Micro Focus Lcc

Er-Xin Shang

Hua-Ming Zhai

Bin Zhou

Shuhui Fu

Yun-Sheng Liu

Peng-Ji Yin

Tezeen Yu

Yun Yuan

Hao-Bin Cui

Wen-Jie Qian

Kai Zhou

Bin Li

Fei Gao

Ran Li

Qian-Ru Zhai

Bo Tian

Amos Nesher

Gil Nakache

Anton Kaminsky

Yan-Jun Yu

Eyal Luzon

Yi-Bin Guo

Tsachi Ben Zur

Haiyu Gao

Chao-Lin Jiang

Bin Gao

Chao Lin Jiang

Chu Jun Dong

An apparatus may include a processor () that may generate automated test scripts to test graphical user interface (GUI) functions of an application under test (AUT) (). The apparatus may generate a screen element () that is overlaid onto at least one or all of the GUIs (). The screen element () may therefore receive user inputs directed at the GUI (), but block such inputs from being provided to the GUI (). The user inputs received at the screen element () may be recorded in an automated test script for later replay. Blocking the user input may prevent a change in appearance of a GUI element () that would otherwise result from the user input, facilitating automated location of the GUI element () during replay of the automated test script.

Recording test usage of a graphical user interface with blocked inputs

According to examples, an apparatus may include a processor that may internationalize an automated test script that was generated to test a Graphical User Interface (GUI) in the first human language. When the GUI is internationalized into a second human language, the automated test script may no longer function. As such, the system may employ computer vision techniques to analyze the GUI in the first human language and the GUI in the second human language to identify text and GUI elements that correlate with one another. Based on the correlation, the system may internationalize the automated test script to function on the GUI in the second human language.

Internationalization of automated test scripts

According to examples, an apparatus may include a processor that may identify sensitive information in a recording of an automated test script that is replayed to automatically test a graphical user interface (GUI) of an application under test (AUT). The apparatus may identify the sensitive information during the recording such that sensitive information is identified as the automated test is recorded or afterward based on an analysis of the recording. as based on user input that identifies the sensitive information (or areas containing the sensitive information), automated text analysis, or automated image analysis such as machine-learning based object detection. Once sensitive information (or area) is identified, the apparatus may generate and apply a mosaic to obscure the sensitive information (or area).

Automated test replay with sensitive information obfuscation

In some examples, a system represents tasks of a project as feature nodes of a force-directed graph, and connects, in the force-directed graph, sub-feature nodes representing sub-features associated by links to the feature nodes in the force-directed graph. The system sets a size of each respective sub-feature node of the sub-feature nodes based on an amount of resource usage expended on a respective sub-feature represented by the respective sub-feature node. The system causes display of the force-directed graph, and collapses or expands a portion of the force-directed graph responsive to user interaction with the force-directed graph.

Project visualizations

An image of a graphical user interface is captured. A process is started to record identification of a graphical object (e.g., a text field) in the image of the graphical user interface. Recording identification of the graphical object in the image of the graphical user interface is based on machine learning. An end to the process to record identification of the graphical object in the image of the graphical user interface is identified. A machine learned software object is updated. For example, the machine learned software object is updated with a location of the graphical object. The updated machine learned software object then is used to test the graphical object. For example, to automatically fill in the text field using a test script.

Machine learning based on functional testing

Method and system to automatically verify the layout of a webpage on various screen sizes. The method includes retrieving screen size data associated with the webpage. The method further includes determining anchor points for the webpage based on the retrieved screen size data. The method also includes rendering the plurality of elements of the webpage based on the retrieved screen size data and the determined anchor points and identifying a respective location of each of the plurality of elements of the webpage to verify the layout of the plurality of elements of the webpage. If an error in the layout of the webpage is detected, a visual and/or audio alert is sent.

Method and system for automatic test website layout

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.

Test script generation based on event data and video frames

According to examples, an apparatus may include a processor and a memory on which are stored machine-readable instructions that when executed by the processor, may cause the processor to track traffic events and user interface (UI) events in parallel and record a first event of a hybrid test script. The first event may be recorded in a traffic mode to record one or more of the traffic events. The processor may transition from the traffic mode to a UI mode and, responsive to the transition from the traffic mode to the UI mode, may share session data between the traffic events and the UI events. Based on the session data, the processor may record a second event of the hybrid test script in the UI mode.

Hybrid test scripts for transitioning between traffic events and user interface events

Embodiments provide for automated testing of an Application Under Test (AUT) that utilizes an infinite scroll element. Automated testing of the AUT can comprise executing one or more test scripts on the AUT which can present a user interface including a plurality of elements and the test scripts can perform one or more functional tests on the AUT through the plurality of elements of the user interface. During performance of the one or more functional tests, a scroll event associated with an element of the user interface can be detected and a determination can be made as to whether the element associated with the scroll event is an infinite scroll element. In response to determining the element is an infinite scroll element, a set of test results for the functional test can be recorded including results for the infinite scroll element and an interaction with the infinite scroll element.

Supporting record and replay for infinite scroll elements

An image of a graphical user interface is captured. For example, a screen shot of a browser display is captured. Text syntax is executed that contains one or more parameters for identifying a graphical object. For example, the text syntax may identify a rectangle that contains the text 'OK' where the text is red. Based on the text syntax, a graphical object is identified in the image of the graphical user interface. Information is returned that identifies how to access the graphical object in the graphical user interface. For example, coordinates of the graphical object are identified. This information can then be used in a test script using existing programming languages to test the graphical user interface. For example, the coordinates may be used to click on the OK button.

Using graphical image analysis for identifying image objects

Embodiments of the disclosure provide systems and methods for executing a functional test on an application. According to one embodiment, a method for running a functional test on an application can comprise executing the function test on the application. The functional test can comprise a plurality of steps. The plurality of steps can comprise a set of related steps having one or more relationships between each other and a set of one or more independent steps having no relationships to other steps in the plurality of steps. The one or more relationships between the set of related steps can be deduced and an indication of the deduced one or more relationships between the set of related steps can be saved. The functional test can then be replayed on the application based on the saved indication of the deduced one or more relationships between the set of related steps.

Methods and systems to automatically deduce relationships among test steps

An image of a user interface of a device is captured. A graphical object is identified in the image of the user interface. For example, a menu item or a text object is identified in the image of the user interface. An Artificial Intelligence (AI) process is used to determine a confidence score for the graphical object; the confidence score identifies a confidence of how likely a type of the graphical object can be identified. In response to the first confidence score not meeting a threshold, a zoomed in image of the graphical object is taken or a zoomed-out image of the graphical object is taken. The zoomed in image or the zoomed-out image is used to increase the confidence score to better identify the type of the graphical object.

Automatic zoom on device screen to improve artificial intelligence identification rate

In some examples, a system executes a program that generates a user interface (UI) screen, provides a user input event to the program during execution, and captures images of the UI screen before and after the user input event. The system determines, based on the captured images, whether a first region of the UI screen changed in response to the user input event, and indicates the first region as a user interactive region and adds an element representing the user interactive region to a representation of user interactive regions of a UI of the program.

Representation of user interface interactive regions

This document describes techniques and apparatuses for supporting web components associated with a document object model (DOM) corresponding to a data file in a web testing environment. A user interaction, relative to a web page or web application from which the DOM is rendered, is monitored in the web testing environment. The monitoring identifies a target element selected by the user that is referenced in a shadow DOM associated with the DOM. One or more parent shadow host elements of the DOM are identified relative to the target element. The one or more shadow host elements define a reduced path, with respect to a tree data structure representing the DOM and the shadow DOM, for linking a document object of the DOM to the target element. Indicia identifying the one or more shadow host elements as linking the document object of the DOM to the target element are recorded. The recorded indicia define the reduced path for identifying the target element relative to the document object in the tree data structure during a replay of a recorded session of the user interaction. A target element may also be identified and replaced with a different object by referencing the one or more shadow host elements.

Supporting web components in a web testing environment

A graphical user interface (GUI) of an application under test (AUT) is rendered. A GUI test object of the AUT is identified within the GUI. Test information regarding the GUI test object of the AUT is retrieved. The GUI test object of the AUT is rendered within the GUI to reflect the test information.

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Shanghai, China

Er-Xin Shang