When analyzing a flame graph, one often asks questions like

• How many time in total was spent on class loading?
• What percentage of time Java code was running in the interpreter and in C1/C2 compiled methods?
• What is the impact of lambdas on the startup time?
• etc.

To assist in performance analysis, async-profiler can automatically classify stack traces into certain categories.
Examples of such categories would be

• Garbage collection
• JIT compilation
• Class loading
• Class verification
• Lambda bootstrapping
• itable/vtable dispatch overhead
• Running in the Interpreter
• VM runtime
• and so on.