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    Code-Clone Detection and Analysis
    3.
    发明申请
    Code-Clone Detection and Analysis 有权
    代码克隆检测与分析

    公开(公告)号：US20110246968A1

    公开(公告)日：2011-10-06

    申请号：US12752942

    申请日：2010-04-01

    Applicant: Dongmei Zhang ,  Yingnong Dang ,  Yingjun Qiu ,  Song Ge

    Inventor： Dongmei Zhang ,  Yingnong Dang ,  Yingjun Qiu ,  Song Ge

    IPC: G06F9/44

    CPC classification number: G06F8/751 ,  G06F8/71 ,  G06F8/75

    Abstract: Techniques for detecting, analyzing, and/or reporting code clone are described herein. In one or more implementations, clone-code detection is performed on one or more source code bases to find true and near clones of a subject code snippet that a user (e.g., a software developer) expressly or implicitly selected. In one or more other implementations, code clone is analyzed to estimate the code-improvement-potential (such as bug-potential and code-refactoring-potential) properties of clones. One or more other implementations present the results of code clone analysis with indications (e.g., rankings) of the estimated properties of the respective the clones.

    Abstract translation: 本文描述了用于检测，分析和/或报告代码克隆的技术。 在一个或多个实现中，在一个或多个源代码库上执行克隆代码检测，以找到用户（例如，软件开发者）明确或隐含地选择的主题代码段的真实和近似克隆。 在一个或多个其他实现中，分析代码克隆以估计克隆的代码提高潜力（诸如错误潜力和代码重构 - 潜在）性质。 一个或多个其他实施方案通过相应克隆的估计性质的指示（例如，排名）呈现代码克隆分析的结果。

    Error report processing using call stack similarity
    4.
    发明授权
    Error report processing using call stack similarity 有权
    使用调用堆栈相似性的错误报告处理

    公开(公告)号：US08949675B2

    公开(公告)日：2015-02-03

    申请号：US12957090

    申请日：2010-11-30

    Applicant: Dongmei Zhang ,  Yingnong Dang ,  Song Ge

    Inventor： Dongmei Zhang ,  Yingnong Dang ,  Song Ge

    IPC: G06F11/00 ,  G06F11/07

    CPC classification number: G06F11/0781 ,  G06F11/0775 ,  G06F11/0778 ,  G06F11/0787

    Abstract: Techniques for error report processing are described herein. Error reports, received by a developer due to program crashes, may be organized into a plurality of “buckets.” The buckets may be based in part on a name and a version of the application associated with a crash. Additionally, a call stack of the computer on which the crash occurred may be associated with each error report. The error reports may be “re-bucketed” into meta-buckets to provide additional information to programmers working to resolve software errors. The re-bucketing may be based in part on measuring similarity of call stacks of a plurality of error reports. The similarity of two call stacks—a measure of likelihood that two error reports were caused by a same error—may be based in part on functions in common, a distance of those functions from the crash point, and an offset distance between the common functions.

    Abstract translation: 这里描述了用于错误报告处理的技术。 开发人员由于程序崩溃而收到的错误报告可以被组织成多个“桶”。桶可以部分地基于与崩溃相关联的应用的名称和版本。 此外，发生崩溃的计算机的调用堆栈可能与每个错误报告相关联。 错误报告可能会重新分级到元数据桶中，以便为解决软件错误的程序员提供更多信息。 可以部分地基于测量多个错误报告的调用堆栈的相似度来重新估计。 两个调用堆栈的相似性 - 两个错误报告由相同错误引起的可能性的度量可能部分地基于共同的功能，这些功能与碰撞点的距离以及公共功能之间的偏移距离 。

    Analyzing Program Execution
    5.
    发明申请
    Analyzing Program Execution 审中-公开
    分析程序执行

    公开(公告)号：US20120278659A1

    公开(公告)日：2012-11-01

    申请号：US13095336

    申请日：2011-04-27

    Applicant: Shi Han ,  Yingnong Dang ,  Song Ge ,  Dongmei Zhang

    Inventor： Shi Han ,  Yingnong Dang ,  Song Ge ,  Dongmei Zhang

    IPC: G06F11/36

    CPC classification number: G06F11/3072 ,  G06F11/302 ,  G06F11/323 ,  G06F11/3466 ,  G06F11/3612 ,  G06F2201/865

    Abstract: A call pattern database is mined to identify frequently occurring call patterns related to program execution instances. An SVM classifier is iteratively trained based at least in part on classifications provided by human analysts; at each iteration, the SVM classifier identifies boundary cases, and requests human analysis of these cases. The trained SVM classifier is then applied to call pattern pairs to produce similarity measures between respective call patterns of each pair, and the call patterns are clustered based on the similarity measures.

    Abstract translation: 调用模式数据库被开采以识别与程序执行实例有关的频繁出现的调用模式。 至少部分基于人类分析师提供的分类，对SVM分类器进行迭代训练; 在每个迭代中，SVM分类器识别边界情况，并请求对这些情况的人类分析。 然后将经过训练的SVM分类器应用于呼叫模式对以在每对的相应呼叫模式之间产生相似性度量，并且基于相似性度量来呼叫模式聚类。

    CODE CLONE NOTIFICATION AND ARCHITECTURAL CHANGE VISUALIZATION
    6.
    发明申请
    CODE CLONE NOTIFICATION AND ARCHITECTURAL CHANGE VISUALIZATION 审中-公开
    代码通知和架构变更可视化

    公开(公告)号：US20120159434A1

    公开(公告)日：2012-06-21

    申请号：US12972535

    申请日：2010-12-20

    Applicant: Yingnong Dang ,  Sadi Khan ,  Dongmei Zhang ,  Weipeng Liu ,  Song Ge ,  Gong Cheng

    Inventor： Yingnong Dang ,  Sadi Khan ,  Dongmei Zhang ,  Weipeng Liu ,  Song Ge ,  Gong Cheng

    IPC: G06F9/44

    CPC classification number: G06F8/36 ,  G06F8/751

    Abstract: A code verification system is described herein that provides augmented code review with code clone analysis and visualization to help software developers automatically identify similar instances of the same code and to visualize differences in versions of software code over time. The system uses code clone search technology to identify code clones and to present the user with information about similar code as the developer makes changes. The system may provide automated notification to the developer or to other teams as changes are made to code segments with one or more related clones. The code verification system also helps the developer to understand architectural evolution of a body of software code. The code verification system provides an analysis component for determining architectural differences based on the code clone detection result between the two versions of the software code base. The code verification system also provides a user interface component for displaying identified differences to developers and others involved with the software development process in intuitive and useful ways.

    Abstract translation: 本文描述了一种代码验证系统，其通过代码克隆分析和可视化来提供增强的代码审查，以帮助软件开发人员自动识别相同代码的相似实例，并可视化软件代码随时间的版本的差异。 该系统使用代码克隆搜索技术来识别代码克隆，并向用户呈现与开发者进行更改相似的代码的信息。 系统可以向开发人员或其他团队提供自动通知，因为对具有一个或多个相关克隆的代码段进行了更改。 代码验证系统还可以帮助开发人员了解一系列软件代码的架构演变。 代码验证系统基于软件代码库的两个版本之间的代码克隆检测结果提供了用于确定架构差异的分析组件。 代码验证系统还提供了一个用户界面组件，用于以直观和有用的方式向开发人员和与软件开发过程相关的其他人显示识别的差异。

    Error Report Processing
    7.
    发明申请
    Error Report Processing 有权
    错误报告处理

    公开(公告)号：US20120137182A1

    公开(公告)日：2012-05-31

    申请号：US12957090

    申请日：2010-11-30

    Applicant: Dongmei Zhang ,  Yingnong Dang ,  Song Ge

    Inventor： Dongmei Zhang ,  Yingnong Dang ,  Song Ge

    IPC: G06F11/00

    CPC classification number: G06F11/0781 ,  G06F11/0775 ,  G06F11/0778 ,  G06F11/0787

    Abstract: Techniques for error report processing are described herein. Error reports, received by a developer due to program crashes, may be organized into a plurality of “buckets.” The buckets may be based in part on a name and a version of the application associated with a crash. Additionally, a call stack of the computer on which the crash occurred may be associated with each error report. The error reports may be “re-bucketed” into meta-buckets to provide additional information to programmers working to resolve software errors. The re-bucketing may be based in part on measuring similarity of call stacks of a plurality of error reports. The similarity of two call stacks—a measure of likelihood that two error reports were caused by a same error—may be based in part on functions in common, a distance of those functions from the crash point, and an offset distance between the common functions.

    Abstract translation: 这里描述了用于错误报告处理的技术。 开发人员由于程序崩溃而收到的错误报告可以被组织成多个“桶”。桶可以部分地基于与崩溃相关联的应用的名称和版本。 此外，发生崩溃的计算机的调用堆栈可能与每个错误报告相关联。 错误报告可能会重新分级到元数据桶中，以便为解决软件错误的程序员提供更多信息。 可以部分地基于测量多个错误报告的调用堆栈的相似度来重新估计。 两个调用堆栈的相似性 - 两个错误报告由相同错误引起的可能性的度量可能部分地基于共同的功能，这些功能与碰撞点的距离以及公共功能之间的偏移距离 。

    Code-clone detection and analysis
    8.
    发明授权
    Code-clone detection and analysis 有权
    代码克隆检测和分析

    公开(公告)号：US09110769B2

    公开(公告)日：2015-08-18

    申请号：US12752942

    申请日：2010-04-01

    Applicant: Dongmei Zhang ,  Yingnong Dang ,  Yingjun Qiu ,  Song Ge

    Inventor： Dongmei Zhang ,  Yingnong Dang ,  Yingjun Qiu ,  Song Ge

    IPC: G06F9/44

    CPC classification number: G06F8/751 ,  G06F8/71 ,  G06F8/75

    Abstract: Techniques for detecting, analyzing, and/or reporting code clone are described herein. In one or more implementations, clone-code detection is performed on one or more source code bases to find true and near clones of a subject code snippet that a user (e.g., a software developer) expressly or implicitly selected. In one or more other implementations, code clone is analyzed to estimate the code-improvement-potential (such as bug-potential and code-refactoring-potential) properties of clones. One or more other implementations present the results of code clone analysis with indications (e.g., rankings) of the estimated properties of the respective the clones.

    Abstract translation: 本文描述了用于检测，分析和/或报告代码克隆的技术。 在一个或多个实现中，在一个或多个源代码库上执行克隆代码检测，以找到用户（例如，软件开发者）明确或隐含地选择的主题代码段的真实和近似克隆。 在一个或多个其他实现中，分析代码克隆以估计克隆的代码提高潜力（诸如错误潜力和代码重构 - 潜在）性质。 一个或多个其他实施方案通过相应克隆的估计性质的指示（例如，排名）呈现代码克隆分析的结果。

    Frequent pattern mining
    9.
    发明授权
    Frequent pattern mining 有权
    频繁模式挖掘

    公开(公告)号：US09348852B2

    公开(公告)日：2016-05-24

    申请号：US13095415

    申请日：2011-04-27

    Applicant: Shi Han ,  Yingnong Dang ,  Song Ge ,  Dongmei Zhang

    Inventor： Shi Han ,  Yingnong Dang ,  Song Ge ,  Dongmei Zhang

    IPC: G06F17/30

    CPC classification number: G06F17/30539 ,  G06F17/30306 ,  H04L67/10

    Abstract: A system for frequent pattern mining uses two layers of processing: a plurality of computing nodes, and a plurality of processors within each computing node. Within each computing node, the data set against which the frequent pattern mining is to be performed is stored in shared memory, accessible concurrently by each of the processors. The search space is partitioned among the computing nodes, and sub-partitioned among the processors of each computing node. If a processor completes its sub-partition, it requests another sub-partition. The partitioning and sub-partitioning may be performed dynamically, and adjusted in real time.

    Abstract translation: 用于频繁模式挖掘的系统使用两层处理：多个计算节点和每个计算节点内的多个处理器。 在每个计算节点内，将要执行频繁模式挖掘的数据集存储在共享存储器中，由每个处理器并发访问。 搜索空间在计算节点之间划分，并在每个计算节点的处理器之间进行子分区。 如果处理器完成其子分区，则它请求另一个子分区。 可以动态执行分区和子分区，并实时调整。

    Frequent Pattern Mining
    10.
    发明申请
    Frequent Pattern Mining 有权
    频繁模式挖掘

    公开(公告)号：US20120278346A1

    公开(公告)日：2012-11-01

    申请号：US13095415

    申请日：2011-04-27

    Applicant: Shi Han ,  Yingnong Dang ,  Song Ge ,  Dongmei Zhang

    Inventor： Shi Han ,  Yingnong Dang ,  Song Ge ,  Dongmei Zhang

    IPC: G06F17/30

    CPC classification number: G06F17/30539 ,  G06F17/30306 ,  H04L67/10

    Abstract: A system for frequent pattern mining uses two layers of processing: a plurality of computing nodes, and a plurality of processors within each computing node. Within each computing node, the data set against which the frequent pattern mining is to be performed is stored in shared memory, accessible concurrently by each of the processors. The search space is partitioned among the computing nodes, and sub-partitioned among the processors of each computing node. If a processor completes its sub-partition, it requests another sub-partition. The partitioning and sub-partitioning may be performed dynamically, and adjusted in real time.

    Abstract translation: 用于频繁模式挖掘的系统使用两层处理：多个计算节点和每个计算节点内的多个处理器。 在每个计算节点内，将要执行频繁模式挖掘的数据集存储在共享存储器中，由每个处理器并发访问。 搜索空间在计算节点之间划分，并在每个计算节点的处理器之间进行子分区。 如果处理器完成其子分区，则它请求另一个子分区。 可以动态执行分区和子分区，并实时调整。

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