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| Content Provider | ACM Digital Library |
|---|---|
| Author | Shacham, Ohad Vechev, Martin Yahav, Eran |
| Abstract | Languages such as Java and C#, as well as scripting languages like Python, and Ruby, make extensive use of Collection classes. A collection implementation represents a fixed choice in the dimensions of operation time, space utilization, and synchronization. Using the collection in a manner not consistent with this fixed choice can cause significant performance degradation. In this paper, we present CHAMELEON, a low-overhead automatic tool that assists the programmer in choosing the appropriate collection implementation for her application. During program execution, CHAMELEON computes elaborate trace and heap-based metrics on collection behavior. These metrics are consumed on-thefly by a rules engine which outputs a list of suggested collection adaptation strategies. The tool can apply these corrective strategies automatically or present them to the programmer. We have implemented CHAMELEON on top of a IBM's J9 production JVM, and evaluated it over a small set of benchmarks. We show that for some applications, using CHAMELEON leads to a significant improvement of the memory footprint of the application. |
| Starting Page | 408 |
| Ending Page | 418 |
| Page Count | 11 |
| File Format | |
| ISBN | 9781605583921 |
| DOI | 10.1145/1542476.1542522 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2009-06-15 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Java Semantic profiler Bloat Collections |
| Content Type | Text |
| Resource Type | Article |
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