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1. 发明授权

US08151146B2 Tool for predicting fault-prone software files 有权
标题翻译：用于预测容易出错的软件文件的工具
公开(公告)号：US08151146B2
公开(公告)日：2012-04-03
申请号：US12137282
申请日：2008-06-11
申请人： Thomas Ostrand , Robert Bell , Andrew Gauld , Elaine Weyuker
发明人： Thomas Ostrand , Robert Bell , Andrew Gauld , Elaine Weyuker
IPC分类号： G06F11/00
CPC分类号： G06F11/3616 , G06F11/008
摘要： A method, apparatus, and computer-readable medium for predicting the fault-proneness of code units (files, modules, packages, and the like) of large-scale, long-lived software systems. The method collects information about the code units and the development process from previous releases, and formats this information for input to an analysis stage. The tool then performs a statistical regression analysis on the collected data, and formulates a model to predict fault counts for code units of the current and future releases. Finally, the method computes an expected fault count for each code unit in the current release by applying the formulated model to data from the current release. The expected fault counts are used to rank the release units in descending order of fault-proneness so that debugging efforts and resources can be optimized.
摘要翻译：一种用于预测大规模，长寿命的软件系统的代码单元（文件，模块，软件包等）的故障倾向性的方法，装置和计算机可读介质。该方法从先前版本收集有关代码单元和开发过程的信息，并将此信息格式化为输入到分析阶段。然后，该工具对收集的数据进行统计回归分析，并制定一个模型来预测当前和将来版本的代码单元的故障计数。最后，该方法通过将配置的模型应用于当前版本的数据来计算当前版本中每个代码单元的预期故障计数。预期故障计数用于按故障倾向的降序对发布单元进行排序，从而可以优化调试工作和资源。

2. 发明申请

US20090313605A1 TOOL FOR PREDICTING FAULT-PRONE SOFTWARE FILES 有权
标题翻译：预测故障软件文件的工具
公开(公告)号：US20090313605A1
公开(公告)日：2009-12-17
申请号：US12137282
申请日：2008-06-11
申请人： Thomas Ostrand , Robert Bell , Andrew Gauld , Elaine Weyuker
发明人： Thomas Ostrand , Robert Bell , Andrew Gauld , Elaine Weyuker
IPC分类号： G06F11/36
CPC分类号： G06F11/3616 , G06F11/008
摘要： A method, apparatus, and computer-readable medium for predicting the fault-proneness of code units (files, modules, packages, and the like) of large-scale, long-lived software systems. The method collects information about the code units and the development process from previous releases, and formats this information for input to an analysis stage. The tool then performs a statistical regression analysis on the collected data, and formulates a model to predict fault counts for code units of the current and future releases. Finally, the method computes an expected fault count for each code unit in the current release by applying the formulated model to data from the current release. The expected fault counts are used to rank the release units in descending order of fault-proneness so that debugging efforts and resources can be optimized.
摘要翻译：一种用于预测大规模，长寿命的软件系统的代码单元（文件，模块，软件包等）的故障倾向性的方法，装置和计算机可读介质。该方法从先前版本收集有关代码单元和开发过程的信息，并将此信息格式化为输入到分析阶段。然后，该工具对收集的数据进行统计回归分析，并制定一个模型来预测当前和将来版本的代码单元的故障计数。最后，该方法通过将配置的模型应用于当前版本的数据来计算当前版本中每个代码单元的预期故障计数。预期故障计数用于按故障倾向的降序对发布单元进行排序，从而可以优化调试工作和资源。

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