Abstract: Example embodiments disclosed herein relate to determination of vulnerability of an application under test using a runtime agent and network sniffer during a security test. A runtime agent monitors execution of an application under test. A network sniffer is used to identify a probe value for determination of the vulnerability.

Abstract: In some examples, a method includes receiving a data packet through a datapath configured by a data source. The datapath may specify a data dimension of data communicated through the data packet. The method may also include identifying, from the data packet, a particular dimension value for the data dimension specified in the datapath and dispatching the data of the data packet to a virtual data channel specific to the particular dimension value to support presentation of the data through a dashboard.

Abstract: Examples disclosed herein relate to acquiring identification of an application lifecycle management (ALM) entity associated with similar code. Examples include identifying a target code segment, and acquiring, from an ALM system, identification of an ALM entity associated with other code similar to the target code segment and identified by a code similarity system.

Abstract: Problem isolation in a virtual environment is described. In one example, a method (300) is provided for isolating problems in a virtual environment. The method includes maintaining (310) a topology of network devices in the virtual environment. The virtual environment can be monitored (320) using a performance module for network device operation irregularities exceeding a threshold. A network device operation irregularity can be identified (330) as well as a portion of the topology associated with the network device operation irregularity. Topology portions associated with network device operation irregularities can be grouped (340) together using a snapshot module to form a snapshot of a problem topology.

Abstract: An apparatus (100) in an example comprises a test-script generator (704) and selection logic (114). The test-script generator (704) serves to create a test script (116) through identification of currently-available elements (604, 606, 608, 610, 612, 614, 616, 618) of an application (106) under test. The test script (116) is employable to exercise the application (106). The selection logic (114) serves to identify elements (406, 408) of a currently-executing component script (402) within the test script (116), contemporaneous with execution of the test script (116), that may be affected by graphical user interface changes made to the application (106). The identification of the elements (406, 408) of the currently-executing component script within the test script (116), contemporaneous with execution of the test script (116), that may be affected by the graphical user interface changes by the selection logic is contemporaneous with the exercise of the application (106) by the test script (116).

Abstract: An example lexical analysis system may include lexical analyzer instructions and training instructions. The lexical analyzer instructions, when executed, may form a universal lexical analyzer that is to lexically analyze an input program by evaluating a function that maps an input tuple of lexemes to an output tuple of tokens based on input probability parameters. The universal lexical analyzer may be configurable for any programming language by inputting a set of probability parameters for the respective programming language as the input probability parameters of the function.

Abstract: A method includes identifying a buddy database projection that corresponds to a recovering database projection that is to be recovered to a recovering node of a database system. A source container containing data of the buddy database projection is identified on a source node of the database system, the source container being characterized by a range of epochs that includes an epoch for which data is to be recovered to the recovering node. Data is copied from the identified source container to the recovering node.

Abstract: An example device in accordance with an aspect of the present disclosure includes an identification engine, a clustering engine, and a weighting engine. The identification engine is to identify User Interface (UI) elements of an application under test based on an image processing analysis of screens of the application under test. The clustering engine is to cluster the UI elements into at least one cluster based on at least one feature of the UI elements. The weighting engine is to assign score weights to the UI elements of a given screen according to which of the at least one cluster that a given one of the UI elements is clustered in.

Abstract: Techniques for identifying a build commit that caused a test failure are provided. A build which includes a failed test may be identified. For each commit in the build a weighting factor may be calculated for files that have been previously associated with the failed test. The weighting factor may be based on the number of times the file has been associated with the failed test and the total number of tests. A weighting factor may also be calculated for files that have not been previously associated with the failed test based on the number of times the file appears with other files that are associated with the failed test. The weighting factors may be added to create a score for the commit. The scores for the commits in the build may be ordered. The higher the score, the more likely the commit was the cause of the failed test.

Abstract: Simulating sensors can include hooking an application associated with sensory data and associating the sensory data with an automation instruction. Simulating sensors can include providing the sensory data to a support device having an ability to modify the application and automatically causing the support device to simulate a sensory input using the sensory data by executing the automation instruction.

Abstract: According to examples, an apparatus may include a processor and a non-transitory computer readable medium storing instructions that cause the processor to classify files stored on a source storage into files for deletion and files for migration based on a storage policy and meta-data, generate aliases to link the files classified for migration to a location on a target storage, copy the files classified for migration from the source storage to the linked location on the target storage, and determine whether the files copied onto the target storage are identical to the files classified for migration on the source storage using a digital key. In response to a determination that the copied files are identical to the files classified for migration, the processor may activate the generated aliases and may decommission the source storage.

Abstract: Examples disclosed herein provide tools for capturing spatial gestures performed by a user and scripting the gestures for testing an application under test. Scripts may be produced by capturing movement of extremities of a skeletal body corresponding to the user, wherein the movement is captured according to a change in coordinates of the extremities from an original position. The movement of the extremities may be matched to a predefined gesture found in a gesture database. A script may be generated from the matched predefined gesture with reference to the extremities captured and coordinates of the extremities from the original position, such that the user is emulated.

Abstract: Dependency monitoring can include monitoring a first application and a second application for un-expected behavior. Dependency monitoring can also include receiving a description of a number of dependencies between a number of applications wherein the description of the number of dependencies is created before monitoring of the first application and the second application begins. Dependency monitoring can include sending a message to an information technology (IT) personnel, wherein the message identifies a dependency from the number of dependencies between the first application and the second application based on the description of the number of dependencies.

Abstract: A realized topology system management (RTSM) database, comprising a database, a number of stored realized topologies, and in which the realized topologies within the DBMS are searchable. A method of generating and tracking a realized topology, comprising deriving a realized topology from an instantiated topology, storing the realized topology in a realized topology system management (RTSM) database, and storing a data file representing an association of the realized topology with data describing attributes of a number of nodes on the realized topology and relationships between the nodes.

Abstract: Examples relate to calculating normalize metrics. The examples disclosed herein calculate respective normalized first metric values for each of a plurality of first metric values that are on a time scale and respective normalized second metric values for each of the plurality of raw second metric values that are on the time scale, where the plurality of first metric values are associated with a first metric, and the plurality of second metric values are associated with a second metric. An extremum of the normalized first metric value and the normalized second metric value at each time of the time scale is averaged to calculate a plurality of extremum baseline values. Examples herein calculate a plurality of sleeve values of the plurality of extremum baseline values based on a standard deviation of the plurality of extremum baseline values.

Abstract: Packets from a first network entity to a second network entity are received. A maximal size of packets from the second network entity to the first network entity is determined based on information in the received packets.

Abstract: Comparing user interfaces (UIs) can refer to comparing information pertaining to a portion of a UI associated with an event with information pertaining to one of a plurality of previous version of the UI and/or identifying, based on the comparison, a revision to the one of the previous version of the UI that caused the event.

Abstract: Example embodiments disclosed herein relate to analyzing a web application. A web application is loaded. User actions are simulated on user interface elements of the web application. A structure of the web application is traversed based on rules to determine a set of actionable tokens. The respective actionable tokens include a portion of the web application that can change a user interface presented based on the web application.

Abstract: Methods, systems, and computer-readable media with executable instructions stored thereon for identifying a user that accesses a webpage from a user device through a proxy are provided. Identifying users through a proxy can include providing rewritten content of the webpage accessed by the user to the user device, the rewritten content including a reference to a data file, and the reference including a checksum computed from actual content of the webpage. The user can be associated with the actual content of the webpage in response to receiving a file request for the data file from the user device.

Abstract: Example embodiments relate to generalized snapshots based on multiple partial snapshots. An example method may include accessing multiple partial snapshots, each from a different client. The method may include creating a generalized snapshot from the multiple partial snapshots. The generalized snapshot includes multiple target pixels, and the color of each of the multiple target pixels may be determined by considering colors of multiple source pixels, each from a different partial snapshot.