We survey basic garbage collection algorithms, and variations such as incremental and generational collection; we then discuss low-level implementation considerations and the relationships between storage management systems, languages, and compilers. Throughout, we attempt to present a uni ed view based on abstract traversal strategies, addressing issues of conservatism, opportunism, and immediacy of reclamation; we also point outavariety of implementation details that are likely to have a significant impact on performance.

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.

Squeak is an open, highly-portable Smalltalk implementation whose virtual machine is written entirely in Smalltalk, making it easy to debug, analyze, and change. To achieve practical performance, a translator produces an equivalent C program whose performance is comparable to commercial Smalltalks. Other noteworthy aspects of Squeak include: a compact object format that typically requires only a single word of overhead per object; a simple yet efficient incremental garbage collector for 32-bit direct pointers; efficient bulkmutation of objects; extensions of BitBlt to handle color of any depth and anti-aliased image rotation and scaling; and real-time sound and music synthesis written entirely in Smalltalk. Overview Squeak is a modern implementation of Smalltalk-80 that is available for free via the Internet, at

. We have developed and implemented techniques that double the performance of dynamically-typed object-oriented languages. Our SELF implementation runs twice as fast as the fastest Smalltalk implementation, despite SELF's lack of classes and explicit variables. To compensate for the absence of classes, our system uses implementation-level maps to transparently group objects cloned from the same prototype, providing data type information and eliminating the apparent space overhead for prototype-based systems. To compensate for dynamic typing, user-defined control structures, and the lack of explicit variables, our system dynamically compiles multiple versions of a source method, each customized according to its receiver's map. Within each version the type of the receiver is fixed, and thus the compiler can statically bind and inline all messages sent to self. Message splitting and type prediction extract and preserve even more static type information, allowing the compiler to inline ma...

Abstract. We have developed and implemented techniques that double the performance of dynamically-typed object-oriented languages. Our SELF implementation runs twice as fast as the fastest Smalltalk implementation, despite SELF’s lack of classes and explicit variables. To compensate for the absence of classes, our system uses implementation-level maps to transparently group objects cloned from the same prototype, providing data type information and eliminating the apparent space overhead for prototype-based systems. To compensate for dynamic typing, user-defined control structures, and the lack of explicit variables, our system dynamically compiles multiple versions of a source method, each customized according to its receiver’s map. Within each version the type of the receiver is fixed, and thus the compiler can statically bind and inline all messages sent to self. Message splitting and type prediction extract and preserve even more static type information, allowing the compiler to inline many other messages. Inlining dramatically improves performance and eliminates the need to hard-wire low-level methods such as +, ==, and ifTrue:. Despite inlining and other optimizations, our system still supports interactive programming environments. The system traverses internal dependency lists to invalidate all compiled methods

The complexity of systems for automatic control and other safety-critical applications grows rapidly. Computer software represents an increasing part of the complexity. As larger systems are developed, we need to find scalable techniques to manage the complexity in order to guarantee high product quality. Memory management is a key quality factor for these systems. Automatic memory management, or garbage collection, is a technique that significantly reduces the complex problem of correct memory management. The risk of software errors decreases and development time is reduced. Garbage collection techniques suitable for interactive and soft real-time systems exist, but few approaches are suitable for systems with hard real-time requirements, such as control systems (embedded systems). One part of the problem is solved by incremental garbage collection algorithms, which have been presented before. We focus on the scheduling problem which forms the second part of the problem, i.e. how the work of a garbage collector should be scheduled in order

Automatic storage management, or garbage collection, is a feature usually associated with languages oriented toward ‘‘symbolic processing,’’ such as Lisp or Prolog; it is seldom associated with ‘‘systems’’ languages, such as C and C++. This report surveys techniques for performing garbage collection for languages such as C and C++, and presents an implementation of a concurrent copying collector for C++. The report includes performance measurements on both a uniprocessor and a multiprocessor.

We describe a memory management toolkit for language implementors. It offers efficient and flexible generation scavenging garbage collection. In addition to providing a core of languageindependent algorithms and data structures, the toolkit includes auxiliary components that ease implementation of garbage collection for programming languages. We have detailed designs for Smalltalk and Modula-3 and are confident the toolkit can be used with a wide variety of languages. The toolkit approach is itself novel, and our design includes a number of additional innovations in flexibility, efficiency, accuracy, and cooperation between the compiler and the collector. This project is supported by National Science Foundation Grant CCR-8658074, and by Digital Equipment Corporation, GTE Laboratories, and Apple Computer. 1 Introduction As part of an ongoing effort to implement Persistent Smalltalk and Persistent Modula-3, we have designed a high performance garbage collector toolkit that can be us...

Modern generational garbage collectors look for garbage among the young objects, because they have high mortality; however, these objects include the very youngest objects, which clearly are still live. We introduce new garbage collection algorithms, called age-based, some of which postpone consideration of the youngest objects. Collecting less than the whole heap requires write barrier mechanisms to track pointers into the collected region. We describe here a new, efficient write barrier implementation that works for age-based and traditional generational collectors. To compare several collectors, their configurations, and program behavior, we use an accurate simulator that models all heap objects and the pointers among them, but does not model cache or other memory effects. For object-oriented languages, our results demonstrate that an older-first collector, which collects older objects before the youngest ones, copies on average much less data than generational collectors. Our resul...

Generational garbage collectors are able to achieve very small pause times by concentrating on the youngest (most recently allocated) objects when collecting, since objects have been observed to die young in many systems. Generational collectors must keep track of all pointers from older to younger generations, by "monitoring " all stores into the heap. This write barrier has been implemented in a number of ways, varying essentially in the granularity of the information observed and stored. Here we examine a range of write barrier implementations and evaluate their relative performance within a generation scavenging garbage collector for Smalltalk. 1 Introduction Generational collectors achieve short collection pause times partly because they separate heap-allocated objects into two or more generations and do not process all generations during each collection. Empirical studies have shown that in many programs most objects die young, so separating objects by age and focusing collecti...