本文在原有高阶单步法研究的基础上对刚度为时间解析函数时方法的适用性进行了研究。
Based on the original research of the high order single step method, this paper makes the research on the applicability of this method for the analytic expression of stiffness.
如果您的解决方案利用处理时间的35%以上来解析soap消息，不要感到惊讶。
Do not be surprised if your solution utilizes up to 35% of your processing time parsing SOAP messages.
其中的原因是，大多数情况下脚本语言是 “即时” 解译的，因而它在执行时会损失一些解析和验证文本的时间和CPU周期。
The reason is that in most cases, the scripting language is interpreted "on the fly" and loses time and CPU cycles having to parse and validate text as it's executed.
处理消息所花费的时间：具体说来，是xml解析、任意流程管理、服务的调用以及最终响应编码。
The time it takes to handle the message: Specifically, the XML parsing, any flow management, invocation of the service, and the final response encoding.
还剩下两项内容需要解析：时间说明符，它是选项后的第一个参数，以及消息，消息是剩余的参数。
There are two remaining things to parse: the time specifier, which is the first argument after the options, and the message, which is any remaining arguments.
遗憾的是，传递XML数据的缺点是需要浏览器多花费一些时间来解析整个XML文档。
Unfortunately, the downside of transferring XML data is that it takes some time for the browser to parse through the XML document.
解析时间和空间与消息格式(结构和编码)有关。
The parsing time and space is related to the format (structure and encoding) of a message.
在这些图表中，您可以将第一个sax2计时值作为解析文档的基本时间。
In these charts you can regard the first timing value, for SAX2, as a base time for parsing the documents.
消息越大，解析它所需要的时间就越长。
The larger the message, the longer the time required to parse it.
随着时间的推移，该文件被解析并提交到我们的SLA数据库中。
Over time, this file is parsed and submitted to our SLA database.
页面解析和呈现时间得到了极大提高。
当然，实际答案取决于解析文件的目标，因此值得花时间探究所有选项。
Of course, the real answer depends on your goal when parsing the file, so it's worth the time to explore all your options.
磁盘中的文件很大，但是其解析和验证的时间也很长。
The file is big on the drive, and takes a long time to parse through and to validate.
应该注意的是，大部分时间花在解析和编译sql语句上。
It should be noted that a major part of the time is spent parsing and compiling the SQL statement.
就垃圾生成和执行时间而言，解析要调度的正确JSP开销非常大。
Resolving the correct JSP to which to dispatch is quite expensive in terms of garbage creation and execution time. For example (inside a JSP).
使用解析树表示还会使调试变得更容易，并缩短开发时间。
Working with a parse tree representation also makes debugging easy and speeds development time.
它还充当了我以前的论点(使用解析树使调试更容易，从而缩短开发时间)的示例。
It also serves as an example of my earlier contention that using parse trees makes debugging easier and consequently speeds development time.
XML解析花费的时间最长，使用的空间最大。
本地计算机上的响应时间是非常出色的，即使服务器代码解析是通过840k的XML。
The response time on my local machine was excellent, even with the server code parsing through 840k of XML.
它以图表的形式来表示解析xml消息的影响，平均来说，它占简单业务功能处理时间的20%到35%。
It diagrams the impact of parsing XML messages that average between 20% to 35% of the processing time of simple business functions.
不幸的是，在大部分的时间里，由于它对于性能方面的影响，解析器的消息验证函数不能被启用。
Unfortunately, a majority of the time, the parser's message validation functions are not enabled due to its impact on performance.
其中的主要原因在于WPF设计器已经拥有了自己的解析器，而重写该解析器以使用这个公共解析器将要花费大量时间。
A major reason for this is that the WPF designers already have their own parsers and rewriting them to use the common parser will take a significant amount of time.
C++程序员需要面对的最复杂的任务之一就是在一段合理的时间期限内编写一个解析器。
One of the more complicated tasks for a C++ programmer is coding a parser within a reasonable time period.
然而，如果使用UTF - 16的话，原始文档的大小便要加倍，这样的文档解析起来要花更多的时间。
However, if you use UTF-16, the size of the original document roughly doubles and the document takes longer to parse.
还要检索当前的用户时间表(使用第1部分所讨论的技术)，并解析时间表xml来显示用户先前消息的列表。
It also retrieves the current user timeline, using a technique discussed in Part 1, and parses the timeline XML to display a list of the user's previous messages.
通过尽快停止解析，您可以极大地减少解析时间。
You can greatly reduce the parsing time by stopping the parsing as soon as possible.
与XML消息相比，解析带标记的消息需要较少的时间，但是比定长消息解析的时间要长。
Parsing a tagged message takes less time than parsing a XML message, but it does take more time than parsing a fixed-length message.
与XML消息相比，解析带标记的消息需要较少的时间，但是比定长消息解析的时间要长。
Parsing a tagged message takes less time than parsing a XML message, but it does take more time than parsing a fixed-length message.
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