Summary

So, there was an awful lot of tools in this chapter, and then some more. What did we really learn from this chapter, besides a litany of tool names? Although it doesn't look like this at first glance, we indeed learned several important things, namely the following:

• What kinds of tools are programmers using for performance analysis?
• What platform, Qt version, and development environment will we be relying on in this book?
• What open source and free tools can we use on Windows in addition to Qt Creator? 
• Much insight can be gained by relatively simple means.
• How to profile a QML application's CPU usage.
• How to profile a C++ (and mixed QML/C++) application's CPU usage.
• How to investigate memory usage and find memory leaks.

There are even more specialized performance tools you could use, so there's virtually no limit to the amount of data you can collect. In the next chapter, we will let the tools rest for a little while and return to programming questions. As Qt is written in C++, and C++ will be used for any high-performance work in Qt (as we will see in the following chapters), we will turn our attention to that language. As you are at least a middle-level developer, you will already know a lot about C++, but we want to look at it from a different angle. Let's ignore the discussion of the most recent hot language feature or the newest annoying quirk and instead have a look at it from the vantage point of a performance engineer.