Abstract: Examples herein involve estimating a first position of a mobile device based on first communication signals, assigning a first set of particles to a number of respective first sampling locations within a threshold distance of the first position, adjusting the assignment of the first set of particles to second sampling locations based on movement of the mobile device, and estimating a second position of the mobile device based on the second sampling locations.

Abstract: Examples herein involve estimating a first position of a mobile device based on first communication signals, assigning a first set of particles to a number of respective first sampling locations within a threshold distance of the first position, adjusting the assignment of the first set of particles to second sampling locations based on movement of the mobile device, and estimating a second position of the mobile device based on the second sampling locations.

Abstract: Examples herein involve estimating a first position of a mobile device based on first communication signals, assigning a first set of particles to a number of respective first sampling locations within a threshold distance of the first position, adjusting the assignment of the first set of particles to second sampling locations based on movement of the mobile device, and estimating a second position of the mobile device based on the second sampling locations.

Abstract: Examples herein involve estimating a first position of a mobile device based on first communication signals, assigning a first set of particles to a number of respective first sampling locations within a threshold distance of the first position, adjusting the assignment of the first set of particles to second sampling locations based on movement of the mobile device, and estimating a second position of the mobile device based on the second sampling locations.

Abstract: Examples herein involve estimating a first position of a mobile device based on first communication signals, assigning a first set of particles to a number of respective first sampling locations within a threshold distance of the first position, adjusting the assignment of the first set of particles to second sampling locations based on movement of the mobile device, and estimating a second position of the mobile device based on the second sampling locations.

Abstract: An apparatus may include a processor that may access and analyze a live log stream of activity of the containerized service and determine whether the containerized service is able to provide a capability of the service based on the analysis. For example, the processor may determine whether the containerized service is executing but is in a hung state and cannot provide the capability. To do so, the processor may parse the live log stream for comparison with log patterns that indicate that the service is no longer able to provide the capability. The patterns may be generated based on observations of output by services that are hung or otherwise cannot provide their respective capabilities. The processor may cause the container to be restarted when the analysis indicates that the capability is not being provided by the containerized service, such as when the containerized service is in a hung state.

Abstract: According to examples, an apparatus may include a processor and a non-transitory computer readable medium that the processor may execute to initiate a testing process of the apparatus following a boot up of the apparatus, in which a popup message is displayed on the apparatus following the boot up and the popup message blocks performance of the testing process and in which the apparatus is to enter into a lock mode following the popup message being displayed. While the apparatus is in the lock mode, the apparatus may be caused to emerge from the lock mode, in which emergence from the lock mode is to dismiss the popup message from being displayed on the apparatus. In addition, execution of the testing process of the apparatus may be continued following dismissal of the popup message.

Abstract: Format preserving encryption of object code is disclosed. One example is a system including at least one processor and a memory storing instructions executable by the at least one processor to identify object code to be secured, where the object code comprises a list of instructions, each instruction comprising an opcode and zero or more parameters. A format preserving encryption (FPE) is applied to the received object code, where the FPE is applied separately to a sub-plurality of instructions in the list of instructions, to generate an encrypted object code comprising a sub-plurality of encrypted instructions. An encrypted object code is provided to a service provider, where the encrypted object code comprises the sub-plurality of encrypted instructions, and any unencrypted portions of the object code.

Abstract: In one implementation, a system calculating a product risk profile includes a criticality score engine to calculate a criticality score via an aggregation of values assigned to a plurality of descriptions of a component of a product criticality. In addition, the system includes a vulnerability score engine to calculate a vulnerability score via an aggregation of a quantity of security risks found during a security assessment for the product. In addition, the system includes a product risk profile engine to calculate a product risk profile for the product via a multiplication of the criticality score and the vulnerability score.

Abstract: Examples disclosed herein relate, among other things, to determining a trend correlation. In one aspect, a method is disclosed. The method may include, for example, receiving a first data set associated with a first parameter of an electronic device and a second data set associated with a second parameter of the electronic device. The method may also include generating a first trend set based on the first data set, and generating a second trend set based on the second data set. The method may further include detecting, based on the first trend set and the second trend set, a trend correlation between the first parameter of the electronic device and the second parameter of the electronic device, and providing for display correlation information describing the trend correlation.

Abstract: In some examples, a method may include receiving, by a system comprising a processor, for a first invocation of a first test of a plurality of code coverage tests run at overlapping times, a first report indicating a first subset of files of application code covered by the first test. The method may include generating, by the system, a test-to-file map associating the first subset of files to the first test. The method may include receiving, by the system, a second report indicating a second subset of files of the application code covered by a second invocation of the first test. The method may include modifying, by the system, the test-to-file map to associate the second subset of files to the first test.

Abstract: A computer-implemented method includes determining a plurality of bulk sets for querying database records. The method also includes assigning a plurality of keysets to the plurality of bulk sets, with each keyset comprising a unique set of dimension attribute values from the database records. The method also includes calculating a predicted load score of each bulk set. The method also includes performing a transfer of a keyset from a first bulk set to a second bulk set when the transfer reduces a difference between predicted load scores of the first bulk set and the second bulk set. The method also includes, after the transfer, executing bulk queries using the plurality of bulk sets.

Abstract: The present subject matter relates to defect reporting in application testing. In an implementation, a category of application testing is determined based on a testing instance of an application. The category of application testing is indicative of an aspect of the application, being tested. A list of previously reported defects associated with the determined category of application testing is displayed in a display layer over the testing instance of the application. A first user-input indicative of one of acceptance and rejection of a previously reported defect, from the list, with respect to the testing instance of the application is received. The first user-input is aggregated with previous user-inputs indicative of one of acceptance and rejection of the previously reported defect. It is determined whether the previously reported defect is irrelevant to the testing instance of the application based on the aggregation.

Abstract: Role based assessment for an IT management system, includes maintaining a plurality of roles, each role attributable to a user type within an IT management system. Mappings are defined between the plurality of user roles and assets of the IT management system. An assessment for the IT management system is then assembled from the perspective of a selected one of the plurality of roles based on mappings between the selected user role and the assets.

Abstract: A non-transitory, computer readable storage device includes software that, while being executed by a processor, causes the processor to choose, based on user activity, a plurality of candidate parameters to be monitored from a plurality of event messages. Further, the processor executes the software to estimate a level of similarity between the chosen plurality of candidate parameters by computing a similarity score for at least two of the chosen candidate parameters. Still further, the processor executes the software to determine a plurality of parameters from the chosen candidate parameters if the similarity score for the plurality of parameters is greater than a threshold.

Abstract: Examples herein involve designating a first dimension of a thread visualization based on timing of a duration of a user action, the user action corresponding to a user interaction with an application; designating a second dimension of the thread visualization based on a number of threads of the application utilized for running tasks in response to the user action, the second dimension comprising a number of parallel timelines corresponding to the number of threads; determining locations for representations of the tasks within the appropriate parallel timelines of the thread visualization based on the timing of the tasks and the threads running the tasks; and rendering the thread visualization on a display.

Abstract: Example embodiments disclosed herein relate to an approach for installing a runtime agent during a security test. A security test is initiated or performed on an application under test executing on a server. An application vulnerability associated with the application under test is determined. The application vulnerability is exploited to install the runtime agent on the server. The security test is continued using the runtime agent to receive additional information about the application under test.

Abstract: Method and systems for analyzing event log elements are provided. In one example, a method includes receiving an event log element in a computer. A similarity index is calculated between the event log element and a text element. A threshold of similarity is calculated. The similarity index is compared to the threshold. If the similarity index is greater than the threshold, the event log element is grouped into a cluster with the text element to create a file of cluster assignments.

Abstract: In some examples, a system includes a color cluster learning engine and a color recognition engine. The color cluster learning engine may be configured to obtain a set of training images, process the training images to obtain clusters of pixel colors for the training images, identify learned color clusters from the clusters of pixel colors obtained from the training images, and label the learned color clusters with color indicators. The color recognition engine may be configured to receive an input image for color identification, process the input image to obtain a particular cluster of pixel colors that covers the highest number of pixels in the input image, match the particular cluster to a particular learned color cluster labeled with a particular color indicator, and identify a color of the input image as specified by the particular color indicator.

Abstract: The method may include periodically obtaining snapshots of the configuration of an environment. The method may also include logging the snapshots of the configuration of the environment in composite CI level. The method may further include causing display of configuration information relating to a first snapshot of the snapshots in composite CI level, while indicating configuration changes in that snapshot with respect to a second earlier snapshot of said snapshots.