Runtime Support of Speculative Optimization for Offline Escape AnalysisProceedings of the 2007 International Conference on Software Engineering Research & Practice
Document TypeConference Proceeding
Catalog RecordCatalog Record
AbstractEscape 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.
Citation InformationKevin Cleereman, Michelle Cheatham and Krishnaprasad Thirunarayan. "Runtime Support of Speculative Optimization for Offline Escape Analysis" Proceedings of the 2007 International Conference on Software Engineering Research & Practice (2007) p. 484 - 489 ISSN: 1601320345
Available at: http://works.bepress.com/tk_prasad/78/