprises the second device nonce and the third HMAC. A final secret is computed using a second device secret and the first device nonce. A new password using a key derivation function that uses the old password and the final secret is computed. Thus, a new password is generated without sending the password over a network.

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: 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.