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Note that in most cases, these allocations are so efficient that it likely won't affect performane. However, it's possible it could have an affect in a tight inner loop. At the very least, it avoids noise when profiling.

Consider Cloning vs Creating a New Instance

In some cases, it can be relatively expensive to create a new instance of an object. In such cases, it might be worth considering if clone()ing an existing instance and mutating it is faster.

Once case where this appears to be beneficial is with ICU4J Calendar objects. Creating a new Calendar object via Calendar.getInstance(...)  is a fairly expensive process with lots of different object allocations. Instead, it is reccommend that one consider something like the following, which minimizes allocations and computations:

object SomeClass {
  val emptyCalendar = {
    val c = Calendar.getInstance(TimeZone.UNKNOWN_ZONE)
    c.clear()
    c
  }
}

def functionThatNeedsANewCalendar = {
  val cal = SomeClass.emptyCalendar.clone.asInstanceOf[Calendar]
  ...
  cal.set(...)
  ...
  cal
}

Examining Bytecode

As is apparent from the above suggestions, minimizing allocations is often key to improving Daffodil performance and making profiling less noisy. Often times an allocation will occur but it isn't clear based on the source why such an allocation might be happening. In these cases, it is often necessary to inspect the bytecode. To do so, the use of the javap  function can be invaluable. The following will convert a class to bytecode, including some helpful comments:

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