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Patent Agency Ranking
公开(公告)号：US20180196785A1
公开(公告)日：2018-07-12
申请号：US15402992
申请日：2017-01-10
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor： Amit Levin , Yaron Burg , Ilan Shufer , Olga Kogan
CPC classification number: G06K9/00449 , G06F17/2725 , G06K9/00463 , G06K2209/01
Abstract: 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.
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公开(公告)号：US20170031800A1
公开(公告)日：2017-02-02
申请号：US15302759
申请日：2014-06-24
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor： Inbar Shani , Ohad Assulin , Yaron Burg
CPC classification number: G06F11/3608 , G06F8/77 , G06F11/34 , G06F11/3604 , G06F11/3616
Abstract: 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.
Abstract translation: 在本公开的一个示例中，接收用于软件程序的代码行，代码行包括代码行的单位。 识别单位内的代码实体。 每个代码实体包括实现程序的不同程序要求或缺陷修补程序的行或连续代码行。 在单元内识别上下文改变，每个上下文改变包括在相同的代码范围内实现实现与实现另一个实体的第二代码行集相邻的实体的第一代码行集合的出现。 代码复杂性分数是根据识别的实体的计数和在单元内识别的上下文变化以及程序中代码行和实体的计数来确定的。
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公开(公告)号：US10474887B2
公开(公告)日：2019-11-12
申请号：US15402992
申请日：2017-01-10
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor： Amit Levin , Yaron Burg , Ilan Shufer , Olga Kogan
Abstract: 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.
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公开(公告)号：US10102105B2
公开(公告)日：2018-10-16
申请号：US15302759
申请日：2014-06-24
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor： Inbar Shani , Ohad Assulin , Yaron Burg
Abstract: 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.
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公开(公告)号：US20180267888A1
公开(公告)日：2018-09-20
申请号：US15758284
申请日：2015-09-08
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor： Inbar Shani , Ayal Cohen , Yaron Burg
CPC classification number: G06F11/3688 , G06F8/71 , G06F11/3692 , G06F16/9024
Abstract: 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.
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