Chapter 9 - Improving XML Performance. Improving .NET Application Performance and Scalability J.D. Meier, Srinath Vasireddy, Ashish Babbar, and Alex Mackman Microsoft Corporation May 2004 Related Links Home Page for Improving .NET Application Performance and Scalability Chapter 5 — Improving Managed Code Performance Checklist: XML Performance Send feedback to Scale@microsoft.com patterns & practices Library Summary: This chapter provides performance guidelines and coding techniques for writing, querying, parsing, and validating XML efficiently with .NET Framework classes.
Contents ObjectivesOverviewHow to Use This ChapterArchitecturePerformance and Scalability IssuesDesign ConsiderationsImplementation ConsiderationsParsing XMLValidating XMLWriting XMLXPath QueriesXSLT ProcessingSummaryAdditional Resources Objectives Optimize XML processing design. Overview When you build .NET applications, you use XML extensively. This chapter starts by providing a brief overview of XML in the Microsoft .NET Framework.
How to Use This Chapter XmlReader. Optimizing Client-Side Performance. This help article offers a few performance tips with code examples on pages where you have used RadAjaxManager to AJAX-enable many controls. Using a RadAjaxManager control allows you to easily create settings that update many controls on the page. Having a large number of AJAX-enabled controls to update, can both help with a performance problem by rendering smaller portions of the page (which is why most developers use AJAX) and worsen the situation by triggering unnecessary DOM layout updates. Dealing with the DOM performance problem will require actions specific for the current scenario. Most of the slowdown happens when updating multiple controls in a table element. Every DOM update triggers a set of layout recalculations that take up unneeded time.
Consider the HTML in Example 1: CopyExample 1: A simple table with labels. Having two AjaxSettings for both labels will cause two DOM element updates: the spans rendered by lblStatus and lblMessage, respectively. CopyCSS CopyHTML. Mockrolesnotobjects.pdf (application/pdf Object) Java performance tuning tips. Java Performance Tuning Java(TM) - see bottom of page Our valued sponsors who help make this site possible New Relic: Try free w/ production profiling and get a free shirt!
ManageEngine's Site24x7: End-to-End analysis on Java EE web transactions. Sign up for FREE! AppDynamics: Get complete browser to backend visibility. Monitor Now! Note that this page is very large. This page lists many other pages available on the web, together with a condensed list of tuning tips that each page includes.
The tips here include only those that are available online for free. Use this page by using your browser's "find" or "search" option to identify particular tips you are interested in on the page, and follow up by reading the referenced web page if clarification is necessary. This page is currently 411KB. Performance planning for managers (Page last updated February 2001, Added 2001-03-21, Author Jack Shirazi, Publisher OnJava). The Performance of Java's Lists. The SDK has several implementations of the ordered collection interface java.util.List.
The three best known are Vector, ArrayList, and LinkedList. One question that frequently reaches the Java Performance Tuning site asks about the performance differences between these List classes. In this article I'll take a look at the performance differences between the LinkedList implementation and the Vector/ArrayList implementations. To consider fully the performance ramifications of these classes, we need to know how they are implemented. So I'll start with brief descriptions of the most important implementation aspects from the point of view of performance.
The Vector and ArrayList implementations Vector and ArrayList are both implemented with an underlying Object[] array that stores the elements. Public Object get(int index) { //check the index is valid first .. code not shown here return elementData[index]; } Java Performance Tuning: Chapter 4: Object Creation. Java Reference Guide > Unit Testing: Tips From The Trenches. Last updated Mar 14, 2003. In recent years, test-driven development, or at least the process of employing unit tests, has been touted as one of the best mechanisms for developing high-quality code.
The reason for test-driven development, or TDD, gaining such widespread adoption is that tested code typically yields higher quality results than untested code (makes sense, right?) The different between TDD and simply writing test cases is that TDD defines a formal process for when and by whom test cases should be written: TDD states that test cases should be written before code is written and that test cases should be written by the developer writing the code that is to be tested.
The emphasis on writing test cases before writing code is so that you can have confidence in your test harness: if you write a test and it passes, but you have never seen it fail, then how do you know that the test case actually works? Integrating Performance Testing into the Agile Development Process. When talking about ‘quality’ in this respect, the focus is solely on functionality; non-functional quality, and particularly the ability of the application to perform and scale at times of peak usage, is excluded from testing that occurs within iterations. The main reason for excluding this type of testing is that performance tests have traditionally required weeks to set-up and hence the popular belief is that there is no time for performance testing within an Agile project’s iterations. Why is this a problem? Let us presume that an Agile project’s iterations last 3 weeks and needs 10 iterations before enough software has been developed and signed off to form a release to the business/client.
Following the commonly believed approach that the only time to performance test applications delivered by Agile projects is just before the software is released, that would mean that the performance testing would occur 30 weeks after the first line of code was written. A solution exists. ProactivePerfTuningJProbeSQLOptimizer-US.pdf (application/pdf Object) Java Reference Guide > Granular Testing with EasyMock.
Last updated Mar 14, 2003. One challenge that we face when writing unit tests is how to test components at a fine-granularity. For example, if you have a web-based application, testing a request as it passes from an action through a business service tier, back to a data access tier, and back out, is a good thing to do, but if the result is incorrect, how do you know where the problem is? In some cases the problem may be obvious, but in others it may be horribly complex. There are various ways to solve this problem, but the most common, and arguably the most effective, is to test each component through an interface using mock objects.
Before going further, a mock object is simply an object that behaves like a real object (typically by implementing the same interface as the real object), but returns known values. Mocking objects is really a two-phased activity: Creating your application to work with interfaces Creating mock versions of your objects Listing 1. Listing 2. Listing 3. Apache JMeter - Apache JMeter™