The third step in profiling performance is to focus the data to pinpoint any bottlenecks in your code.
The base dataset collected for a run can be very large, but Quantify helps you focus on the specific data that concerns you.
Quantify begins the focusing process by automatically applying a set of default filters. These filters hide data that is ordinarily of no interest, such as data collected for system libraries.
To focus even more closely on data for specific parts of your code, you can:
§ Specify additional filters to remove functions based on module, class, pattern (for example, functions with CWnd in their name), or measurement type (for example, all waiting and blocking functions).
§ Focus on a specific subtree in the Call Graph.
§ Hide or show columns of data to display only the type of performance data you are currently interested in.
Techniques for focusing data are essential, given the completeness of the data Quantify collects. In addition to focusing data after you collect it, Quantify provides ways of focusing data both before you collect data and while you are collecting data. For a list of the ways you can focus data, read Tips for Focusing Data.
(C) Copyright IBM Corporation 1993, 2009.