Much research has been devoted to studies of and algorithms for memory management based on garbage collection or explicit allocation and deallocation. An alternative approach, region-based memory management, has been known for decades, but has not been wellstudied. In a region-based system each allocation specifies a region, and memory is reclaimed by destroying a region, freeing all the storage allocated therein. We show that on a suite of allocation-intensive C programs, regions are competitive with malloc/free and sometimes substantially faster. We also show that regions support safe memory management with low overhead. Experience with our benchmarks suggests that modifying many existing programs to use regions is not difficult. 1 Introduction The two most popular memory management techniques are explicit allocation and deallocation, as in C's malloc/free, and various forms of garbagecollection [Wil92]. Both have well-known advantages and disadvantages, discussed further below. A t...

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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 Eclipse, something their developers had not previously done. Cork is accurate, scalable, and efficient enough to consider using online. Categories and Subject Descriptors D.2.5 [Software Engineering]: Testing and Debugging—Debugging aids

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 Eclipse, something their developers had not previously done. Cork is accurate, scalable, and efficient enough to consider using online. Categories and Subject Descriptors D.2.5 [Software Engineering]: Testing and Debugging—Debugging aids