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MEMORY LEAK ANALYSIS BY USAGE TRENDS CORRELATION

机译:通过使用趋势相关性进行内存泄漏分析

摘要

Tools and techniques assist developers with the detection of memory leaks by using correlation of data type memory usage trends. In particular, investigations of memory leaks can be prioritized without always resorting to the use of bulky and performance-degrading memory dumps, by using these tools and techniques to identify leaky correlated data types. Data about a program's memory usage is processed to identify memory usage trends over time for respective data types, and the trends are searched for significant correlations. Correlated trends (and hence their corresponding data types) are grouped. Memory usage analysis information is displayed for grouped data types, such as the names of the most rapidly leaking data types, the names of correlated data types, leak rates, and leak amounts in terms of memory size and/or data object counts. Memory usage data may also be correlated with processing load requests to indicate which requests have associated memory leaks.
机译:工具和技术通过使用数据类型内存使用趋势的相关性来帮助开发人员检测内存泄漏。特别是,通过使用这些工具和技术来识别泄漏相关数据类型,可以优先进行内存泄漏调查,而不必始终依靠使用体积大且性能下降的内存转储。处理有关程序的内存使用情况的数据,以识别各个数据类型随时间推移的内存使用情况趋势,并在趋势中搜索明显的相关性。关联趋势(及其相应的数据类型)被分组。显示针对分组数据类型的内存使用情况分析信息,例如,根据内存大小和/或数据对象计数,最快速泄漏的数据类型的名称,相关数据类型的名称,泄漏率和泄漏量。存储器使用数据也可以与处理负载请求相关联,以指示哪些请求具有关联的存储器泄漏。

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