Patents by Inventor Yaron Burg
Yaron Burg has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11119899Abstract: Example implementations relate to determining potential test actions. Some implementations may include a data capture engine to capture data points during test executions of the application under test. The data points may include, for example, test action data and application action data. Additionally, some implementations may include a data correlation engine to correlate each of the data points with a particular test execution of the test executions, and each of the data points may be correlated based on a sequence of events that occurred during the particular test execution. Furthermore, some implementations may also include a test verification engine to determine, based on the correlation of the data points, a potential test action to perform during a future test execution of the application under test.Type: GrantFiled: May 28, 2015Date of Patent: September 14, 2021Assignee: MICRO FOCUS LLCInventors: Inbar Shani, Amichai Nitsan, Yaron Burg
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Patent number: 11016867Abstract: Example implementations relate to test execution comparisons. Some implementations may include a data capture engine to capture data points during test executions of the application under test. The data points may include, for example, test action data and application action data. Additionally, some implementations may include a data correlation engine to correlate each of the data points with a particular test execution of the test executions, and each of the data points may be correlated based on a sequence of events that occurred during the particular test execution. Furthermore, some implementations may also automatically compare the test executions, based on the correlated data points, to identify commonalities.Type: GrantFiled: December 18, 2015Date of Patent: May 25, 2021Assignee: Micro Focus LLCInventors: Inbar Shani, Amichai Nitsan, Yaron Burg
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Patent number: 10528456Abstract: Example implementations relate to determining idle testing periods. Some implementations may include a data capture engine to capture data points during test executions of the application under test. The data points may include, for example, test action data and application action data. Additionally, some implementations may include a data correlation engine to correlate each of the data points with a particular test execution of the test executions, and each of the data points may be correlated based on a sequence of events that occurred during the particular test execution. Furthermore, some implementations may also include an idle testing period determination engine to determine, based on the correlation of the data points, idle testing periods of the test executions. The idle testing periods may be periods of time where both the test executions and the application under test are idle.Type: GrantFiled: May 4, 2015Date of Patent: January 7, 2020Assignee: Micro Focus LLCInventors: Inbar Shani, Amichai Nitsan, Yaron Burg
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Patent number: 10509719Abstract: Example implementations relate to automatically identifying regressions. Some implementations may include a data capture engine to capture data points during test executions of the application under test. The data points may include, for example, test action data and application action data. Additionally, some implementations may include a data correlation engine to correlate each of the data points with a particular test execution of the test executions, and each of the data points may be correlated based on a sequence of events that occurred during the particular test execution. Furthermore, some implementations may also include a regression identification engine to automatically identify, based on the correlated data points, a regression between a first version of the application under test and a second version of the application under test.Type: GrantFiled: September 8, 2015Date of Patent: December 17, 2019Assignee: MICRO FOCUS LLCInventors: Inbar Shani, Ayal Cohen, Yaron Burg
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Patent number: 10474887Abstract: First object model data from a first application state generated in a first browser mode may be collected. The first object model data may comprise a code-based representation of a first layout element and a second layout element of the first application state. According to a layout detection rule, a first attribute of the first layout element may be compared with a second attribute of the first layout element or of a second layout element. A layout error corresponding to the first layout element may be identified based on the comparison of the first attribute with the second attribute.Type: GrantFiled: January 10, 2017Date of Patent: November 12, 2019Assignee: MICRO FOCUS LLCInventors: Amit Levin, Yaron Burg, Ilan Shufer, Olga Kogan
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Patent number: 10365995Abstract: Example implementations relate to composing future tests. Some implementations may include a data capture engine to capture data points during test executions of the application under test. The data points may include, for example, test action data and application action data. Additionally, some implementations may include a data correlation engine to correlate each of the data points with a particular test execution of the test executions, and each of the data points may be correlated based on a sequence of events that occurred during the particular test execution. Furthermore, some implementations may also include a test composition engine to compose, based on an interaction with a visualization of results of a verification query of the correlated data points, a future test of the application under test.Type: GrantFiled: August 4, 2015Date of Patent: July 30, 2019Assignee: ENTIT SOFTWARE LLCInventors: Inbar Shani, Amichai Nitsan, Yaron Burg
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Patent number: 10318122Abstract: Examples disclosed herein relate to determining event and input coverage metrics for a graphical user interface (GUI) control instance. Examples include accessing event and input occurrence data identifying interactions performed on a GUI of an application, determining an event coverage metric for the given GUI control instance based on the event occurrence data, and determining an input coverage metric for the given GUI control instance based on the input occurrence data.Type: GrantFiled: February 27, 2013Date of Patent: June 11, 2019Assignee: ENTIT SOFTWARE LLCInventors: Alexei Ledenev, Ilan Shufer, Yaron Burg
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Patent number: 10175958Abstract: 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.Type: GrantFiled: January 30, 2013Date of Patent: January 8, 2019Assignee: ENTIT SOFTWARE LLCInventors: Inbar Shani, Yaron Burg, Amichai Nitsan
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Publication number: 20180365123Abstract: Example implementations relate to test execution comparisons. Some implementations may include a data capture engine to capture data points during test executions of the application under test. The data points may include, for example, test action data and application action data. Additionally, some implementations may include a data correlation engine to correlate each of the data points with a particular test execution of the test executions, and each of the data points may be correlated based on a sequence of events that occurred during the particular test execution. Furthermore, some implementations may also automatically compare the test executions, based on the correlated data points, to identify commonalities.Type: ApplicationFiled: December 18, 2015Publication date: December 20, 2018Inventors: Inbar Shani, Amichai Nitsan, Yaron Burg
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Patent number: 10102105Abstract: In one example of the disclosure, code lines for a software program are received, the code lines including a unit of code lines. Code entities within the unit are identified. Each code entity includes a line or consecutive lines of code implementing a distinct program requirement or defect fix for the program. Context changes are identified within the unit, each context change including an occurrence of a first code line set implementing an entity, adjacent to a second code line set implementing another entity, within a same code scope. A code complexity score is determined based upon counts of entities identified and context changes identified within the unit, and upon counts of code lines and entities within the program.Type: GrantFiled: June 24, 2014Date of Patent: October 16, 2018Assignee: ENTIT SOFTWARE LLCInventors: Inbar Shani, Ohad Assulin, Yaron Burg
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Publication number: 20180267888Abstract: Example implementations relate to automatically identifying regressions. Some implementations may include a data capture engine to capture data points during test executions of the application under test. The data points may include, for example, test action data and application action data. Additionally, some implementations may include a data correlation engine to correlate each of the data points with a particular test execution of the test executions, and each of the data points may be correlated based on a sequence of events that occurred during the particular test execution. Furthermore, some implementations may also include a regression identification engine to automatically identify, based on the correlated data points, a regression between a first version of the application under test and a second version of the application under test.Type: ApplicationFiled: September 8, 2015Publication date: September 20, 2018Inventors: Inbar Shani, Ayal Cohen, Yaron Burg
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Publication number: 20180232299Abstract: Example implementations relate to composing future tests. Some implementations may include a data capture engine to capture data points during test executions of the application under test. The data points may include, for example, test action data and application action data. Additionally, some implementations may include a data correlation engine to correlate each of the data points with a particular test execution of the test executions, and each of the data points may be correlated based on a sequence of events that occurred during the particular test execution. Furthermore, some implementations may also include a test composition engine to compose, based on an interaction with a visualization of results of a verification query of the correlated data points, a future test of the application under test.Type: ApplicationFiled: August 4, 2015Publication date: August 16, 2018Inventors: Inbar Shani, Amichai Nitsan, Yaron Burg
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Publication number: 20180196785Abstract: First object model data from a first application state generated in a first browser mode may be collected. The first object model data may comprise a code-based representation of a first layout element and a second layout element of the first application state. According to a layout detection rule, a first attribute of the first layout element may be compared with a second attribute of the first layout element or of a second layout element. A layout error corresponding to the first layout element may be identified based on the comparison of the first attribute with the second attribute.Type: ApplicationFiled: January 10, 2017Publication date: July 12, 2018Inventors: Amit Levin, Yaron Burg, Ilan Shufer, Olga Kogan
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Publication number: 20180143897Abstract: Example implementations relate to determining idle testing periods. Some implementations may include a data capture engine to capture data points during test executions of the application under test. The data points may include, for example, test action data and application action data. Additionally, some implementations may include a data correlation engine to correlate each of the data points with a particular test execution of the test executions, and each of the data points may be correlated based on a sequence of events that occurred during the particular test execution. Furthermore, some implementations may also include an idle testing period determination engine to determine, based on the correlation of the data points, idle testing periods of the test executions. The idle testing periods may be periods of time where both the test executions and the application under test are idle.Type: ApplicationFiled: May 4, 2015Publication date: May 24, 2018Applicant: ENTIT Software LLCInventors: Inbar Shani, Amichai Nitsan, Yaron Burg
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Publication number: 20180137036Abstract: Example implementations relate to determining potential test actions. Some implementations may include a data capture engine to capture data points during test executions of the application under test. The data points may include, for example, test action data and application action data. Additionally, some implementations may include a data correlation engine to correlate each of the data points with a particular test execution of the test executions, and each of the data points may be correlated based on a sequence of events that occurred during the particular test execution. Furthermore, some implementations may also include a test verification engine to determine, based on the correlation of the data points, a potential test action to perform during a future test execution of the application under test.Type: ApplicationFiled: May 28, 2015Publication date: May 17, 2018Inventors: Inbar Shani, Amichai Nitsan, Yaron BURG
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Publication number: 20170031800Abstract: In one example of the disclosure, code lines for a software program are received, the code lines including a unit of code lines. Code entities within the unit are identified. Each code entity includes a line or consecutive lines of code implementing a distinct program requirement or defect fix for the program. Context changes are identified within the unit, each context change including an occurrence of a first code line set implementing an entity, adjacent to a second code line set implementing another entity, within a same code scope. A code complexity score is determined based upon counts of entities identified and context changes identified within the unit, and upon counts of code lines and entities within the program.Type: ApplicationFiled: June 24, 2014Publication date: February 2, 2017Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LPInventors: Inbar Shani, Ohad Assulin, Yaron Burg
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Publication number: 20160132427Abstract: Verifying user interface conformance can include deriving a conformance rule set based on desired user interface characteristics identified through an examination of mockup data for the user interface. That mockup data includes a visual representation of the desired characteristics. Conformance data can then be generated based on differences between the desired characteristics and actual characteristics. Those differences are identified by processing the conformance rule set against screen capture data of the user interface as produced by an application under test. The screen capture data includes a visual representation of the actual characteristics of the user interface.Type: ApplicationFiled: June 27, 2013Publication date: May 12, 2016Inventors: Inbar Shani, Yaron Burg, Amichai Nitsan
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Publication number: 20150355888Abstract: 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.Type: ApplicationFiled: January 30, 2013Publication date: December 10, 2015Inventors: Inbar Shani, Yaron Burg, Amichai Nitsan
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Publication number: 20150339019Abstract: Examples disclosed herein relate to determining event and input coverage metrics for a graphical user interface (GUI) control instance. Examples include accessing event and input occurrence data identifying interactions performed on a GUI of an application, determining an event coverage metric for the given GUI control instance based on the event occurrence data, and determining an input coverage metric for the given GUI control instance based on the input occurrence data.Type: ApplicationFiled: February 27, 2013Publication date: November 26, 2015Inventors: Alexei Ledenev, Ilan Shufer, Yaron Burg
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Patent number: 8555253Abstract: A system and method for monitoring exploratory testing by a plurality of testers of software containing a graphical user interface is disclosed. The method includes recording interactions of each of the plurality of testers with a graphical user interface (GUI) under test. The recorded interactions of each tester can be stored in an interaction database. An interaction footprint map is created from the interaction database to show which portions of the GUI under test have had interaction with at least one of the testers. The interaction footprint map is displayed in relation to the GUI for at least one end user.Type: GrantFiled: November 2, 2009Date of Patent: October 8, 2013Assignee: Hewlett-Packard Development Company, L.P.Inventors: Ilan Shufer, Alexei Ledenev, Yaron Burg