ABSTRACT: In previous heap storage systems, the cost of creating objects and garbage collection is independent of the lifetime of the object. Since objects with short lifetimes account for a large portion of storage use, it is worth optimizing a garbage collector to reclaim storage for these objects more quickly. The garbage collector should spend proportionately less effort reclaiming objects with longer lifetimes. We present a garbage collection algorithm that (1) makes storage for short-lived objects cheaper than storage for long-lived objects, (2) that operates in real-time--object creation and access times are bounded, (3) increases locality of reference, for better virtual memory performance, (4) works well with multiple processors and a large address space. 1.

We present a method, adapted to polymorphically typed functional languages, to detect and collect more garbage than existing GCs. It can be applied to strict or lazy higher order languages and to several garbage collection schemes. Our GC exploits the information on utility of arguments provided by polymorphic types of functions. It is able to detect garbage that is still referenced from the stack and may collect useless parts of otherwise useful data structures. We show how to partially collect shared data structures and to extend the type system to infer more precise information. We also present how this technique can plug several common forms of space leaks.

This paper describes a new language feature that allows dynamically allocated objects to be saved from deallocation by an automatic storage management system so that clean-up or other actions can be performed using the data stored within the objects. The program has full control over the timing of clean-up actions, which eliminates several potential problems and often eliminates the need for critical sections in code that interacts with clean-up actions. Our implementation is "generation-friendly" in the sense that the additional overhead within a generation-based garbage collector is proportional to the work already done there, and the overhead within the mutator is proportional to the number of clean-up actions actually performed. 1 Introduction Many programming systems, such as Scheme, Common Lisp, ML, and Prolog, support dynamic allocation and automatic deallocation of objects. Within these systems, some form of storage manager takes responsibility for handling both requests to al...

. A purely functional file system has been built on top of pure Scheme. It provides persistent structures and massive storage expected of file systems, without explicit side-effects like read and write. The file system becomes an additional, lazy argument to programs that would read from it, and an additional result from functions that would alter it. Functional programming on lazy structures replaces in-place side-effects with a significant storage management problem, handled by conjoining the heap to the file system. A hardware implementation of reference counting is extended out to manage sectors, as well as the primary heap. Backing it is a garbage collector of heap and of disk (i.e. UNIX's fsck), needed only at reboot. CR categories and Subject Descriptors: D.4.2 [Storage Management]: Storage hierarchies; D.1.1 [Applicative (Functional) Programming]; E.2 [Data Storage Representations]: Linked representations; H.0 [Information Systems]. General Term: Design. Additional Key Wor...

In previous heap storage systems, the cost of creating objects and garbage collection is independent of the lifetime of the object. Since objects with short lifetimes account for a large portion of storage use, it is worth optimizing a garbage collector to reclaim storage for these objects more quickly. The garbage collector should spend proportionately less effort reclaiming objects with longer lifetimes. We present a garbage collection algorithm that (1) makes storage for short-lived objects cheaper than storage for long-lived objects, (2) that operates in real-time--object creation and access times are bounded, (3) increases locality of reference, for better virtual memory performance, (4) works well with multiple processors and a large address space. 1.