Work

Runtime Support of Speculative Optimization for Offline Escape Analysis

Year: 2007

Type: article

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.

Source: Journal of Bioresource Management

Authors: Kevin Cleereman, Michelle Cheatham, Krishnaprasad Thirunarayan

Language: English

Topic: Logic, programming, and type systems

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W1525893933

FWCI:

Cites: 11

Cited by: 2

Related to: 10