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    >> It is the theory that decides what can be observed. - Albert Einstein
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    【 以下文字转载自 小百合BBS Algorithm 讨论区 】
    【 原文由 starfish@lilybbs 所发表 】

    Three Great Challenges for Half-Century-Old Computer Science

    FREDERICK P. BROOKS, JR.
    University of North Carolina at Chapel Hill

    1. Quantification of Structural Information

    Shannon and Weaver [1949] performed an inestimable service by giving
    us a definition of information and a metric for information as
    communicated from place to place, negentropy. This metric,

          H = - Σ p_i log(p_i)

    and the associated concept of noise, have proved rich sources of
    further theory and of applications galore.

    We have no theory, however, that gives us a metric for the information
    embodied in structure, especially physical structure. We know that an
    automobile is a more complex structure than a rowboat. We cannot yet
    say it is x times more complex, where x is some number. Yet we know
    that the complexity is related to the Shannon information that would
    be required to specify the structures of the car and the boat.

    I consider this missing metric to be the most fundamental gap in the
    theoretical underpinnings of information science and of computer
    science. Recent developments, however, make it timely to address
    it. The fundamental biological structures are rich enough to repay
    study and yet simple enough that there is hope of making real progress
    on an information theory of structure. (Rowboats and automobiles are
    much too hard.) The coding of genetic information by DNA is apparently
    simple enough that it can be handled with existing communication
    theory. The folded structure of proteins is not. Entropic and
    energetic considerations are necessary, but not yet sufficient, for
    explaining and predicting that structure, even after the amino acid
    sequence is known. Yet proteins are relatively simple structures.

    A young information theory scholar willing to spend years on a deeply
    fundamental problem need look no further.

    2. Software Estimation

    Given specific functional, reliability, and performance specifications
    for a software system, we do not yet know how to estimate the effort
    required to build it. Nor, given the product specifications and a
    quite specific description of the skills of a particular team, can we
    reliably estimate how long it will take to grow the product.  The
    first book on computer software, by Wilkes et al. appeared in
    1951. Now, a half century later, there have been many, many advances
    in concept and technique.  Not the least of these is Boehm's
    monumental Software Engineering Economics [Boehm 1981] the COCOMO
    model set forth therein, and the subsequent software economic models
    stimulated by that work. Nevertheless, we still don't know what we are
    doing, unless it is very similar to something we have done before.

    The challenge is to make software engineering as predictable a
    discipline as civil or electrical engineering. I still do not expect
    any radical breakthrough, any silver bullet, to solve this problem
    [Brooks 1986]. But the accretion of many contributions has already
    made much progress, and I believe continued careful research, ever
    validated by real practice, will bring us to that goal.

    3. User Interface Design for Computer Systems

    Today, the design of the user interface for an operating system or an
    application program is still an art, not yet an engineering
    discipline.

    Much research has been done on human perception, human cognition, and
    on the human factors of output from the mind to the bodily
    effectors. On the other side of the human---computer interface, much
    research and development has advanced interface technologies: computer
    graphics, sound synthesis, speech synthesis, speech recognition, and
    haptics.

    Substantial as these research corpora are, we seem still to lack any
    systematic or disciplined way of integrating them when designing a new
    hardwaresoftwareuser interface. We do not have reliable ways even of
    predicting whether a proposed specific interface design will be good,
    that is,

    ---Intuitive for the novice;

    ---Efficient in perception and motion for the expert;

    ---Robust under misuse;

    ---Facilitating in recovery from cognitive or manipulative mistakes;

    ---Helpful in diagnosing errors and suggesting corrective action;

    ---Rich in incrementally learnable functions, like the alphabetical
       shortcuts on the Mac interface.

    The challenge is to integrate the relevant but disparate bodies of
    knowledge into a discipline of design.

    ACKNOWLEDGMENTS. Conversations with colleagues over the years have
    stimulated these ideas. I am especially indebted to Professor Jurg
    Nievergelt, whose thoughts on these challenges especially resonated
    with mine.

    REFERENCES

    BOEHM, B. 1981. Software Engineering Economics. Prentice Hall,
    Englewood Cliffs, N.J.

    BROOKS, F. P. 1986. No silver bullet---Essence and accident in
    software engineering. Information Processing 1986. Reprinted as
    Chapter 16 of Brooks, F. P. 1995. The Mythical ManMonth, Anniversary
    Edition, AddisonWesley, Reading, Mass.

    SHANNON,C .E.,AND WEAVER, W. 1949. The Mathematical Theory of
    Communication. University of Illinois Press, Urbana, Ill.

    WILKES,M .V.,WHEELER,D.J.,AND GILL, S. 1951. The Preparation of
    Programs for an Electronic Digital Computer, with Special Reference to
    the EDSAC and the Use of a Library of Subroutines. AddisonWesley,
    Reading, Mass.


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