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Versions: 00 01 02 03                                                   
IETF media feature registration WG                        Graham Klyne
Internet draft                              Integralis Technology Ltd.
                                                         11 March 1998
                                            Expires: 11 September 1998


             An algebra for describing media feature sets
              <draft-ietf-conneg-feature-algebra-00.txt>

Status of this memo

  This document is an Internet-Draft.  Internet-Drafts are working
  documents of the Internet Engineering Task Force (IETF), its areas,
  and its working groups.  Note that other groups may also distribute
  working documents as Internet-Drafts.

  Internet-Drafts are draft documents valid for a maximum of six
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  To learn the current status of any Internet-Draft, please check the
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  Coast), or ftp.isi.edu (US West Coast).

  Copyright (C) 1998, The Internet Society

Abstract

  A number of Internet application protocols have a need to provide
  content negotiation for the resources with which they interact [1].
  A framework for such negotiation is described in [2].  Part of this
  framework is a way to describe the range of media features which
  can be handled by the sender, recipient or document transmission
  format of a message.  A format for a vocabulary of individual media
  features and procedures for registering media features are
  presented in [3].

  This document describes an algebra which can be used to define
  feature sets which are formed from combinations and relations
  involving individual media features.  Such feature sets are used to
  describe the media feature handling capabilities of message
  senders, recipients and file formats. This document does not set
  out to specify a syntax for defining feature sets.








Klyne                                                         [Page 1]


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An algebra for describing media feature sets


Table of contents

1. Introduction.............................................2
  1.1 Structure of this document ...........................3
  1.2 Discussion of this document ..........................3
  1.3 Ammendment history ...................................4
  1.4 Unfinished business ..................................4
2. Terminology and definitions..............................4
3. Media feature values.....................................5
  3.1 Complexity of feature algebra ........................5
  3.2 Sufficiency of simple types ..........................6
     3.2.1 Unstructured data types..........................6
     3.2.2 Cartesian product................................6
     3.2.3 Disciminated union...............................6
     3.2.4 Array............................................7
     3.2.5 Powerset.........................................7
     3.2.6 Sequence.........................................8
4. Feature set predicates...................................8
  4.1 An algebra for data file format selection ............9
     4.1.1 Describing file format features..................9
       4.1.1.1 Feature ranges                               10
       4.1.1.2 Feature combinations                         11
     4.1.2 Content, sender and recipient capabilities.......12
  4.2 Conclusion and proposal ..............................12
5. Other issues.............................................13
  5.1 Some thoughts on describing preferences ..............13
6. Security considerations..................................14
7. Copyright................................................14
8. Acknowledgements.........................................15
9. References...............................................15
10. Author's address........................................16



1. Introduction

  A number of Internet application protocols have a need to provide
  content negotiation for the resources with which they interact [1].
  A framework for such negotiation is described in [2].  A part of
  this framework is a way to describe the range of media features
  which can be handled by the sender, recipient or document
  transmission format of a message.

  Descriptions of media feature capabilities need to be based upon
  some underlying vocabulary of individual media features. A format
  for such a vocabulary and procedures for registering media features
  are presented in [3].








Klyne                                                         [Page 2]


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An algebra for describing media feature sets


  This document defines an algebra which can be used to describe
  feature sets which are formed from combinations and relations
  involving individual media features.  Such feature sets are used to
  describe the media handling capabilities of message senders,
  recipients and file formats.

  The feature set algebra is built around the principle of using
  feature set predicates as mathematical relations which define
  constraints on feature handling capabilities.  The idea is that the
  same form of feature set expression can be used to describe sender,
  receiver and file format capabilities.  This has been loosely
  modelled on the way that the Prolog programming language uses Horn
  Clauses to describe a set of result values.

  This document does not attempt to describe a concrete syntax for
  the algebra.  Examples are given using notation drawn from the C
  and Prolog programming languages.

1.1 Structure of this document

  The main part of this draft addresses four main areas:

  Section 2 introduces and references some terms which are used with
  special meaning.

  Section 3 discusses constraints on the data types allowed for
  individual media feature values.

  Section 4 introduces and describes the algebra used to construct
  feature set descriptions with expressions containing media
  features.

  Section 5 introduces other related issues which are not covered by
  the feature set algebra.

1.2 Discussion of this document

  Discussion of this document should take place on the content
  negotiation and media feature reagistration mailing list hosted by
  the Internet Mail Consortium (IMC):

  Please send comments regarding this document to:

      ietf-medfree@imc.org

  To subscribe to this list, send a message with the body 'subscribe'
  to "ietf-medfree-request@imc.org".








Klyne                                                         [Page 3]


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An algebra for describing media feature sets


  To see what has gone on before you subscribed, please see the
  mailing list archive at:

      http://www.imc.org/ietf-medfree/

1.3 Ammendment history

  00a       11-Mar-1998
            Document initially created.

1.4 Unfinished business

  .  Array values: are they needed? (section 3.2.4)

  .  Feature set predicates: clean up description

  .  Other issues: are there more?

  .  Security considerations: are there any?


2. Terminology and definitions

  Feature Collection
            is a collection of different media features and
            associated values.  This might be viewed as describing a
            specific rendering of a specific instance of a document
            or resource by a specific recipient.

  Feature Set
            is a set of zero, one or more feature collections.

  Feature set predicate
            A function of an arbitrary feature set value which
            returns a Boolean result.  A TRUE result is taken to mean
            that the corresponding feature set belongs to some set of
            media feature handling capabilities defined by the
            predicate.

  Other terms used in this draft are defined in [2].















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3. Media feature values

  This document assumes that individual media feature values are
  simple atomic values:

  .  Boolean values

  .  Enumerated values

  .  Numeric values

  More complex media feature values might be accommodated, but they
  would (a) be undesirable because they would complicate the algebra,
  and (b) are not necessary.

  These statements are justified in the following sub-sections.

3.1 Complexity of feature algebra

  Statement (a) above is justified as follows: predicates constructed
  as expressions containing media feature values must ultimately
  resolve to a logical combination of feature value tests.

  A full range of simple tests for all of the data types listed above
  can be performed based on just two fundamental operations: equality
  and less-than.  All other meaningful tests can be constructed as
  predicates incorporating these two basic tests.

  For example:
     ( a != b )  iff  !( a == b )
     ( a <= b )  iff  !( b < a )
     ( a > b  )  iff   ( b < a )
     ( a >= b )  iff  !( a < b )

  If additional (composite) data types are introduced, then
  additional operators must be introduced to test their component
  parts: the addition of just one further comparison operator
  increases the number of such operators by 50%.

3.2 Sufficiency of simple types

  To justify statement (b), let us first review the range of
  composite data types that might reasonably be considered.

  In 1972, a paper "Notes on data structuring" by C. A. R. Hoare was
  published in the book "Structured Programming" [4].  This was an
  early formalization of data types used in programming languages,
  and its content has formed a sufficient basis for describing the
  data types in almost every programming language which has been






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An algebra for describing media feature sets


  developed.  This gives good grounds to believe that the type
  framework is also sufficient for media features.

  The data types covered by this paper are:

  .  Unstructured data types: (integer, real, enumeration, ordered
     enumeration, subranges).

  .  Cartesian product (e.g. C 'struct').

  .  Discriminated union (e.g. C 'union').

  .  Array.

  .  Powerset (e.g. Pascal 'SET OF').

  .  Sequence (e.g. C string, Pascal 'FILE OF').

  To demonstrate sufficiency of simple types for media features we
  must show that the feature-set defining properties of these
  composite types can be captured using predeicates on the simple
  simple types described previously.

3.2.1 Unstructured data types

  Note that the unstructured data types noted correspond closely to,
  and can be represented by the proposed simple value types for media
  features.

3.2.2 Cartesian product

  A cartesian product value (e.g. resolution=[x,y]) is easily
  captured as a collection of two or more separately named media
  features (e.g. x-resolution=x, y-resolution=y).

3.2.3 Disciminated union

  A discriminated union value is an either/or type of choice. For
  example, a given workstation might be able to display 16K colours
  at 1024x768 resolution, OR 256 colours at 1280x1024 resolution.

  These possibilities are captured by a logical-OR of predicates:
     ( ( x-resolution <= 1024 ) &&
       ( y-resolution <= 768  ) &&
       ( colours <= 16384     ) ) ||
     ( ( x-resolution <= 1280 ) &&
       ( y-resolution <= 1024 ) &&
       ( colours <= 256       ) )







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3.2.4 Array

  An array represents a mapping from one data type to another.  For
  example, the availability of pens in a pen plotter might be
  represented by an array which maps a pen number to a colour.

  If the array index which forms the basis for defining a feature set
  is assumed to be a constant, then each member can be designated by
  a feature name which incorporates the index value.  For example:
  Pen-1=black, pen-2=red, etc.

  Another example where an array might describe a media feature is a
  colour pallette: an array is used to associate a colour value (in
  terms of RGB or some other colour model) with a colour index value.
  In this case is is possible to envisage a requirement for a
  particular colour to be loaded in the pallette without any
  knowledge of the index which maps to it.

  In this case, the colour might be treated as a named Boolean
  attribute: if TRUE then that colour is deemed to be available in
  the pallette

  Feature selection based on a variable array index is more
  difficult, but it is believed that this is not a required
  capability for media selection.

  [[I cannot think of any example of feature selection which involves
  a variable index into an array. If such a feature is presented, an
  array type could be added to the set of allowable media feature
  types, and an array selection operator added to the algebra.]]

3.2.5 Powerset

  A powerset is a collection of zero, one or more values from some
  base set of values.  A colour pallette may be viewed as a powerset
  of colour values, or the fonts available in a printer as a powerset
  of all available fonts.

  A powerset is very easily represented by a separate Boolean-values
  feature for each member of the base set.  The value TRUE indicates
  that the corresonding value is a member of the powerset value.

3.2.6 Sequence

  A sequence is a list of values from some base set of values, which
  are accessed sequentially.

  A sequence can be modelled by an array if one assumes integer index
  values starting at (say) 1 and incrementing by 1 for each






Klyne                                                         [Page 7]


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An algebra for describing media feature sets


  successive element of the sequence.  Other variants of a sequence
  can be similarly modelled by an array.

  Thus, the considerations described above relating to array values
  can be considered as also applying (in part) to sequence values.
  That is, if arrays are deemed to be adequately handled, then
  sequence values too can be handled.


4. Feature set predicates

  [[This section may be incomplete and is certainly not polished.  It
  consists mainly of a reproduction of the proposals previously
  posted as messages to the 'conneg' mailing list]]

  A model for data file selection based on relational set definition
  and selection from the resulting set, using a subset of the Prolog
  programming language [5] as a descriptive notation for this
  purpose.

       NOTE: The use of Prolog as a syntax for feature
       description is NOT being proposed;  rather, the Prolog-
       like notation is used to develop the semantics of an
       algebra.  Once the semantics have been developed, they
       can be mapped to some convenient syntax.

  For the purposes of developing this algebra, examples are drawn
  from the media features described in <draft-masinter-media-
  features-02.txt> [6], which in summary are:

     pix-x=n      (Image size, in pixels)
     pix-y=m

     res-x=n      (Image resolution, pixels per inch)
     res-y=m

     UA-media= screen|stationary|transparency|envelope|
               continuous-long
     papersize= na-letter|iso-A4|iso-B4|iso-A3|na-legal

     color=n      (Colour depth in bits)
     grey=n       (Grey scale depth in bits)

4.1 An algebra for data file format selection

  The basic idea proposed here is that a feature capability of the
  original content, sender, data file format or recipient is
  represented as a predicate of a feature set.  Under universal
  quantification (i.e. selecting all possible values that satisfy
  it), a predicate indicates a range of feature sets).





Klyne                                                         [Page 8]


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  This idea is inherent in Prolog clause notation, which is used in
  the example below to describe a predicate
  'acceptable_file_format(File)' which yields a set of possible file
  transfer formats using other predicates which indicate the file
  formats available to the sender and feature capabilities of the
  file format, original content,

     acceptable_file_format(File) :-
       sender_available_file_format(File),
       match_format(File).

     match_format(File) :-
       pix_x(File,Px), content_pix_x(Px), recipient_pix_x(Px),
       pix_y(File,Py), content_pix_x(Py), recipient_pix_y(Py),
       res_x(File,Rx), content_res_x(Rx), recipient_res_x(Rx),
       res_y(File,Ry), content_res_y(Ry), recipient_res_y(Ry),
       colour(File,C), content_colour(C), recipient_colour(C),
       grey(File,G),   content_grey(G),  recipient_grey(G),
       ua_media(File,M),
          content_ua_media(M),
          recipient_ua_media(M),
       papersize(File,P),
          content_papersize(P),
          recipient_papersize(P).

  Essentially, this selects a set of file transfer formats from those
  available ('sender_available_file_format'), choosing any whose
  feature capabilities have a non-empty intersection with the feature
  capabilities of the original content and the recipient.

4.1.1 Describing file format features

  The above framework suggests a file format is described by a set of
  feature values.  As an abstract theory, this works fine but for
  practical use it has a couple of problems:

  (a)  description of features with a large number of possibilities

  (b)  describing features which are supported in specific
       combinations

  A typical case of (a) would be where a feature (e.g. size of image
  in pixels) can take any value from a range.  To present and test
  each value separately is not a practical proposition, even if it
  were possible.  (A guide here as to what constitutes a practical
  approach is to make a judgement about the feasibility of writing
  the corresponding Prolog program.)

  A typical case of (b) would be where different values for certain
  features can occur only in combinations (e.g. allowable





Klyne                                                         [Page 9]


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  combinations of resolution and colour depth on a given video
  display).  If the features are treated independently as suggested
  by the framework above, all possible combinations would be allowed,
  rather than the specifically allowable combinations.

4.1.1.1 Feature ranges

  The first issue can be addressed by considering the type of value
  which can represent the allowed features of a data file format. The
  features of a specific data file are represented as values from an
  enumeration (e.g. ua_media, papersize), or a numeric values
  (integer or rational).  The description of allowable file format
  feature needs to represent all the allowable values.

  The Prolog clauses used above to describe file format features
  already allow for multiple enumerated values.  Each acts as a
  mathematical relation to select a subset of the set of file values
  allowed by the preceding predicates.

  Section 3 of this document describes proposed media feature value
  types.

  For numeric feature values, a sequence of two numbers to represent
  a closed interval is suggested, where either value may be replaced
  by an empty list to indicate no limiting value.  Thus:

     [m,n]  => { x : m <= x <= n }
     [m,[]] => { x : m <= x }
     [[],n] => { x : x <= n }

  The following Prolog would be used to describe such range matching:

     feature_match(X,[[],[]]).
     feature_match(X,[L,[]]) :- L <= X.
     feature_match(X,[[],H]) :- X <= H.
     feature_match(X,[L,H])  :- L <= X, X <= H.
     feature_match(X,X).

  (This example strectches standard Prolog, which does not support
  non-integer numbers.  The final clause allows 'feature_match' to
  deal with equality matching for the normal enumerated value case.)

4.1.1.2 Feature combinations

  Representing allowed combinations of features is trickier.  I can
  see two possible approaches:

  (a)  use additional predicates to impose relationships between
       features.






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  Thus, if x- and y- resolutions were to be constrained to square or
  semi-square aspect-ratios, the following predicates might be added
  to the feature set description:

     ( feature_match(Rx,Ry) ;
       feature_match(Rx,2*Ry) ;
       feature_match(2*Rx,Ry) ),
     feature_match(Rx,[72,600]),
     feature_match(Ry,[72,600])

  (where the last two constraints might be imposed by the 'res_x' and
  'res_y' predicates).

  Another example might be:

     ( ( feature_match(Px,640),  feature_match(Py,480) ) ;
       ( feature_match(Px,600),  feature_match(Py,800) ) ;
       ( feature_match(Px,1024), feature_match(Py,768) ) )

  This is based on the predicates 'pix_x(File,Px)', 'pix_y(File,Py)',
  'res_x(File,Rx)' and 'res_y(File,Ry)' from the initial framework
  above.)

  (b)another approach might be to allow meta-features which are
  groupings of other features.

  Applying this to the above examples would replace:

     pix_x(File,Px),
     pix_y(File,Py),
     res_x(File,Rx),
     res_y(File,Ry),

  with:

     pix(File,[Px,Py]),
     res(File,[Rx,Ry])

  where:

     pix(File,[640, 480]).
     pix(File,[800, 600]).
     pix(File,[1024,768]).
     res(File,[Rx,Ry]) :-
       feature_match(Rx,[72,600]),
       feature_match(Ry,[72,600]),
       ( feature_match(Rx,Ry) ;
         feature_match(Rx,2*Ry) ;
         feature_match(2*Rx,Ry) ).






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  On closer examination, these two options turn out to be pretty much
  the same thing:  a requirement to impose additional constraint
  predicates on a file feature set.  They differ only in where the
  predicates are applied.

  This all suggests that file format capabilities can be described by
  feature set predicates:  arbitrary logical expressions using AND,
  OR, NOT logical combining operators, and media feature value
  matching.

4.1.2 Content, sender and recipient capabilities

  It has already been suggested that these are represented as
  predicates on the feature set of a particular data file.

  Having also shown that these same predicates can represent
  constraints on feature combinations, we proceed directly to a
  proposal in which everything is represented by predicates.

4.2 Conclusion and proposal

  My conclusion is that data file features, original content
  features, sender features and recipient features (and user
  features) should all be represented as predicates.

  A key insight, which points to this conclusion, is that a
  collection of feature values can be viewed as describing a specific
  document actually rendered by a specific recipient.  The
  capabilities that we wish to describe, be they sender, file format,
  recipient or other capabilities, are sets of such feature
  collections, with the potential to ultimately render using any of
  the feature value collections in the set.

  This raises a terminology problem, because the term "feature set"
  has been used to mean a collection of specific feature values and a
  range of possible feature values.  Thus the more restricted
  definitions of "feature collection" and "feature set which appear
  in the terminology section of this document.

  Original content, data files and recipients (and users) all embody
  the potential capability to deal with a "feature set".  One of the
  aims of content negotiation is to select an available data file
  format (availability being circumscribed by the original content
  and sender capabilities) whose feature set intersection with the
  recipient feature set is non-empty.  (The further issue of
  preference being deferred for later consideration.)

  The concept of a mathematical relation as a subset defined by a
  predicate can be used to define feature sets, using universal






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  quantification (i.e. using the predicate to select from some
  notional universe of all possible feature collections).

  Thus, a common framework of predicates can be used to represent the
  feature capabilities of original content, data file formats,
  recipients and any other participating entity which may impose
  constraints on the usable feature sets.

  Within this framework, I believe it is sufficient to represent
  individual feature values as enumerated values or numeric ranges.
  The thesis in section 3 of his document, and a study of <draft-
  masinter-media-features-01.txt> [6], indicate that more complex
  media feature values can be handled by predicates.


5. Other issues

5.1 Some thoughts on describing preferences

  The general problem of describing preferences between feature sets
  is very much more complex than describing allowable feature sets.

  Before any real progress can be made, some simplifying assumptions
  are required.  At the end of the day, it is possible that any
  preference selection mechanism is at best a hint which must be
  subject to override by operator input.

  It has been suggested that numeric q-factors, as used in some HTTP
  negotiations, are misleading and are really just a way of ranking
  feature sets.

  The problem appears to be very multidimensional:  there may be
  preferences implied by the original content, the recipient system
  or the receiving user.  In addition, the different features each
  add an additional dimensions of posible preference.
  Mathematically, the set of all feature collections and a fully
  general ordering relation of "preference" could be viewed as
  yielding a partially ordered set.  Simplifying assumptions should,
  I believe, be aimed at making this into a fully ordered set, so
  that an ordering relation is defined for every pair of feature
  collections.

  Given some simplifying assumptions, the approach suggested for
  using predicates to select allowable data formats might be extended
  to preferences.  One might then view a predicate as a restricted
  preference (i.e. preference compared with no data transfer).









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6. Security considerations

  [[Does this introduce any security considerations which are not
  already covered in [1,2,3]?  I suspect not.]]


7. Copyright

  Copyright (C) The Internet Society 1998.  All Rights Reserved.

  This document and translations of it may be copied and furnished to
  others, and derivative works that comment on or otherwise explain
  it or assist in its implementation may be prepared, copied,
  published and distributed, in whole or in part, without restriction
  of any kind, provided that the above copyright notice and this
  paragraph are included on all such copies and derivative works.
  However, this document itself may not be modified in any way, such
  as by removing the copyright notice or references to the Internet
  Society or other Internet organizations, except as needed for the
  purpose of developing Internet standards in which case the
  procedures for copyrights defined in the Internet Standards process
  must be followed, or as required to translate it into languages
  other than English.

  The limited permissions granted above are perpetual and will not be
  revoked by the Internet Society or its successors or assigns.

  This document and the information contained herein is provided on
  an "AS IS" basis and THE INTERNET SOCIETY AND THE INTERNET
  ENGINEERING TASK FORCE DISCLAIMS ALL WARRANTIES, EXPRESS OR
  IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTY THAT THE USE OF
  THE INFORMATION HEREIN WILL NOT INFRINGE ANY RIGHTS OR ANY IMPLIED
  WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE.


8. Acknowledgements

  My thanks to Larry Masinter for demonstrating to me the breadth of
  the media feature issue, and encouraging me to air my early ideas.

  Early discussions of early ideas on the IETF-HTTP and IETF-FAX
  discussion lists led to useful inputs from Koen Holtman, Larry
  Masinter, Ted Hardie and Dan Wing.

  The debate was later moved to the IETF conneg WG mailing list,
  where Al Gilman was particularly helpful in helping me to refine
  these ideas for a feature set algebra.








Klyne                                                        [Page 14]


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9. References

[1]  "Scenarios for the Delivery of Negotiated Content"
     T. Hardie, NASA Network Information Center
     Internet draft: <draft-ietf-http-negotiate-scenario-02.txt>
     Work in progress, November 1997.

[2]  "Requirements for protocol-independent content negotiation"
     G. Klyne, Integralis Ltd.
     Internet draft: <draft-ietf-conneg-requirements-00.txt>
     Work in progress, March 1998.

[3]  "Content feature tag registration procedures"
     Koen Holtman, TUE
     Andrew Mutz, Hewlett-Packard
     Ted Hardie, NASA
     Internet draft: <draft-ietf-http-feature-reg-03.txt>
     Work in progress, November 1997.

[4]  "Notes on data structuring"
     C. A. R. Hoare,
     in "Structured Programming"
     Academic Press, APIC Studies in Data Processing No. 8
     ISBN 0-12-200550-3 / 0-12-200556-2
     1972.

[5]  "Programming in Prolog" (2nd edition)
     W. F. Clocksin and C. S. Mellish,
     Springer Verlag
     ISBN 3-540-15011-0 / 0-387-15011-0
     1984.

[6]  "Media Features for Display, Print, and Fax"
     Larry Masinter, Xerox PARC
     Koen Holtman, TUE
     Andrew Mutz, Hewlett-Packard
     Dan Wing, Cisco Systems
     Internet draft: <draft-masinter-media-features-02.txt>
     Work in progress, January 1998.
















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10. Author's address

  Graham Klyne
  Integralis Technology Ltd
  Brewery Court
  43-45 High Street
  Theale
  Reading, RG7 5AH
  United Kingdom

  Telephone: +44 118 930 6060

  Facsimile: +44 118 930 2143

  E-mail: GK@ACM.ORG








































Klyne                                                        [Page 16]