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Next, we look at the process of identifying and addressing a resource leak from the 30,000 foot view, and then we start to dig into the details
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The process of resolving a resource leak in your code is illustrated in Figure 91 In this section, we examine each of the parts of the process in detail
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Step 1: Identify Potential Resource Leaks
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The first step in the resource leak process is convincing yourself that what you are seeing is, in fact, a leak Many applications will include internal caches that are filled during heavy load and subsequently released when in an idle state, hence leading to a false positive Another false positive might be that an overall increase in memory usage is observed, but it might not necessarily mean that your application is leaking All good investigations start with the basics, and, as such, the first step should be identifying potentially leaking resources This is accomplished by a thorough analysis of the state of the machine, paying careful attention to abnormally large amounts of one or more resource types Only after this has been confirmed can you safely move on to the diagnostics stage Several different tools are out there that allow you to analyze
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system health The most basic tool (part of Windows) is the Task Manager (CTRL+SHIFT+ESC or taskmanexe) Using Task Manager, you get a global view of the system resource consumption, as well as a more granular view for each process running, as shown in Figure 92
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Is it even a resource leak
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Done
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Identify the type of resource leaked
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Perform an initial analysis
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Make use of resource leak detection tools
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Figure 91 Task Manager can be customized to show different types of process data If the process you are investigating is showing an unusually high amount of resource usage, chances are good that you are seeing a resource leak At this point, the first step of the process is completed You have identified a large amount of resources being consumed by the alleged process by using Task Manager, and it is time to move on to the diagnostics stage
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9 RESOURCE LEAKS
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9
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Resource Leaks
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Step 2: What Is Leaking
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The next critical step is figuring out what type of resource the application is leaking In step 1, we have already touched on how Task Manager can display useful data for any given process running in the system You can customize the available options by opening Task Manager (CTRL+SHIFT+ESC) followed by View, Choose Columns This opens the Select Columns dialog in Figure 93
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The columns most applicable to resource leaks are
Memory Usage (working set size) Memory Usage Delta Peak Memory Usage Virtual Memory Size Handle Count Thread Count GDI Objects (if the application uses UI features) and USER Objects
After you ve enabled the columns of interest, Task Manager will display the data as new columns in the Processes view Another great tool that can be used to track resource leaks is Performance Monitor (Start, Run: perfmonexe) Performance Monitor has the added benefit of including a ton of memory-related counters that can be used to track leaks over time
Step 3: Initial Analysis
Let s say that step 2 showed your process using a large number of handles (more than it should) The next step is to do an initial analysis Because you are probably familiar with the code you are analyzing, a great starting point is to look at code paths involving handles It is surprising how many resource leaks can be identified simply by following some basic steps and eyeballing the code that works with the resource in question What is actually happening to make the resource usage grow in the first place If you have the answer to that question, you can begin with either code reviewing the paths during those operations or stepping through it in the debugger, paying careful attention to any of those specific resources being used After you have identified where the resource is opened, finding the missing resource close is fairly trivial Congratulations! You have just identified and fixed a resource leak at a very low cost Unfortunately, not all solutions to resource leaks are as trivial as merely eyeballing the code, and it is sometimes impossible to find the source of the leak that way Several reasons for this exist: