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It does so by checking whether the process memory usage increased before and after calling the function many times. Note that this is hard (probably impossible) to do reliably, due to how the OS handles memory, the GC and so on (memory can even decrease!). In order to avoid false positives, in case of failure (mem > 0) we retry the test for up to 5 times, increasing call repetitions each time. If the memory keeps increasing then it's a failure. If available (Linux, OSX, Windows), USS memory is used for comparison, since it's supposed to be more precise, see: https://gmpy.dev/blog/2016/real-process-memory-and-environ-in-python If not, RSS memory is used. mallinfo() on Linux and _heapwalk() on Windows may give even more precision, but at the moment are not implemented. PyPy appears to be completely unstable for this framework, probably because of its JIT, so tests on PYPY are skipped. 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