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Automated scalable and adaptive system for memory analysis via identification of leak root candidates

机译:自动化的可扩展自适应系统,用于通过识别泄漏根源来进行内存分析

摘要

A method for identifying a set of objects in a target application program includes: receiving a plurality of samples of one or more object reference graphs, wherein each object reference graph includes live objects and their references; deriving a set of candidate data structures from the samples; collecting a plurality of properties of each of the live objects in relation to data structures over time; and using a mixture model, combining the plurality of the properties of each live object in a non-linear manner for ranking leak root candidates within each set of candidate data structures The method also includes the identification of an initial set of highly-ranked candidate objects that are possible causes of at least one object leak, wherein the higher the ranking the smaller the identified set.
机译:一种用于在目标应用程序中识别一组对象的方法,包括:接收一个或多个对象参考图的多个样本,其中,每个对象参考图包括活动对象及其参考。从样本中得出一组候选数据结构;随时间收集与数据结构有关的每个活动对象的多个属性;并使用混合模型,以非线性方式组合每个活动对象的多个属性,以对每组候选数据结构内的泄漏根候选进行排序。该方法还包括识别一组初始的高排名候选对象这些是可能导致至少一个对象泄漏的原因,其中等级越高,所标识的集合就越小。

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