According to the present disclosure various network functions are dynamically instantiated on a selected data center to utilize the most efficient and rapid resources available. An analytic module and a data lake receive performance data from the various data centers of a cellular network, such as a Regional Data Center, a National Data Center and an Edge Data Center. The analytic module will analyze the received performance data and apply artificial intelligence and machine learning to determine current resource use and estimate future resources available on various data centers of the cellular network. The appropriate data center is then selected to perform a particular network function.

A relay and metering test instrument includes an application processor circuitry to control functional operation of the relay and metering test instrument. The application processor circuitry may receive a user selected source code state program, and operational parameters input by the user. The application processor circuitry may compile the source code state program and the operational parameters into a test routine for storage in a memory circuitry with other test routines. The relay and metering instrument may also include a real time processor circuitry and an input/output processor circuitry. The real time processor circuitry may selectively and independently execute the test routine or one of the other test routines to perform one or more respective testing stages. The input/output processor circuitry may cooperatively operate with the real time processor circuitry to output test signals and monitor for receipt of input test signals according to execution of the test routine.

Techniques are disclosed for setting a breakpoint for debugging a neural network. User input is received by a debugger program executable by a host processor indicating a target layer of a neural network at which to halt execution of the neural network. The neural network includes a first set of instructions to be executed by a first execution engine and a second set of instructions to be executed by a second execution engine. A first halt point is set within the first set of instructions and a second halt point is set within the second set of instructions. It is then determined that operation of the first execution engine and the second execution engine has halted. It is then determined that the first execution engine has reached the first halt point. The second execution engine is then caused to move through instructions until reaching the second halt point.

A real-time debugger implementation maintains and manages multiple debug contexts allowing developers to interact with real-time applications without breaking the system in which the debug application is executing. The debugger allows multiple debug contexts to exist and allows break points in real-time and non-real-time code portions of one or more applications executing on a debug enabled core of a processor. A debug monitor function may be implemented as a hardware logic module on the same integrated circuit as the processor. Higher priority interrupt service requests may be serviced while otherwise maintaining a context for the debug session (e.g., stopped at a developer defined breakpoint). Accordingly, the application developer executing the debugger may not have to be concerned with processing occurring on the processor that may be unrelated to the current debug session.

A method and device for automating analysis of executed performance testing is disclosed. The device includes a processor, and a communications module and memory coupled to the processor. The memory stores computer executable instructions that when executed by the processor cause the processor to receive an input associated with executing a performance test of an application. The processor identifies a test analysis template from a plurality of test analysis templates based on the performance test or the application, each test analysis template defining analysis parameters for interpreting results of executed performance tests. The processor creates a session for analyzing a result of the performance test being executed. Within the analysis session, one or more models are applied to the result, where the one or more models are responsive to the analysis parameters. The processor generates a performance analysis report based on the applied one or more models.

A method for testing a user interface (UI) includes obtaining a first state of the UI and setting a current position to specified location coordinates. The method includes determining whether the first state satisfies criteria for a goal and, if so, updating a collection of completed tests with a test distance and test data. The method includes, in response to the first state not satisfying the criteria: determining a set of potential user actions to be performed in the first state based on interactive elements of the UI; selecting and executing an action; and updating the test distance based on the current position and location coordinates of the element associated with the action. The method includes determining a shortest path to the goal in the UI based on the collection of completed tests. The method includes, based on the determined shortest path, automatically visually transforming a state of the UI.

The application testing system and method provide an efficient and effective way to test multiple application variants of an application on at least one mobile device. The application testing system may cause a first application variant selection indication to be transmitted to at least one mobile device having the application. The first application variant selection indication may be configured to cause the mobile device to interact with the application according to a first application variant of the plurality of application variants. The application testing system may analyze data corresponding to the usage of the first application variant by the at least one mobile device, and cause a second application variant selection indication to be transmitted to the mobile device, wherein the second application variant selection indication is configured to cause the mobile device to interact with the application according to a second application variant of the plurality of application variants.

Computer systems and methods perform a chaos experiment for a target application. The computer system: (i) generates, for the chaos experiment, a simulated traffic stream for a non-production version of the target application; (iii) provides chaos event settings for one or more chaos conditions to the non-production version of the target application; (iv) executes the non-production version of the target application during the chaos experiment, such that the non-production version of the target application, during the chaos experiment, (a) generates responses to the simulated traffic stream while simultaneously (b) being subject to the one or more chaos conditions of the chaos event settings; and (iv) monitors the responses generated by the non-production version of the target application during the chaos testing.

An embodiment identifies a fileset used by an executing application. An embodiment generates, at a first time, a first snapshot of the fileset, the first snapshot comprising a first state of the fileset at the first time and a first indicator corresponding to the first state of the fileset. An embodiment selects, at a recovery time later than the first time, from a sequence of snapshots of the fileset including the first snapshot, a recovery snapshot, the recovery snapshot comprising a recovery indicator, wherein the recovery indicator has a difference from the first indicator that is higher than a threshold value. An embodiment restores, using the recovery snapshot, the fileset to a state other than the first state, the restoring resulting in a restored application.

In one embodiment, a device identifies an application programming interface call within new code for an application. The device conducts testing of a plurality of endpoints associated with the application programming interface call. The device selects, based on results of the testing, a particular endpoint from among the plurality of endpoints. The device steers the application programming interface call made by the application towards the particular endpoint.