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Communications of the ACM
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ACM Letters on Programming Languages and Systems (LOPLAS)
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ACM SIGPLAN Notices
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IEEE Transactions on Knowledge and Data Engineering
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ACM Transactions on Programming Languages and Systems (TOPLAS)
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Science of Computer Programming
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One of the most promising automatic storage reclamation techniques, generation-based storage reclamation, suffers poor performance if many objects live for a fairly long time and then die. We have investigated the severity of this problem by simulating Generation Scavenging automatic storage reclamation from traces of actual four-hour sessions. There was a wide variation in the sample runs, with garbage-collection overhead ranging from insignificant, during the interactive runs, to severe, during a single non-interactive run. All runs demonstrated that performance could be improved with two techniques: segregating large bitmaps and strings, and mediating tenuring with demographic feedback. These two improvements deserve consideration for any generation-based storage reclamation strategy.