# draft of GC workshop report

Here's a draft of the workshop report, which will go in Real Soon Now
for inclusion in the Addendum to the OOPSLA proceedings.

Please have a look at it, especially your part, and see if it looks OK.
(Don't worry about formatting --- that will change.)

If you'd rather NOT have your address appear in the report, just let
us know.

Report follows in latex .tex format.  Even if you don't do latex, you
should be able to read it.

Thanks,

Paul

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\title{The 1991 Workshop on Garbage Collection in Object-Oriented Systems}

\author{Paul R. Wilson\thanks{Paul R. Wilson,
Dept. of Computer Sciences,
University of Texas,
Taylor Hall 2.124, Austin, Texas 78712-1188
(internet: wilson@cs.utexas.edu).}\\
University of Texas at Austin
\and
Barry Hayes\thanks{Barry Hayes,
Xerox PARC,
Room 2113 CSL,
Palo Alto, California 94304
(internet: bhayes@neon.stanford.edu).}\\
Stanford University and Xerox PARC}

\date{}

\begin{document}

\maketitle

{\em  \ldots we have the ability to handle garbage more
intelligently, using both emerging technologies and new and
improved versions of older solutions\ldots}
\\ ---Mariette DiChristina, How we can win the war against garbage,''
{\em Popular Science}, October 1990, p. 57.

\section{Overview}

This workshop consisted primarily of 10-minute presentations
researchers and software developers, interspersed with a few
20-minute presentations and a panel discussion on
conservative vs. accurate approaches to garbage collection.

While the format was partly due to our indecisiveness in
selecting the best'' papers for presentation, it also reflected
the generally good quality of accepted papers and the high standard
of background knowledge among the participants.  We got several
comments to the effect that the 10-minute slots were just
right,'' because nearly all of the attendees had sufficient
background that little preparatory explanation was needed---speakers
could quickly get to the novel and interesting points of their
papers.\footnote{We also adjusted the ordering of the talks
to present related topics together, and many of the presenters
conferred to make sure their presentations were not too
redundant.  In fact, some people thought this made some of the
20-minute slots a shade too long.}  Future workshop organizers
might want to take the success of this format into account.

Given the pleasant result of this self-organizing anarchy, we
present the workshop report in much the same spirit---we are mostly
presenting the abstracts of the accepted papers and panelists'
positions.  The ordering below is roughly the one in which
papers were presented.  (A few papers weren't actually presented,
but we include their abstracts here.)

Full versions of most of the presented papers are available in
PostScript form via anonymous internet ftp from cs.utexas.edu,
in the directory pub/garbage/GC91.  Papers from the first workshop
(organized by Eric Jul and Niels-Christian Juul) are in
pub/garbage/GC90.  We are also compiling a bibliography which
will be made available there.\footnote{A similar repository,
maintained by Niels-Christian Juul, is on ftp.diku.dk for
European access.}

We would like to thank all of the participants in the workshop,
including our special invited guests David Chase (of Sun)
and Andrew Koenig (of AT\&T), and panelists Joel Bartlett,
Hans Boehm, and Eliot Moss.

\section{Morning Session Abstracts}

\subsection*{On Multi-Threaded List Processing and Garbage Collection}

\sloppypar{
Wolfgang Keuchlin and Nicholas Nevin,
Dept of Computer and Information Science, The Ohio State University,
Columbus, Ohio 43210-1277, U.S.A.
\{keuchlin,nevin\}@cis.ohio-state.edu.
}

We discuss the problem of parallel list-processing based on {\em threads
of control}, such as Mach's C Threads.  Our main insigh is that the
heap memory layout and garbage collection technique which is quite
different from existing Lisp and Prolog Systems.

\subsection*{A High-Performance Architecture for Real-Time Garbage Collection}

\sloppypar{
Kelvin Nilsen, Dept. of Computer Science, Iowa State University,
Ames, IA  50011 (515) 294-2259
(kelvin@cs.iastate.edu uunet!atanasoff!kelvin)
}

Hardware-assisted garbage collection offers the potential of high
average-case allocation rates and memory bandwidth, with very low
worst-case allocation, fetch, and store times.  This paper describes
an architecture that allows memory fetch and store operations to
execute, on the average, nearly as fast as traditional memory.  The
architecture is high-performance in that it includes support for
caching of garbage-collected memory cells.  The architecture is
real-time in that the worst-case time required for a memory fetch or
store is approximately six traditional memory cycles, and the time
required to allocate an object is bounded by a small constant times the
size of the object.  A prototype of the proposed architecture has been
successfully simulated.  Continuing research focuses on measuring the

\subsection*{How Real is Real-Time'' GC?}

\sloppypar{
P. T. Withington, Symbolics, Inc.,  Eight New England Executive Park,
East Burlington, MA 01803, U.S.A.
(ptw@Jasper.SCRC.Symbolics.COM)
}

A group at Symbolics is developing a Lisp runtime kernel, derived from
its Genera(R) operating system, to support real-time control
applications.  The first candidate application has strict response-time
requirements (so strict that it does not permit the use of paged virtual
memory).  Traditionally, Lisp's automatic storage-management mechanism
has made it unsuitable to real-time systems of this nature.  A number of
garbage collector designs and implementations exist (including the
Genera garbage collector) that purport to be real-time'', but which
actually have only mitigated the impact of garbage collection
sufficiently that it usually goes unnoticed by humans.  Unfortunately,
electro-mechanical systems are not so forgiving.  This paper examines
the limitations of existing real-time garbage collectors and describes
the avenues that we are exploring in our work to develop a CLOS-based
garbage collector that can meet the real-time requirements of real
real-time systems.

\subsection*{Automatic Storage Management for Systems with Real Time
Constraints}

Stephen Engelstad (marv1@iexist.att.com) and James E. Vandendorpe,
AT\&T Bell Laboratories, Naperville, IL 60566

A garbage collector programmed in C reclaims objects by executing during the
allocation of new objects.  After a dynamically scheduled number of object
allocations the application is delayed while lost resources are recovered.
The average delay is 6 ms on a Sun3 and 2 ms on a Sun4 with a worst case
delay of 10 ms on both.  To achieve these results we refined the generational
implemented within the Calico programming system.

\subsection*{Comparing Two Garbage Collectors}

Douglas Johnson, Texas Instruments MS 369,  P.O. Box 655621,
Dallas, Texas 75265 (johnson@ti.com)

Based on an experiment comparing two garbage collection algorithms on
a large, long-running Lisp program, we find that a simple, two generation
stop-and-copy colector is equal or superior to a complex, multigenerational
incremental collector in every measured area except paging performance
in limited physical memory sizes.  The major conclusion from this experiment
is that it is difficult to justify the cost of complex incremental collectors
unless they are used to optimize paging performance via object reordering.
However, there are interesting classes of programs that can get significant
benefit from such optimization.

\subsection*{Simple GC-Safe Compilation}

\sloppypar{
Hans-Juergen Boehm, Xerox PARC, 3333 Coyote Hill Road, Palo Alto,
California 94304, USA (boehm@xerox.com)
}

We propose that C compilers (and translators from future standard intermediate
languages) optionally produce code that guarantees safety in the presence
of a conservative garbage collector.  It is argued that this is
essential, and that it should have negligible impact on object code
performance.  It is easy to specify what is required of the compiler.
The necessary changes to the compiler are independent of the original
source language, be it C itself, or another language that is compiled to C.

\subsection*{The UMass Language Independent Garbage Collector Toolkit}

\sloppypar{
J. Eliot B. Moss, Department of Computer Science,
University of Massachussetts, Amherst, MA 01003
(moss@cs.umass.edu)
}

At the OOPSLA/ECOOP '90 workshop on garbage collection Rick Hudson and Amer
Diwan presented a scheme for flexible scavenging based on a varying number of
fixed size generations. We have since developed a new scheme that we believe
is even more flexible. The sizes of generations can vary, as well as the
number of generations, and we provide very efficient age-based promotion using
no age counters or high water mark tests. In addition, we have implemented the
scheme in such a way as to separate language specific parts (e.g., details of
locating roots for a scavenge) from language independent components. The
result is a toolkit that substantially reduces the effort in supporting
scavenging in new language implementations.

\subsection*{Stack Tracing In a Statically Typed Language}

\sloppypar{
Amer Diwan, Object Oriented Systems Laboratory,
Department of Computer Science,
University of Massachussetts (diwan@cs.umass.edu)
}

Statically-typed languages such as Modula-3 provide many opportunities to
mitigate the costs of garbage collection.  Compiler generated tables can
assist the collector in locating the root pointers and in updating them when
objects are moved.  This obviates the need for run-time tags in the stack and
offers substantial performance improvements.

In this paper, we describe some key issues that need to be addressed before
we have an efficient stack tracing scheme.  We also describe our solutions to
these problems in the context of Modula-3.

\subsection*{Main Memory Management for Persistence}

Anthony Hosking, Object Oriented Systems Laboratory,
Department of Computer and Information Science,
University of Massachussetts, Amherst MA 01003
(hosking@cs.umass.edu)

Reachability-based persistence imposes new requirements for main memory
management in general, and garbage collection in particular. After a brief
introduction to the characteristics and requirements of reachability-based
persistence, we present the design of a run-time storage manager for
Persistent Smalltalk and Persistent Modula-3, which allows the reclamation of
storage from both temporary objects and buffered persistent objects.

\subsection*{Finalization in a Garbage Collected World}

Richard L. Hudson, Research Associate,
University Computing Services,
University of Massachusetts at Amherst (hudson@cs.umass.edu)

With the advent of object oriented technologies, data structures have become
more complex and the tradition of relying on programmers to explicitly
deallocate objects has become tenuous. To relieve the programmer of the
increasingly intractable problem of detecting references that have expired,
modern run-time platforms use garbage collection to help manage memory.
However, before an object can be deallocated, it is sometimes necessary to
execute a {\em finalization} routine associated with the object.  Such a
routine might include closing an open file or informing the windowing system
that a window is no longer needed.  In some languages, the only way to free
storage is to execute finalization routines that explicitly deallocate the
object.  On the other hand, garbage collection algorithms automatically detect
when objects are no longer needed.  This frees the user from having to
deallocate storage explicitly in a finalization routine, but does not address
the problem of executing finalization routines that have other
responsibilities.  In this paper, we propose semantics to extend finalization
to include garbage collected objects.  In the context of a type accurate
generational garbage collector, we describe an implementation strategy that
allows finalization to be performed concurrently with the user's threads.

\subsection*{Outwitting GC Devils:  A Hybrid Incremental Garbage Collector}

David Ungar and Frank Jackson, ParcPlace Systems, Inc., 1550 Plymouth St.,
Mountain View, CA 94043  (David.Ungar@sun.com, Jackson@parcplace.com)

No garbage collector is perfect, and it is possible to invest a
great deal of effort in a particular design of a collector before
the extent of its weaknesses become apparent.  Even large benchmarks
may fail to expose a flaw that can interfere with attaining acceptable
performance for other application programs.  Designers need to
build collectors that exhibit robust behavior in the face of a
wide variety of application program allocation and reclamation
patterns.  In order to focus on this goal, it helps to imagine
an adversary who writes application programs with the specific
purpose of confounding the garbage collector.  In fact, in developing
a collector for a commercial product, we found that this was
more than a conceptual device; users did (unwittingly) construct
some programs that exhibited peculiar behavior which caused an early
version of our collector to fail. As a result, we implemented a hybrid
collector combining Generation Scavenging, with an incremental mark-sweep
algorithm.  Its design was influenced by the desire to avoid potential
pathologies.  Users report satisfaction with the new collector. We are
waiting to see what its pathologies may be.

\subsection*{The Myth of High Object Allocation Rates}

Urs Hoelzle, Computer Systems Laboratory, Stanford University
(urs@self.stanford.edu)

Garbage collector designs are often motivated by the high allocation
rates displayed by the system for which the collector is intended;
this furious object creation rate is accepted as a given.

I argue that a promising way to reduce the GC overhead is to reduce
the amount of garbage produced, i.e. to lower the allocation rate of
the system.  Garbage prevention'' should be an integral part of any
system using garbage collection, and the potential gains of compiler
optimizations aimed at reducing the allocation rate could well
outweigh the gains achievable by just tuning the garbage collector.
Some measurements of the Self system are used to illustrate this
point.

\subsection*{Cost of Garbage Collection in the Self System}

Craig Chambers, Department of Computer Science and Engineering, FR-35,
University of Washington, Seattle, WA 98195 (chambers@cs.washington.edu)

Differences in the overhead of garbage collection for different
systems stem from differences in the language implementation
technology and in typical programming style.  Ungar reports remarkably
low overheads of 2-3\% for Generation Scavenging in Berkeley Smalltalk
and SOAR, but these Smalltalk systems had relatively unoptimized
language implementations relative to traditional languages and
fostered high object allocation and death rates relative to

Self provides a new data point in this matrix: an optimizing language
implementation combined with high object allocation and death rates.
Optimizations in the Self system both dramatically speed up normal
program execution compared to Smalltalk systems and reduce the object
allocation and death rates by optimizing away many closure creations.
We measured the overhead of garbage collection in Self on four large
benchmarks and found overheads ranging from 4\% to 27\%.  Interestingly,
store checking consumes a major fraction of this overhead.

\section{Panel Discussion:  Conservative vs. Accurate Garbage Collection}

\subsection*{Hans Boehm}

By conservative garbage collection we mean garbage collection in the presence
of values for which it is not known whether or not they are pointers.  There
are various degrees of conservative garbage collection depending on how much
pointer information is known.  For example, the layout of heap allocated
objects may be known, while stack layout may not be known.

Garbage collectors that accommodate a high degree of conservativism, i.e. that
can operate with minimal pointer location information are currently desirable
for two reasons.  First, new code that relies on garbage collection should
interoperate correctly with traditional C code.  Thus the garbage collector
must be able to understand references from C data structures.  Second, new
programming language implementations increasingly compile to C to obtain both
portability and access to machine dependent optimizers that were built with an
(often proprietary) understanding of hardware timing.  This makes it difficult
or impossible to provide data structure layout information to the collector.

Even very conservative, nonmoving garbage collectors can provide performance
that is often better than malloc/free performance, and competitive with other
kinds of collectors.  They may, on rare occasions, retain noticably more
unreachable data than other types of collectors.  But essentially no existing
garbage collector provides guarantees on what storage will be reclaimed.
Conservative garbage collectors impose some minimal requirements on code
optimizers, but these can be easily standardized, and are independent of the
original source language.

\subsection*{Joel Bartlett}

The terms accurate'' and conservative'' are an attempt to put black
and white labels on a gray scale that measures the amount of information
that the garbage collector has to work with.  People don't build
conservative collectors because they're lazy, sloppy, or have loose
morals.  They build them because they wish to provide garbage collection
in inhospitable environments.  When faced with the choice of not enough
information at runtime, or a GC unsafe'' language, one can abandon the
implementation, or use conservative techniques.  As I'm interested to
bringing garbage collection to more users, I do the later.

At WRL, we have used mostly-copying'' garbage collection to build an
efficient, portable Scheme-to-C compiler, Scheme\verb$->$C, and over
40,000 lines of CAD tools in C++.  In spite of the fact that it's easy
to demonstrate how conservative techniques can cause memory leaks, our
experience is that this is a rare occurrence in production programs.
Challenges for the future include convincing others that conservative
collection is preferable to bare-handed allocation and that code generators
should preserve the minimal invariants required by conservative collectors.

\subsection*{Eliot Moss}

%XXXX I think it should be pointed out that fully conservative mark-sweep
%XXXX GC's are conservative about pointers between heap objects as well
%XXXX as roots.
In order to understand my position on garbage collection strategies,
it is useful to see my taxonomy of the strategies. There are {\em ambiguous
roots} collectors (frequently called {\em conservative} because they
must {\em assume} a quantity is a pointer unless proven otherwise) and
{\em unambiguous} ones.  Ambiguous roots collectors are simple in the
absence of certain compiler optimizations, but making language
implementation {\em gc-safe} requires additional analysis in the compiler,
and will sometimes affect the object code (e.g., to retain base pointers
that wuld otherwise be considered dead).  Unambiguous roots collectors need
at least to know the types of most things, hence they are predicated on
{\em type accuracy}. For good performance, one can avoid tagging pointers
at run-time, at the expense of additional compiler work and space consumed
by tables. The compiler's analysis can be increasingly refined, striving
towards perfect {\em precision} (knowing exactly what is garbage and what
is not), which is undecidable.

My main point is that once you go to the effort of enhancing a compiler to
make its output gc-safe, you might as well go the extra mile of supporting
type accuracy. The improved accuracy avoids the accidental retention of space
that sometimes happens with ambiguous roots collectors, but more importantly,
type accuracy allows objects to move, and thus allows a wider range of gc
strategies, especially compaction. This is important in our work on persistent
programming languages, but my position is that it is also important in the
absence of persistence. Thus, I hope that conservative'' collectors will
only be a stop-gap until better techniques are deployed. (Note: we have indeed
developed the necessary compiler technology for our Modula-3 implementation.)

In my view, these are the {\em issues}, whether or not you agree with my
position:

\begin{itemize}
\item{Accuracy: How much garbage does the collector fail to
reclaim?}

\item{Optimization: Which compiler optimizations may cause the
collector to fail?}

\item{Ambiguity: Can objects move? Can the collector and run-time distinguish
pointers from non-pointers?}

\item{Effort: How much implementation effort is required?}
\end{itemize}

The only issue on which type accurate collectors are not strong is
implementation effort, and we argued above that the effort required is
only a little more than that needed for gc-safety, so type accuracy should
be our goal.

\subsection*{David Chase}

There is an interaction between optimizing compilers and garbage
collectors---good optimizers can do an arbitrarily amazing job of
hiding pointers (stored in registers, not in the heap) from the garbage
collector.  There is no part of the C or Fortran or C++ specifications
that tells compilers not to do this, and market pressure encourages
compilers to do this.  The RS/6000 compilers are known to do this today,
and I observed Sun's f77 compiler into this in 1988.  Do understand that
these are not interior'' pointers---these are typically encodings of the
form p - K'' (to which K is added to reconsitute the p'') or p2 - p1''
(to which p1'' is added to reconstitute p2'').

Bartlett's conservative collector goes a long way in solving this problem,
but to be sure, some optimizer support is also required.  For languages
that interoperate with C, one must also beware of routines in the C library
that return derived'' (interior) pointers based on their parameters.

%XXXX this doesn't really belong here, as part of the conservative vs.
%XXXX accurate debate... maybe we should have a discussion section
%XXXX that includes Ungar's comment that conservative mark-sweep
%XXXX is bad because it doesn't compact, my response (that it's probably
%XXXX not as important as you might think because the real problem is
%XXXX deferred reuse of memory, no matter how you slice it)
%XXXX and so on.  Chase responded to that, I think... I'd pointed out
%XXXX that copying gc's give you nice linear allocation, but even that
%XXXX may happen with a good mark-sweep that uses bitmaps for allocation
%XXXX and can usually find significant runs of free memory due to locality
%XXXX in object creations and deaths, cf. Hayes 91...

On another note, I think that prefetch'' instructions for some forms of
cache management (see the i860 pipelined load instructions, or recent
papers in ASPLOS) may have interesting uses in garbage collectors, and
should be investigated.  One reason this is a good hardware feature to
exploit is that it is useful for Fortran, and thus will probably become
widely available (as opposed to hardware features designed to support
less-popular languages).

\section{Afternoon Session Abstracts}

\subsection*{Standardizing Memory Management Descriptions}

Alan M. Durham and Ralph Johnson,
Department of Computer Science, University of Illinois,
Urbana-Champaign (durham@cs.uiuc.edu)

This position paper describes my research on describing memory management
to an optimizing compiler.  The goal is to make optimizing copilers for
languages like Smalltalk easier to retarget to new memory management
systems.

\subsection*{The Treadmill: Real-Time Garbage Collection Without
Motion Sickness}

Henry G. Baker, Nimble Computer Corporation, 16231 Meadow Ridge Way,
Encino, CA 91436 (818) 501-4956,  (818) 986-1360 FAX.

A simple real-time garbage collection algorithm is presented which
does not copy, thereby eavoiding some of the problems caused by
the asynchronous motion of objects.  This in-place treadmill''
garbage collection scheme has approximately the same complexity
as other non-moving garbage collectors, thus making it usable
in a high-level language implementation where some pointers
cannot be traced.  The treadmill is currently being used in a

\subsection*{Garbage Collecting an Object-Oriented Operating System Kernel}

\sloppypar{
Vincent F. Russo, Department of Computer Science, Purdue University,
West Lafayette, IN 47907 (russo@cs.purdue.edu)
}

As part of the {\em Renaissance} project at Purdue University, we are
investigating the feasibility of garbage collecting an actively running
operating system kernel.  In this paper, we discuss the algorithm we have
adapted to our needs, along with the techiques we use to support garbage
collection in C++ (the object-oriented language in which we have coded
our system).

\subsection*{Towards User (Application) Language-Level Garbage Collection in
Object-Oriented Concurrent Languages}

\sloppypar{
Masahiro Yasugi and Akinori Yonezawa, Department of Information Science,
University of Tokyo (yonezawa@is.s.u-tokyo.ac.jp)
}

We are implementing object-oriented concurrent languages on
highly-parallel computers without shared memory.Our approach to GC is
to translate a user program (which is written in an object-oriented
concurrent language) into the user program with GC which is also written
in the object-oriented concurrent language. In this approach, the runtime
routines for GC is not required when we implement language systems. We
will present an example of GC schemes aimed at user-language-level general
GC. To illustrate the example, we will also give a general definition of
garbage in terms of groups.

\subsection*{Parallel Conservative Garbage Collection with Fast Object
Allocation}

\sloppypar{
Shinichi Furusou, Satoshi Matsuoka, and Akinori Yonezawa,
Department of Information Science, The University of Tokyo,
7-3-1, Hongo, Bunkyo-ku, Tokyo, 113 JAPAN;
Phone +81-3-3812-2111 ext. 4108
(furuso@is.s.u-tokyo.ac.jp, matsu@is.s.u-tokyo.ac.jp,
yonezawa@is.s.u-tokyo.ac.jp)
}

Conservative Garbage Collection (GC) algorithm provides garbage
collection independent of programming languages and applications, but
is difficult to extend naively into a concurrent algorithm, where
allocation speed of up to one million objects per second per thread is
required. Our parallel conservative GC is a parallel and real-time
conservative GC algorithm, whose allocation and collection can be done
almost totally in parallel without the need for synchronization or
mutual exclusion. Results derived from proof of correctness of the
algorithm allows object allocation to be done totally distributed and
parallel, so that the allocation cost is estimated to be as little as
13--15 instructions per object allocation, including the overhead of
(rare) synchronization. The preliminary version of our algorithm is
already running on a 4-processor LUNA-88K with Mach 2.5. Our algorithm
relies on the availability of virtual memory primitives to the user in
order to maintain the necessary invariants of the collector.

\subsection*{A System Model of Memory Management}

\sloppypar{
Robert MacLachlan, Dept. of Computer Science, Carnegie-Mellon University
(Rob.MacLachlan@cs.cmu.edu)
}

As both memory systems and memory managers become more complex, it is
increasingly important to develop a unified framework for examining the
interaction between memory system hardware and memory management software.
This paper explores one possible connection.

\subsection*{Garbage Collection in C++}

Paulo Ferriera, INESC/IST,
R. Alves Redol $n^{o}$ 9, $6^{o}$, 1000 Lisboa, PORTUGAL;
Phone: (351) 1.3155150, fax: (351) 1.525843, (pjpf@sabrina.inesc.pt)

This paper describes the problems and solutions found when developing a
library providing garbage collection for C++ programs.  Not only objects
are reclaimed, but also non-object memory which is usually allocated
with the \verb+malloc()+ call.  In order to reclaim non-object
memory, an incremental mark-and-sweep algorithm is provided.  The
reclamation of ojbects can be done by the same incremental mark and
sweep, or a multigenerational copy algorithm which drastically reduces
the time of a global collection.  Pointers to the interior of objects
are fully supported.  The programmer only has to use a few simple
macros in order to have garbage collection in his program.  He can
also specify which objects are to be garbage-collected on a class-by-class
basis.  Thus, within an application there might coexist objects that are
garbage collected along with others that are not.  A preprocessor is
being developed to release the programmer from using these macros.

\subsection*{Generational Garbage Collection for C-Based Object-Oriented
Languages}

Kazushi Kuse and Tsutomu Kamimura,
IBM Japan, Tokyo Research Laboratory,
5-19, Sanban-cho, Choyoda-ku, Tokyo

The approach we have taken here is to separate memory management of
objects from that of standard C data.  We provide automatic reclamation
of objects, but do not reclaim C data.  For this purpose, we impose
restrictions on the use of objects, so garbage collection of objects
can be performed safely.  Such restrictions are basically to make typing
of objects strong, to make run-time type information available, to disallow
a network of pointers in the heap as well as the stack, and to disallow
pointers to the middle of objects.

\subsection*{DGD: Doom, Gloom and Despair---Distributed Garbage Detection

Peter Dickman, Cambridge University and INRIA (Peter.Dickman@cl.cam.ac.uk)

The talk will introduce some of the main problems that arise in Distributed
Garbage Detection. A variety of techniques will be presented, together with
the problems that they are intended to solve and those that defeat them. This
survey will motivate the use of hybrid mechanisms, for example the one that
David will present immediately afterwards. Variants on reference counting,
the problems with tracing techniques and the use of non-conservative ageing
and refresh schemes will all be discussed.

The various ways in which DGD's can be analysed will be mentioned, in
particular the various issues in counting messages and analysing space
requirements will be presented.  Finally, scaling is introduced, with some
guidelines on what to look for in a scalable garbage detector.

\subsection*{Local and Global Distributed Garbage Collection}

\sloppypar{
Stephen C. Crawley, Defence Science and Technology Organisation,
PO Box 1600, Salisbury 5107, Australia
(sxc@itd.dsto.oz.au)
}

This paper describes three garbage collection algorithms in a distributed
object system.  The local algorithm collects garbage on a single machine
independent of others.  The extended local algorithm funs asynchronously
on each machine collecting local and distributed garbage.  The global
algorithm provides faster collection of all distributed garbage including
cycles.  All of the algorithms will work when parts of the object system
are unavailable.

\subsection*{Distributed Garbage Collector as an Operating System Component}

David Plainfosse' and Marc Shapiro, INRIA, BP105, 78153 Rocquencourt Cedex,
France (dp@sor.inria.fr)

Recent development of object-oriented technology has sparked interest
in low-level support systems for user-defined objects.  A number of
operating systems and database systems offer such support.  Until
recently, garbage collection has often been judged to be too language-
dependent, too complex, and too costly for general-purpose systems.
In contrast, we think that operating systems should be designed and
implemented to offer support for garbage collection.  Our approach
is to provide a generic service for distributed garbage collection,
building upon existing, language-dependent, local garbage collectors.
We have designed an efficient fault-tolerant distributed garbage
collection protocol, and we are currently planning to integrate
it in the Soul nucleus, a general-purpose object-oriented
sytsem layered above the Chorus micro-kernel.  In the paper, we
focus on the protocol itself and especially on distribution and
reliablity aspects.

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