An automated testing framework and associated tools for executable applications such as games focus on integration testing, wherein users create data-driven tests by using test modules and configuration data as building blocks. The tools facilitate cooperation between coders and non-technical Quality Assurance (QA) staff in creating automated tests, by simplifying the user interface for configuring tests. Components of the tools simulate user interactions with the application under test, for example, gamepad button presses. The tools are also capable skipping portions of gameplay or other interactive activity and directly jumping into a desired game mode during automated testing, and other functions.

In some examples, a system processes event data and video frames produced by a program during execution of the program, the event data representing user actions with respect to a graphical user interface (GUI) of the program. The system identifies an area of the GUI that corresponds to a respective user action of the user actions, wherein identifying the area of the GUI uses a first video frame before an event corresponding to the respective user action, and a second video frame after the event corresponding to the respective user action. The system identifies, based on the identified area, a test object representing a user interface (UI) element, and generates a test script for testing the program, the test script including the test object.

Systems and methods for sourcing participants for a usability study are provided. In some embodiments the systems and methods receive study parameters including the type of study, time-to-field of the study, required number of participants, and required participant attributes. Additionally, a set of business rules for the study are received. These business rules may be received from a client, extrapolated from a service contract with a client for which the study is being performed, or generated based on the monitored outcomes of sourcing of previous studies. Next, panel sources for potential participants and pricing data are queried, and a set of the sources are selected based upon the pricing data. Participants are then received from these sources, which are then fielded in the study and monitored for outcomes.

Provided herein are systems and methods for creating, testing and providing digital guidance for use in an underlying computer application. In one exemplary implementation, a method includes using a browser extension to record steps of digital guidance content as the steps are created by a content author, automatically testing the content with the same browser and making the tested content available for playback. The testing may include receiving an execute testing command, fetching test case data from a server, executing a test case in the browser using the test case data, running tests on the test case in a background tab of the browser, recording passes and or failures of the tests, sending reports of the passes and failures to the server, sending a notification to the content author that the testing results are ready to view, and displaying the testing results in the dashboard.

Methods for generating data models using a generative adversarial network can begin by receiving a data model generation request by a model optimizer from an interface. The model optimizer can provision computing resources with a data model. As a further step, a synthetic dataset for training the data model can be generated using a generative network of a generative adversarial network, the generative network trained to generate output data differing at least a predetermined amount from a reference dataset according to a similarity metric. The computing resources can train the data model using the synthetic dataset. The model optimizer can evaluate performance criteria of the data model and, based on the evaluation of the performance criteria of the data model, store the data model and metadata of the data model in a model storage. The data model can then be used to process production data.

Provided is a system and method for dynamically adjusting a descriptive document with instructions for a user interface based on configuration settings and software version and/or release for a particular user and document data stored in a technical data object. The process ensures that the content of the descriptive document matches what a user will see on a screen when viewing the user interface. In one example, the method may include retrieving user interface configuration settings generating a simulated user interface that includes a plurality of user interface elements and formatting the user interface elements based on the user interface configuration settings, composing a window with text from a document and screenshot images of one or more formatted user interface elements from the simulated user interface corresponding to the text, and rendering the window via a display of a computing device.

Examples described herein include systems and methods for fuzz testing low-level virtual devices and virtual devices with DMA write functionality. A fuzz tester includes components distributed across a virtual machine and its host system. The fuzz testing components in the virtual machine are implemented as firmware installed in the virtual machine's ROM. These components operate independent of data stored in the virtual machine's RAM and do not require an operating system to be installed on the virtual machine. As a result, any changes made to the virtual machine's RAM during the fuzzing process by low-level virtual devices or virtual devices with DMA write functionality cannot interrupt the fuzz testing or otherwise negatively impact the fuzz tester itself.

A testing system and method for testing application code against various failure scenarios. The testing system and method generate a test workflow including test source code implementing a series of actions that affect an application component and or an infrastructure component included in application code. The testing system and method execute the test workflow to determine the performance of the application code during one or more failure scenarios caused by the series of actions included in the test workflow. Performance data generated by the test code is analyzed by a performance analysis service or method to identify limitations of the application code and build resiliency patterns that address the limitations and improve the performance of the application code.

A device is further configured to determine a location within a spatial domain for a first program. The device is further configured to determine a first distance threshold value that corresponds with a first distance away from the location of the first program within the spatial domain. The device is further configured to determine distances between the location of the first program and locations of other programs from the plurality of programs and to identify one or more programs from the plurality of programs that are less than the first distance threshold value. The device is further configured to identify the one or more programs from the plurality of programs that are less than the first distance threshold value.

A method and apparatus for performing a user interface test by a middleware server including determining a state change of a portion of the user interface, receiving a test command indicative of a user interface functional test from a test interface, determining an auxiliary test associated with the test command, generating an altered test command requesting performance of the user interface functional test and the auxiliary test, transmitting the altered test command to the user interface, receiving a functional result from the user interface in response to the altered test command, generating an altered test result indicative of the functional result, and transmitting the altered test result to the test interface.