DETERMINING CODE COMPLEXITY SCORES
    3.
    发明申请
    DETERMINING CODE COMPLEXITY SCORES 审中-公开
    确定代码复杂度

    公开(公告)号:US20170031800A1

    公开(公告)日:2017-02-02

    申请号:US15302759

    申请日:2014-06-24

    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。

    IDENTIFYING A CONFIGURATION ELEMENT VALUE AS A POTENTIAL CAUSE OF A TESTING OPERATION FAILURE
    4.
    发明申请
    IDENTIFYING A CONFIGURATION ELEMENT VALUE AS A POTENTIAL CAUSE OF A TESTING OPERATION FAILURE 有权
    将配置元素值确定为测试操作失败的潜在原因

    公开(公告)号:US20160283355A1

    公开(公告)日:2016-09-29

    申请号:US15035053

    申请日:2013-11-15

    CPC classification number: G06F11/3664 G06F11/3684 G06F11/3688 G06F11/3692

    Abstract: Examples disclosed herein relate to identifying a configuration element value as a potential cause of a testing operation failure. Examples include causing a testing operation to be performed approximately in parallel on each of a plurality of instances of an application executed in respective testing environments, acquiring configuration element values from each of the testing environments, and identifying at least one of the configuration element values as a potential cause of a testing operation failure.

    Abstract translation: 本文公开的示例涉及将配置元素值识别为测试操作失败的潜在原因。 示例包括使测试操作大致并行地执行在各个测试环境中执行的应用的多个实例中,从每个测试环境中获取配置元素值,并且将配置元素值中的至少一个识别为 测试操作失败的潜在原因。

    Separating test verifications from test executions

    公开(公告)号:US10534700B2

    公开(公告)日:2020-01-14

    申请号:US15508710

    申请日:2014-12-09

    Abstract: Example implementations relate to separating verifications from test executions. Some implementations may include a data capture engine that captures data points during test executions of the application under test. The data points may include, for example, application data, test data, and environment data. Additionally, some implementations may include a data correlation engine that correlates each of the data points with a particular test execution state of the application under test based on a sequence of events that occurred during the particular test execution state. Furthermore, some implementations may also include a test verification engine that, based on the correlation of the data points, verifies an actual behavior of the application under test separately from the particular test execution state.

    Production sampling for determining code coverage

    公开(公告)号:US10360140B2

    公开(公告)日:2019-07-23

    申请号:US15032667

    申请日:2013-11-27

    Abstract: Example embodiments relate to determining code coverage based on production sampling. In example embodiments, a production execution data set that includes metrics for code units of a software application is obtained, where the metrics include input and output values for each of the code units and an average execution count for each of the code units. Further, application code execution is tracked during a testing procedure of the software application to determine executed lines of code. At this stage, production code coverage of the software application is determined based on the production execution data set and the executed lines of code.

    EXECUTION OF INTERACTION FLOWS
    7.
    发明申请

    公开(公告)号:US20170371727A1

    公开(公告)日:2017-12-28

    申请号:US15535235

    申请日:2014-12-22

    CPC classification number: G06F9/547 G06F9/445 G06F15/16 H04L67/34

    Abstract: Examples relate to execution of interaction flows. The examples disclosed herein enable obtaining, via a user interface of a local client computing device, an interaction flow that defines an order of execution of a plurality of interaction points and values exchanged among the plurality of interaction points, the plurality of interaction points comprising a first interaction point that indicates an event executed by an application; triggering the execution of the interaction flow; determining whether any of remote client computing devices that are in communication with the local client computing device includes the application; and causing the first interaction point to be executed by the application in at least one of the remote client computing devices that are determined to include the application.

    Determining application change success ratings

    公开(公告)号:US10860458B2

    公开(公告)日:2020-12-08

    申请号:US15316618

    申请日:2014-07-31

    Abstract: In one example of the disclosure, a user-defined success criterion for an application change is received. The criterion is provided to a computing system associated with a developer-user of the application. Evaluation code, for evaluating implementation of the change according to the criterion, is received from the computing system. The evaluation code is caused to execute responsive to receipt of a notice of production deployment of the change. A success rating for the change is determined based upon application performance data attained via execution of the evaluation code.

    Determining code complexity scores

    公开(公告)号:US10102105B2

    公开(公告)日:2018-10-16

    申请号:US15302759

    申请日:2014-06-24

    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.

    AUTOMATIC REGRESSION IDENTIFICATION
    10.
    发明申请

    公开(公告)号:US20180267888A1

    公开(公告)日:2018-09-20

    申请号:US15758284

    申请日:2015-09-08

    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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