1993
DOI: 10.1145/152739.152747
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Infant mortality and generational garbage collection

Abstract: Generation-based garbage collection has been advocated by appealing to the intuitive but vague notion that "young objects are more likely to die than old objects". The intuition is, that if a generation-based garbage collection scheme focuses its effort on scanning recently created objects, then its scanning efforts will pay off more in the form of more recovered garbage, than if it scanned older objects. In this note, we show a counterexample of a system in which "infant mortality" is as high as you please, b… Show more

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Cited by 35 publications
(12 citation statements)
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“…Baker suggested theoretical models to explain allocation behavior [Bak94,Bak93]. Hayes analyzed survival rates for long-lived objects in Cedar, a Modula-like language, and found that objects that survive a certain age tend to die in clusters [Hay91].…”
Section: Related Workmentioning
confidence: 99%
“…Baker suggested theoretical models to explain allocation behavior [Bak94,Bak93]. Hayes analyzed survival rates for long-lived objects in Cedar, a Modula-like language, and found that objects that survive a certain age tend to die in clusters [Hay91].…”
Section: Related Workmentioning
confidence: 99%
“…Generational garbage collectors preferentially scan newly allocated objects, based on the premise that most objects have short lifetimes. But this strategy does not work if object lifetimes are exponentially distributed [45].…”
Section: Usesmentioning
confidence: 99%
“…In some sense, a garbage collector acts like a refrigerator. Baker [4] also considers a hypothetical case in which object lifetimes are distributed in the same way as radioactive halflife decay times. He proposes this model as a convenient mathematical abstraction, to show that the mark-cons ratio is the same for all generations with this kind of object lifetime distribution, even when the weak generational hypothesis is empirically valid, i.e.…”
Section: Application Of Mathematical Frameworkmentioning
confidence: 99%