NDLI: Cork: dynamic memory leak detection for garbage-collected languages

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Cork: dynamic memory leak detection for garbage-collected languages

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Cork: dynamic memory leak detection for garbage-collected languages

Content Provider	ACM Digital Library
Author	McKinley, Kathryn S. Jump, Maria
Abstract	A memory leak in a garbage-collected program occurs when the program inadvertently maintains references to objects that it no longer needs. Memory leaks cause systematic heap growth, degrading performance and resulting in program crashes after perhaps days or weeks of execution. Prior approaches for detecting memory leaks rely on heap differencing or detailed object statistics which store state proportional to the number of objects in the heap. These overheads preclude their use on the same processor for deployed long-running applications.This paper introduces a dynamic heap-summarization technique based on type that accurately identifies leaks, is space efficient (adding less than 1% to the heap), and is time efficient (adding 2.3% on average to total execution time). We implement this approach in Cork which utilizes dynamic type information and garbage collection to summarize the live objects in a type points-from graph (TPFG) whose nodes (types) and edges (references between types) are annotated with volume. Cork compares TPFGs across multiple collections, identifies growing data structures, and computes a type slice for the user. Cork is accurate: it identifies systematic heap growth with no false positives in 4 of 15 benchmarks we tested. Cork's slice report enabled us (non-experts) to quickly eliminate growing data structures in SPECjbb2000 and Elipse, something their developers had not previously done. Cork is accurate, scalable, and efficient enough to consider using online.
Starting Page	31
Ending Page	38
Page Count	8
File Format	PDF
ISBN	1595935754
DOI	10.1145/1190216.1190224
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2007-01-17
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Garbage collection Dynamic Runtime analysis Memory leak detection Memory leaks
Content Type	Text
Resource Type	Article

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