If you forget where the memory is that you asked for, in fact, that is how you make a memory leak.
如果您忘记了你要的内存在哪里，实际上，那就是造成你内存泄漏的原因。
RAD offers the following views for memory leak analysis
RAD为内存泄漏分析提供了以下视图
Listing 1. Code with memory leak and dangling pointer (mem_errors.c).
列表1 .带有一个内存渗漏和一个不断摆动的指针的代码(mem_errors. c)。
Deleting XMLHttpRequest objects to avoid a memory leak in the Web browser.
删除XMLHttpRequest对象以避免Web浏览器发生内存泄漏。
The code shown in Listing 1 shows both a memory leak and a dangling pointer.
显示在列表1中的代码展示了一个内存渗漏和一个不断摆动的指针。
Error detection example 1: Rational Purify memory error and memory leak reports.
错误检测实例1：RationalPurify内存错误和内存泄露报告。
The suspects TAB of the analysis results lists memory leak suspects in four tables.
分析结果的Suspects选项卡在四个表中列出了内存泄漏可疑点。
Figure 1 shows a sample notification generated by the memory leak detection feature.
图1显示了由内存泄漏检测特性所产生的示例通知。
The rate of memory leak can vary with load, but the total leaked memory will not drop.
内存泄漏率因负载而异，但泄漏的总内存则不会降低。
Listing 1 shows the serious memory leak created if you forget to join joinable threads.
清单1显示在忘记联接可接合线程时引发的严重内存泄漏。
The analysis results showing the memory leak suspects are shown in Figures 2, 3, and 4.
显示内存泄漏疑点的分析结构显示在图2、图3和图4中。
And most likely, such a memory leak is caused by a failure to join the joinable threads.
这种内存泄漏很有可能是因未能联接可接合线程而造成的。
Now, this may seem like an easy way to lose objects, which would result in a memory leak.
此方法看似容易丢失对象，会导致内存泄漏。
Figure 11 shows a memory leak case involving a large number of JMSTopicConnection objects.
图11显示了涉及大量JMSTopicConnection对象的内存泄漏情况。
It mimics a memory leak by randomly placing some of these arrays (~ 20% of them) into a list.
它通过随机将这些数组的一部分(大约20%)放入一个列表来模拟内存泄漏。
Many analysis tools, including MDD4J, analyze heap dumps to find the root cause of a memory leak.
许多分析工具（包括MDD4J）都可以分析堆转储，以找到内存泄漏的根源。
WebSphere Extended Deployment provides a number of policies that configure memory leak detection.
WebSphereExtendedDeployment提供了许多配置内存泄漏检测的策略。
Also, the test completion details included the results of memory leak analysis following each run.
同样，测试完成的详情包括每次运行后的内存泄漏分析的结果。
If a memory leak is present in your application, the heap memory usage steadily increases over time.
如果您的应用程序出现了内存泄漏，堆内存使用量将随时间稳步增长。
Comparative analysis is well suited to be used in conjunction with lightweight memory leak detection.
比较分析非常适合与轻量级内存泄漏检测一起使用。
Figure 13 shows a memory leak analysis suspect pointing at the WebSphere MemorySessionContext object.
图13显示了指向WebSphereMemorySessionContext对象的内存泄漏分析可疑点。
For this example I had let a colleague deliberately add a rather large memory leak to the application.
本例中，我请同事有意给程序增加了一处明显的内存泄露。
A memory leak is really identified when a system cannot recover used memory after the load is removed.
如果在删除负载之后，系统不能够恢复所使用的内存，那么我们就确定发生了内存泄漏。
If the memory leak is exacerbated by certain requests, failures can be intermittent and hard to predict.
如果内存泄漏由于某些请求而恶化，可能会不断出现错误并且难以预测。
Every memory leak I've seen is based on traffic, so the more traffic you get, the faster you leak memory.
我目前见到的内存泄漏情况都是与流量相关的，也就是说，流量越大，内存泄漏的速度就越快。
This heuristic has been found to be effective in a large number of memory leak cases handled in IBM Support.
在大量由IBM支持部门处理的内存泄漏案例中，已经发现这种启发式方法非常有效。
If the free memory after a GC cycle is consistently decreasing, then there is a high chance of a memory leak.
如果垃圾收集周期之后的可用内存持续降低，那么存在内存泄漏的可能性较高。
However, the tool does not aid in identifying the faulty source code responsible for causing the memory leak.
不过，该工具不能帮助确定导致内存泄漏的错误源代码。
Identification of suspected data structures aid in a better understanding of the root cause of a memory leak.
标识可疑数据结构有助于更好地理解内存泄漏的根源。
The most likely type is a memory problem, such as memory leak, heap fragmentation, or large object allocation.
最有可能的类型是内存问题，如内存泄漏、堆碎片、或者大对象分配。
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