Document Type
Conference Proceeding
Publication Date
6-2007
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Abstract
Escape analysis can improve the speed and memory efficiency of garbage collected languages by allocating objects to the call stack, but an offline analysis will potentially interfere with dynamic class loading and an online analysis must sacrifice precision for speed. We describe a technique that permits the safe use of aggressive, speculative offline escape analysis in programs potentially loading classes that violate the analysis results.
Repository Citation
Cleereman, K.,
Cheatham, M.,
& Thirunarayan, K.
(2007). Runtime Support of Speculative Optimization for Offline Escape Analysis. Proceedings of the 2007 International Conference on Software Engineering Research & Practice, 484-489.
https://corescholar.libraries.wright.edu/knoesis/884
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Comments
Presented at the International Conference on Software Engineering Research & Practice, Las Vegas, NV, June 25-28, 2007.
Attached is the unpublished, author's version of this proceeding. The final, publisher's version can be found in the proceedings via the Catalog Record.