SMART TEST CODE GENERATION
    1.
    发明公开

    公开(公告)号:US20240362154A1

    公开(公告)日:2024-10-31

    申请号:US18766625

    申请日:2024-07-08

    申请人: Nathan Shevick

    发明人: Nathan Shevick

    IPC分类号: G06F11/36

    CPC分类号: G06F11/3684 G06F11/3664

    摘要: A smart test generation system is described herein that removes much of the burden of creating boilerplate or routine code from the developer. The system intelligently generates as much code as possible so that the developer can focus on what he or she wants the test to do, rather than spending time setting up the test's framework. The unit test code generated by the smart test generation system is extremely detailed and complete compared to past solutions for test code generation. Thus, the smart test generation system quickly and easily sets developers up to write unit test code by freeing the developer from writing boring and repetitive test framework and setup code.

    Sandboxing Databases
    3.
    发明公开

    公开(公告)号:US20240354226A1

    公开(公告)日:2024-10-24

    申请号:US18305990

    申请日:2023-04-24

    申请人: MICRO FOCUS LLC

    IPC分类号: G06F11/36 G06F16/27

    CPC分类号: G06F11/3664 G06F16/27

    摘要: A sandbox database is created. The sandbox database is typically a temporary database. For example, the sandbox database may be a test database for evaluating a new version of software. Creating the sandbox database comprises creating a sandbox cache in the sandbox database and copying metadata from a main database to the sandbox database. The sandbox cache is used to store record(s) that are accessed during the use of the sandbox database. The metadata is used to reference the record(s). This allows for a simpler process for creating a temporary database to be used for testing software.

    SIMULATED SOFTWARE FEATURES IN A SIMULATED SANDBOX WITHIN A PRODUCTION ENVIRONMENT

    公开(公告)号:US20240338302A1

    公开(公告)日:2024-10-10

    申请号:US18329332

    申请日:2023-06-05

    申请人: Salesforce, Inc.

    IPC分类号: G06F11/36

    CPC分类号: G06F11/3664

    摘要: Implementations(s) for simulated software features are described. Responsive to a request for accessing a first web page, first code for the first web page is caused to be retrieved from a first web application. Responsive to the first code, the first web page is caused to be displayed with an access to a simulation of a feature that may be used in the first web application. Responsive to a user's selection of the access, the first web page is caused to be updated to include a first user interface (UI) component that identifies a second web page; responsive to the updated first web page, second code for the second web page is caused to be retrieved from a second web application; and responsive to the second code, the second web page is caused to be displayed inside the first UI component to allow for the simulation.

    Unique Signpost Strings for Automation Task Names to Directly Correlate Task Outputs to Specific Files and Originating Lines of Source Code

    公开(公告)号:US20240330147A1

    公开(公告)日:2024-10-03

    申请号:US18130053

    申请日:2023-04-03

    发明人: Charles Emery

    IPC分类号: G06F11/36

    CPC分类号: G06F11/3612 G06F11/3664

    摘要: Automation methods of utilizing signposts assigned to automation tasks in order to correlate automation output with lines of automation source code are disclosed. Automation job(s) are identified/detected (manually or automatically), and then processed. Tasks in the job are identified and unique identifiers (e.g., signposts in and to the source code) are assigned for each task and inserted into the source code. The unique identifiers may include task numbers, code directory identifiers, nested file identifiers, and/or standalone file identifiers, or a hexadecimal alias may be used as the identifier. Job task indicia can be stored in memory with the associated unique identifiers. If a job failure is detected during execution, a log identifying the signpost at which the fault occurred can be generated. This facilitates debugging and troubleshooting, because lines of automation output are correlated with lines of automation code.

    Debugging applications for delivery via an application delivery server

    公开(公告)号:US12106084B2

    公开(公告)日:2024-10-01

    申请号:US17840328

    申请日:2022-06-14

    申请人: Google LLC

    摘要: Analyzing or debugging applications is provided. The system identifies an action for an application provided by a developer. The system determines a first classification score based on historical execution of the action. The system generates a machine generated action for the application based on metadata associated with the application. The system determines a second classification score based on a comparison of the action with the machine generated action. The system selects, via a matching program, a second application that matches the application. The system determines a third classification score based on a comparison of an action approved for the second application with the action provided by the application developer. The system updates a delivery control parameter based on the first classification score, the second classification score and the third classification score. The system controls delivery of the application based on the delivery control parameter.

    Regression testing for web applications

    公开(公告)号:US12105619B2

    公开(公告)日:2024-10-01

    申请号:US18353529

    申请日:2023-07-17

    IPC分类号: G06F11/36 G06N5/022 G06N5/04

    摘要: Training a predict model with network traffic and data change messages generated by an existing web application running in a production environment. The predict model being is trained to predict data changes resulted from API calls embodied in network traffic. A stream of network traffic of the existing web application is replayed with an upgraded version of the existing web application to generate real data changes. The stream of network traffic is applied to the predict model to generate predicted data change messages. The predicted data change messages are comparing with real data change messages representing the real data changes. One or more existing APIs is identified as being possibly functionally degraded based on any inconsistency of the predicted data change messages with the real data change messages.