A method for preserving data during system migration includes determining which files on a computer should not be preserved, preserving all files from the computer not identified by the determining step, performing a system migration on the computer, and downloading the preserved files to the computer. The determining step may determines which files should not be preserved by applying rules that specify which files should not be preserved. A system for preserving data during system migration includes a plurality of workstation computers and a remote site server connected to the plurality of workstation computers. Each workstation computer includes a plurality of files.
Again, we will look at examples to understand this runtime analysis capability. Function list view Function List View is a typical runtime analysis view that can be generated with a specialized Runtime analysis tool such as Quantify see Figure 5. This view provides exact information about the number of calls to methods, time spent in methods only, time spent and memory accumulated in selected methods and all their descendants, and so on.
Function detail view A runtime analysis tool such as Quantify can also extend the information in Measurement Example 1 to include information about the distribution of measured data between calling methods and descendants.
This is shown in the Function Detail View Figure 6. This view highlights callers and descendants that contribute to a performance or memory hotspot -- information that can help detect the exact cause of a performance or memory bottleneck.
Quantify function detail view for a Visual C. NET application in Visual Studio. NET Measurement example 3: PureCoverage display of code coverage on the method level for a mixed C. Error detection example 1: Purify memory error and memory leak reports Purify can pinpoint the exact line of code where a developer has created a memory error.
In this particular example, the developer forgot to take the termination string into consideration when building an array variable. This error was causing the release build of the application to crash, whereas the debug build worked fine. Quantify annotated source Quantify has a unique capability to measure distribution of time recorded for each of the user methods per line of code.
Quantify annotated source displays times measured for each line of code, along with times spent and inside functions called on the line. This information can help you narrow the performance bottleneck down to an individual line of code Figure 9. Purify object and reference graph In Java and.
NET managed code, it is not possible to make runtime memory errors such as out of bounds reads and writes and free memory reads and writes, because the automatic memory management in the runtime subsystem prevents developers from directly accessing allocated memory.
As long as there is a reference to such dynamically allocated objects somewhere in the code, they will stay in memory and will not be cleaned by the automatic memory management garbage collector.
The memory becomes unavailable for this and all other processes running on the host operating system. By doing a runtime analysis with Purify, however, you can pinpoint the exact line of code where the reference to the object in question has been created Figure This helps you assess the overall quality of the project and measure the influence of newly introduced features and code changes on overall application performance, reliability, and test harness completeness.Amazon is the exception to nearly every rule in business..
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