Abstract: Example embodiments disclosed herein relate to generating a point-wise protection based on dynamic security analysis. Vulnerability solution recommendation are provided based on the dynamic security analysis. A point-wise protection is generated based on a selection of the vulnerability solution recommendation.

Abstract: A automative management server for receiving information technology system events and wind turbine events; correlating the information technology system event with the wind turbine event to determine a cause of an event; and generating an alert reporting the cause of the event or taking action to resolve the root cause of the event.

Abstract: Described herein are techniques for generating a model based on input. In an example, a first model can be generated based on decomposing a rating matrix into a product of two matrices U and V, where U represents correlations between users and a plurality of factors and V represents correlations between items and the plurality of factors. At least some of the users and items can be grouped into groups according to the correlations. Input on one or more of the groups can be received. A second model can be generated based on the input on the one or more of the groups.

Abstract: Application management based on data correlations is disclosed. One example is a system including a data processor, a data element generator, a matrix generator, a data analysis module, a performance module, and a load test manager. The data processor accesses test data based on an application under load testing. The data element generator generates a plurality of transactional data elements based on the test data, each data element comprising at least three data components. The matrix generator generates a covariance matrix based on the data components. The data analysis module determines an eigenvector associated with the covariance matrix, and identifies a correlation between a sub-plurality of the at least three data components based on coefficients of the eigenvector. The performance module determines, based on the correlation, performance metrics for the application under load testing. The load test manager manages, based on the performance metrics, the application under load testing.

Abstract: In one example of the disclosure, incident data indicative of a crash of an application is obtained, the crash occurring during an access of the application by a user at a computing device. A session depth at which the crash occurred is determined based upon the incident data. Time period data is obtained, the time period data indicative of a time period, following the crash, until the user next accesses the application at the computing device. A severity score for the crash is determined based upon the session depth and the time period.

Abstract: In an example, an aggregate function is associated with an aggregate projection for a data storage system. Input data to be loaded into the data storage system is aggregated according to the aggregate function and stored in the aggregate projection.

Abstract: Interactive sequential pattern mining is disclosed. One example is a system including a sequence miner, and an interaction processor. A sequence database is received, the sequence database including a plurality of input sequences, where each sequence of the plurality of input sequences is an ordered list of events, and each event in the list of events includes at least one item. The sequence miner mines the sequence database for a plurality of candidate sequence patterns, the mining based on an interaction with a user. The interaction processor processes the interaction with the user, the interaction based on domain relevance of the plurality of candidate sequence patterns to the user.

Abstract: Example embodiments relate to measuring user interface (UI) responsiveness related to a UI of an application running on a computing device. An example method may include accessing a list of actionable controls, where the list indicates at least one UI control of the UI as being actionable. The method may include detecting a user interaction when a user interacts with a UI control of the UI. The method may include determining a list of change controls. The change controls are UI controls that change, refresh or load in response to the user interaction, which will ultimately be displayed on a next screen of the UI after the user interaction, and which are also on the list of actionable controls. The method may include determining a UI responsive time based on the list of change controls.

Abstract: Example implementations relate to database records associated with a trie. For example, a computing device may include at least one processor to receive a query string and determine, based on the query string, a lookup string associated with a plurality of words in an order. The at least one processor may identify, based on the lookup string and a trie associated with the lookup string, a set of records from a database of records, each record in the set being associated with a score that is associated with a degree to which each record matches the query string, wherein the set is identified based on a penalty value calculated for each record based on a hypothesized collection of typing errors sufficient to transform a prefix of a string associated with each record into the lookup string. The at least one processor may provide a result based on the set.

Abstract: Examples relate to identifying shortest paths. In one example, a computing device may: access an edge table that specifies, for each edge of a graph, an edge source, an edge destination, and an edge distance value; access a current path table that specifies paths between nodes of the graph and, for each path, a source node, a destination node, a distance, and a node path; identify each path included in the current path table as a shortest known path; and for each path having a destination node that matches an edge source node, add a new path to the current path table, the new path specifying: the source node as a new source; the edge destination as a new destination; a sum of the edge value and the path distance as a new distance; and the edge destination appended to the node path as a new node path.

Abstract: In one implementation, a static analysis system can include an operator engine to identify a modification operation on a string based on a structural comparison of program code to a static analysis rule, a label engine to maintain a label with the string based on the static analysis rule, and a sink engine to identify that the label denotes a string property and provide an analysis message associated with the string property based on the label.

Abstract: The present disclosure includes a system and method for apportioning power consumption. In an example of apportioning power consumption according to the present disclosure, a transaction mix for a service is determined (104, 204, 330, 420), component resource usage for each of a number of components that are used while completing the service is determined (106, 206, 108, 208, 422), and component power consumption for each of the number of components is determined by use of the component resource usage (334, 424).

Abstract: An application process can be executed based on an initialization instruction, where the application process includes instructions associated with a hook framework. A virtual machine configured to load the hook framework on the virtual machine based on instructions included in the application process can be initiated and the instructions associated with the hook framework can be executed upon initiation of the virtual machine to insert a hook on the virtual machine. A nascent process configured to initiate an additional virtual machine can be initiated based on a request to load an application, where the additional virtual machine is hooked via the hook inserted on the virtual machine.

Abstract: A technique includes comparing a first sequence of tasks of a first data processing pipeline of a plurality of data processing pipelines for a data streaming system to a second data processing pipeline of the plurality of data processing pipelines. The technique includes, based on the comparing, combining the first data processing pipeline and the second data processing pipeline into a single data processing pipeline.

Abstract: An example method is provided in according with one implementation of the present disclosure. The method comprises generating a group of most frequent elements in a dataset, calculating features of each of the most frequent elements in the dataset, applying a trained model to the features of each of the most frequent elements, and generating a list of predicted relevant elements from the list of most frequent elements. The method further comprises determining at least one element-chain group for each predicted relevant element and a group score for the element-chain-group, ordering a plurality of element-chain groups for the dataset based on the group score for each of the element-chain groups, and identifying a predetermined number of element-chain groups to be outputted to a user.

Abstract: Example embodiments relate to parallelizing structured query language (SQL) on distributed file systems. In example embodiments, a subquery of a distributed file system is received from a query engine, where the subquery is one of multiple subqueries that are scheduled to execute on a cluster of server nodes. At this stage, a user defined function that comprises local, role-based functionality is executed, where the partitioned magic table triggers parallel execution of the user defined function. The execution of the UDF determines a sequence number based on a quantity of the cluster of server nodes and retrieve nonconsecutive chunks from a file of the distributed file system, where each of the nonconsecutive chunks is offset by the sequence number.

Abstract: A technique includes applying a first mapping to associate a plurality of data records for a plurality of database nodes with a plurality of segments of a storage that is shared by the database nodes; and applying a many-to-many second mapping to associate the segments with the database nodes.

Abstract: Example implementations relate to separating verifications from test executions. Some implementations may include a data capture engine that captures data points during test executions of the application under test. The data points may include, for example, application data, test data, and environment data. Additionally, some implementations may include a data correlation engine that correlates each of the data points with a particular test execution state of the application under test based on a sequence of events that occurred during the particular test execution state. Furthermore, some implementations may also include a test verification engine that, based on the correlation of the data points, verifies an actual behavior of the application under test separately from the particular test execution state.

Abstract: In some examples, continuous integration and continuous deployment (CI/CD) system failure analysis and resolution may include analyzing data for a CI/CD system to identify anomalous tests related to the CI/CD system. A plurality of hypotheses on a cause of failure associated with the CI/CD system may be determined based on a further analysis of the analyzed data. The determined hypotheses may be prioritized based on a confidence level analysis. Failure resolution to prevent failure associated with the CI/CD system may be determine based on a response to one of the prioritized hypotheses. Further, the determined failure resolution may be implemented.

Abstract: In some examples, a first pair of parameters in respective first and second log message streams associated with respective first and second source components and a second pair of parameters in the respective first and second log message streams may be identified. The first pair may be identical and the second pair may be identical. It may be determined that first pair of parameters was simultaneously generated and that the second pair of parameters was simultaneously generated in the first and in the second log message streams. A linkage score may be determined between the first and the second source components. The linkage score may be based on the determination that each of the respective first and the second pairs of parameters was simultaneously generated. It may be determined that that the first and second source components are topologically linked based on the linkage score.