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Finding What's Not There: A New Approach to Revealing Neglected Conditions in Software

Finding What's Not There: A New Approach to Revealing Neglected Conditions in Software
寻找不存在的东西:揭示软件中被忽视的条件的新方法
批准号:
0702693
负责人:
H. Andy Podgurski
金额:
$0.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-06-01 至 2011-05-31

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中文摘要
翻译
P0702693寻找不存在的东西:揭示软件中被忽视条件的新方法Andy Podgurski探索了一种检测软件中被忽视条件的新方法,该方法基于这样的想法,即关于被忽视条件的重要线索通常分布在整个项目代码库中。 线索被表示为程序依赖图的未成年人,其模型编程模式中的特定条件得到妥善处理。 PDG minor允许各种各样的模式被建模简洁,而没有不必要的约束的上下文中,其中可能会发现的patterns.Patterns挖掘依赖图的数据库,以确定经常出现的图minor,在假设的编程模式被使用的越多,它就越有可能是正确的。 在识别出完全正确的模式之后,再次搜索图形数据库以识别对应于被忽略的条件的模式违规。 这种方法是区别于缺陷检测的相关工作,其重点是被忽视的条件,其使用的依赖图未成年人表示编程模式,并通过使用图挖掘技术来识别模式。 该方法将通过应用它来揭示各种开源项目中被忽视的条件来进行评估和改进。
英文摘要
P0702693Finding What's Not There: A New Approach to Revealing Neglected Conditions in SoftwareAndy PodgurskiA new approach to the detection of neglected conditions in software is explored that is based on the ideas that vital clues about neglected conditions are often distributed throughout a project code base. Clues are represented as graph minors of program dependence graphs, which model programming patterns in which particular conditions are handled properly. PDG minors permit a wide variety of such patterns to be modeled concisely and without unnecessary constraints on the contexts in which the patterns may be found. Patterns are found by mining a database of dependence graphs to identify recurring graph minors, on the assumption that the more a programming pattern is used, the more likely it is to be correct. After putatively correct patterns are identified, the graph database is searched again to identify pattern violations corresponding to neglected conditions. This approach is distinguished from related work on defect detection by its focus on neglected conditions, by its use of dependence graph minors to represent programming patterns, and by its use of graph mining technology to identify patterns. The approach will be evaluated and refined by applying it to reveal neglected conditions in a variety of open-source projects.
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SHF: Small: Causal Foundations of Statistical Fault Localization
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    1525178
  • 项目类别:
    Standard Grant
  • 资助金额:
    $49.75万
  • 财政年份:
    2015
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    0098325
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    Standard Grant
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  • 项目类别:
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  • 资助金额:
    $5.5万
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    1990
  • 负责人:
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  • 批准年份:
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