Pretenuring can reduce copying costs in garbage collectors by allocating long-lived objects into regions that the garbage collector will rarely, if ever, collect. We extend previous work on pretenuring as follows: (1) We produce pretenuring advice that is neutral with respect to the garbage collector algorithm and configuration. We thus can and do combine advice from different applications. We find for our benchmarks that predictions using object lifetimes at each allocation site in Java programs are accurate, which simplifies the pretenuring implementation. (2) We gather and apply advice to both applications and Jikes RVM, a compiler and runtime system for Java written in Java. Our results demonstrate that building combined advice into Jikes RVM from different application executions improves performance, regardless of the application Jikes RVM is compiling and executing. This build-time advice thus gives user applications some benefits of pretenuring, without any application profiling. No previous work uses profile feedback to pretenure in the runtime system. (3) We find that application-only advice also consistently improves performance, but that the combination of build-time and application-specific advice is almost always noticeably better. (4) Our same advice improves the performance of generational, Older First, and Beltway collectors, illustrating that it is collector neutral. (5) We include an immortal allocation space in addition

Utility programs, which perform similar and largely independent operations on a sequence of inputs, include such common applications as compilers, interpreters, and document parsers; databases; and compression and encoding tools. The repetitive behavior of these programs, while often clear to users, has been difficult to capture automatically. We present an active profiling technique in which controlled inputs to utility programs are used to expose execution phases, which are then marked, automatically, through binary instrumentation, enabling us to exploit phase transitions in production runs with arbitrary inputs. Experiments with five programs from the SPEC benchmark suites show that phase behavior is surprisingly predictable in many (though not all) cases. This predictability can in turn be used for optimized memory management leading to significant performance improvement. 1.

JavaScript is widely used in web-based applications and is increasing popular with developers. So-called ”browser wars ” in recent years have focused on JavaScript performance, specifically claiming comparative results based on benchmark suites such as SunSpider and V8. In this paper we evaluate the behavior of JavaScript web applications from commercial websites and compare this behavior with the benchmarks. We measure three specific areas of JavaScript runtime behavior: 1) functions and code; 2) heap-allocated objects and data; 3) events and handlers. We find that the benchmarks are not representative of many real websites and that conclusions reached from measuring the benchmarks may be misleading. Specific examples of such misleading conclusions include the following: that web applications have many loops, that non-string objects in web applications are extremely short-lived, and that web applications handle few events. We hope our results will convince the JavaScript community to develop and adopt benchmarks that are more representative of real web applications. To reduce the total length of the paper, we have chosen to shrink our figures substantially, and we recommend that an interested reader view the document in color, preferably with the ability to enlarge the figures as needed. Our intent of including this much raw data is to allow interested readers an opportunity to draw their own conclusions. 2 1

In large programs written in managed languages such as Java and C#, holding unnecessary references often results in memory leaks and bloat, degrading significantly their run-time performance and scalability. Despite the existence of many leak detectors for such languages, these detectors often target low-level objects; as a result, their reports contain many false warnings and lack sufficient semantic information to help diagnose problems. This paper introduces a specification-based technique called LeakChaser that can not only capture precisely the unnecessary references leading to leaks, but also explain, with high-level semantics, why these references become unnecessary. At the heart of LeakChaser is a three-tier approach that uses varying levels of abstraction to assist programmers with different skill levels and code familiarity to find leaks. At the highest tier

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