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Besides the services listed above, because the DLR is built on top of the CLR, applications based on the DLR automatically benefit from the CLR s services. For example, .NET Application Domain and Remoting are leveraged in the DLR Hosting API to allow hosting dynamic languages in separate process or on a remote machine. The CLR s garbage collection is readily available to dynamic languages built on the DLR. If you were going to implement a language without taking advantage of the DLR, CLR, or JVM for that matter, imagine how much work you d have to do to, for example, implement a garbage collector for your language s runtime. While we are on the subject of runtimes and how they (i.e., the CLR and DLR) can be built on one another, let s throw IronPython into the picture. As mentioned earlier, IronPython is a runtime that interprets Python code. It is built on DLR. So when we run IronPython code, there will be three language runtimes, CLR, DLR, and IronPython, working together one on top of another.

This function asserts whether $value does not resolve to NULL. This function asserts whether $first is roughly equivalent (==) to $second. This function asserts whether $first is not equal to $second (!=). This function asserts whether $first is identical (===) to $second. This function asserts whether $first is not identical (!==) to $second. This function asserts that the raw HTML content of the current page matches the regular expression defined in $pattern. This function asserts that the raw HTML content of the current page does not match the regular expression defined in $pattern. This function asserts that the HTML defined in the $raw parameter exists in the content on the current page. This function asserts that the HTML defined in the $raw parameter does not exist in the content on the current page. This function asserts that the value stored in $text appears on the current page. This function asserts that the value stored in $text does not appear on the current page.

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You now have a perfectly valid way of building a system from scratch with little to no user interaction. All you need to do at this stage is supply the Vista build software and a unique product ID (or an enterprise key if you have a license agreement), and the system will install completely automatically. However, if you continue with the following sections, you ll be able to easily deploy the image to many systems at once, facilitating mass rollouts at an enterprise level. So, after you have finished configuring the installation, you need to do what is called a generalization of the system using sysprep.exe, whereby you remove all specific information from the image so you can deploy it over and over again.

$this->assertTitle($title, $message = %s , $group= Other ) $this->assertNoTitle($title, $message = %s , $group= Other ) $this->assertUniqueText($text, $message= %s , $group= Other ) $this->assertNoUniqueText($text, $message= %s , $group= Other ) $this->assertLink($label, $index = 0, $message= % , $group= Other )

On your master computer installation, you will need to run the sysprep.exe command from the command prompt to remove all specific installation characteristics from this system before it can be imaged. To do this, do the following: 1. Start the command prompt by pressing the Windows Logo+R, then typing cmd.exe, and finally pressing Enter. 2. Type C:\Windows\System32\Sysprep.exe /oobe /generalize /shutdown, and then press Enter. 3. Sysprep removes all machine-specific information and then shuts Vista down, ready for the imaging process.

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