Dynamic memory allocation has been a fundamental part of most computer systems since roughly 1960, and memory allocation is widely considered to be either a solved problem or an insoluble one. In this survey, we describe a variety of memory allocator designs and point out issues relevant to their design and evaluation. We then chronologically survey most of the literature on allocators between 1961 and 1995. (Scores of papers are discussed, in varying detail, and over 150 references are given.) We argue that allocator designs have been unduly restricted by an emphasis on mechanism, rather than policy, while the latter is more important; higher-level strategic issues are still more important, but have not been given much attention. Most theoretical analyses and empirical allocator evaluations to date have relied on very strong assumptions of randomness and independence, but real program behavior exhibits important regularities that must be exploited if allocators are to perform well in practice.

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...

this paper was presented at the 7th ACM Symposium on Operating Systems Principles, Pacific Grove, Calif., Dec. 10-12, 1979

Region-based memory management systems structure memory by grouping objects in regions under program control. Memory is reclaimed by deleting regions, freeing all objects stored therein. Our compiler for C with regions, RC, prevents unsafe region deletions by keeping a count of references to each region. Using type annotations that make the structure of a program's regions more explicit, we reduce the overhead of reference counting from a maximum of 27% to a maximum of 11% on a suite of realistic benchmarks. We generalise these annotations in a region type system whose main novelty is the use of existentially quantified abstract regions to represent pointers to objects whose region is partially or totally unknown. A distribution of RC is available at http://www.cs.berkeley.edu/~dgay/rc.tar.gz.

This dissertation characterizes the space of trust metrics, under both the scalar assumption where each assertion is evaluated independently, and the group assumption where a group of assertions are evaluated in tandem. We present a quantitative framework for evaluating the attack resistance of trust metrics, and give examples of trust metrics that are within a small factor of optimum compared to theoretical upper bounds. We discuss experiences with a realworld deployment of a group trust metric, the Advogato website. Finally, we explore possible applications of attack resistant trust metrics, including using it as to build a distributed name server, verifying metadata in peer-to-peer networks such as music sharing systems, and a proposal for highly spam resistant e-mail delivery.

Programmers hoping to achieve performance improvements often use custom memory allocators. This in-depth study examines eight applications that use custom allocators. Surprisingly, for six of these applications, a state-of-the-art general-purpose allocator (the Lea allocator) performs as well as or better than the custom allocators. The two exceptions use regions, which deliver higher performance (improvements of up to 44%). Regions also reduce programmer burden and eliminate a source of memory leaks. However, we show that the inability of programmers to free individual objects within regions can lead to a substantial increase in memory consumption. Worse, this limitation precludes the use of regions for common programming idioms, reducing their usefulness. We present a generalization of general-purpose and region-based allocators that we call reaps. Reaps are a combination of regions and heaps, providing a full range of region semantics with the addition of individual object deletion. We show that our implementation of reaps provides high performance, outperforming other allocators with region-like semantics. We then use a case study to demonstrate the space advantages and software engineering benefits of reaps in practice. Our results indicate that programmers needing fast regions should use reaps, and that most programmers considering custom allocators should instead use the Lea allocator.

Current general-purpose memory allocators do not provide sufficient speed or flexibility for modern high-performance applications. Highly-tuned general purpose allocators have per-operation costs around one hundred cycles, while the cost of an operation in a custom memory allocator can be just a handful of cycles. To achieve high performance, programmers often write custom memory allocators from scratch -- a difficult and error-prone process. In this

Region-based memory management can be used to control dynamic memory allocations and deallocations safely and efficiently. Existing (direct-style) region systems that statically guarantee region safety---no dereferencing of dangling pointers---are based on refinements of Tofte and Talpin's seminal work on region inference for managing heap memory in stacks of regions.

Garbage collection offers numerous software engineering advantages, but interacts poorly with virtual memory managers. Existing garbage collectors require far more pages than the application's working set and touch pages without regard to which ones are in memory, especially during full-heap garbage collection. The resulting paging can cause throughput to plummet and pause times to spike up to seconds or even minutes. We present a garbage collector that avoids paging. This bookmarking collector cooperates with the virtual memory manager to guide its eviction decisions. Using summary information ("bookmarks") recorded from evicted pages, the collector can perform in-memory full-heap collections. In the absence of memory pressure, the bookmarking collector matches the throughput of the best collector we tested while running in smaller heaps. In the face of memory pressure, it improves throughput by up to a factor of five and reduces pause times by up to a factor of 45 over the next best collector. Compared to a collector that consistently provides high throughput (generational mark-sweep), the bookmarking collector reduces pause times by up to 218x and improves throughput by up to 41x. Bookmarking collection thus provides greater utilization of available physical memory than other collectors while matching or exceeding their throughput.

We report on our experience with designing, implementing, proving correct, and evaluating a region-based memory management system.