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How Do You Write a Research Proposal for Academic Writing
If you are in college then one of the many questions on your mind may be, how do you write a research proposal for academic writing. To write an academic research proposal is most likened to writing a proposal that addresses a project. The only difference is that the research proposal has either academic or scientific research at the …

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How To Write A Dissertation

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default How To Write A Dissertation

Post by Admin on Mon Jan 07, 2013 8:08 am

How To Write A Dissertation


or


Bedtime Reading For People Who Do Not Have Time To Sleep







To The Candidate:



So, you are preparing to write a Ph.D. dissertation in an experimental
area of Computer Science. Unless you have written many formal documents
before, you are in for a surprise: it's difficult!


There are two possible paths to success:



    • Planning Ahead.
      Few take this path. The few who do leave the University so
      quickly that they are hardly noticed. If you want to make a
      lasting impression and have a long career as a graduate student,
      do not choose it.



    • Perseverance.
      All you really have to do is outlast your doctoral committee. The
      good news is that they are much older than you, so you can guess
      who will eventually expire first. The bad news is that they are
      more practiced at this game (after all, they persevered in the face
      of their doctoral committee, didn't they?).




Here are a few guidelines that may help you when you finally get serious
about writing. The list goes on forever; you probably won't want to read it
all at once. But, please read it before you write anything.









The General Idea:




  1. A thesis is a hypothesis or conjecture.



  2. A PhD dissertation is a lengthy, formal document that argues in defense
    of a particular thesis. (So many people use the term ``thesis'' to refer
    to the document that a current dictionary now includes it as the third
    meaning of ``thesis'').


  3. Two important adjectives used to describe a dissertation are ``original''
    and ``substantial.'' The research performed to support a thesis must
    be both, and the dissertation must show it to be so. In particular,
    a dissertation highlights original contributions.


  4. The scientific method means starting with a hypothesis and then
    collecting evidence to support or deny it. Before one can write a
    dissertation defending a particular thesis, one must collect evidence
    that supports it. Thus, the most difficult aspect of writing a
    dissertation consists of organizing the evidence and associated
    discussions into a coherent form.


  5. The essence of a dissertation is critical thinking, not experimental
    data. Analysis and concepts form the heart of the work.


  6. A dissertation concentrates on principles: it states the lessons learned,
    and not merely the facts behind them.


  7. In general, every statement in a dissertation must be supported either
    by a reference to published scientific literature or by original work.
    Moreover, a dissertation does not repeat the details of critical thinking
    and analysis found in published sources; it uses the results as fact and
    refers the reader to the source for further details.


  8. Each sentence in a dissertation must be complete and correct in a
    grammatical sense. Moreover, a dissertation must satisfy the stringent
    rules of formal grammar (e.g., no contractions, no colloquialisms, no
    slurs, no undefined technical jargon, no hidden jokes, and no slang,
    even when such terms or phrases are in common use in the spoken
    language). Indeed, the writing in a dissertaton must be crystal clear.
    Shades of meaning matter; the terminology and prose must make fine
    distinctions. The words must convey exactly the meaning intended,
    nothing more and nothing less.


  9. Each statement in a dissertation must be correct and defensible in a
    logical and scientific sense. Moreover, the discussions in a
    dissertation must satisfy the most stringent rules of logic applied to
    mathematics and science.


What One Should Learn From The Exercise:




  1. All scientists need to communicate discoveries; the PhD dissertation
    provides training for communication with other scientists.


  2. Writing a dissertation requires a student to think deeply, to organize
    technical discussion, to muster arguments that will convince other
    scientists, and to follow rules for rigorous, formal presentation of
    the arguments and discussion.


A Rule Of Thumb:



    Good writing is essential in a dissertation. However, good writing
    cannot compensate for a paucity of ideas or concepts. Quite the
    contrary, a clear presentation always exposes weaknesses.



Definitions And Terminology:




  1. Each technical term used in a dissertation must be defined either by
    a reference to a previously published definition (for standard terms
    with their usual meaning) or by a precise, unambiguous definition
    that appears before the term is used (for a new term or a standard
    term used in an unusual way).


  2. Each term should be used in one and only one way throughout the
    dissertation.


  3. The easiest way to avoid a long series of definitions is to include
    a statement: ``the terminology used throughout this document follows
    that given in [CITATION].'' Then, only define exceptions.


  4. The introductory chapter can give the intuition (i.e., informal
    definitions) of terms provided they are defined more precisely later.




Terms And Phrases To Avoid:




  • adverbs

      Mostly, they are very often overly used. Use
      strong words instead. For example, one could
      say, ``Writers abuse adverbs.''

    </li>
  • jokes or puns

      They have no place in a formal document.

    </li>
  • ``bad'', ``good'', ``nice'', ``terrible'', ``stupid''

      A scientific dissertation does not make moral
      judgements. Use ``incorrect/correct'' to refer
      to factual correctness or errors. Use precise
      words or phrases to assess quality (e.g.,
      ``method A requires less computation than
      method B''). In general, one should avoid all
      qualitative judgements.

    </li>
  • ``true'', ``pure'',

      In the sense of ``good'' (it is judgemental).

    </li>
  • ``perfect''

      Nothing is.

    </li>
  • ``an ideal solution''

      You're judging again.

    </li>
  • ``today'', ``modern times''

      Today is tomorrow's yesterday.

    </li>
  • ``soon''

      How soon? Later tonight? Next decade?

    </li>
  • ``we were surprised to learn...''

      Even if you were, so what?

    </li>
  • ``seems'', ``seemingly'',

      It doesn't matter how something appears;

    </li>
  • ``would seem to show''

      all that matters are the facts.

    </li>
  • ``in terms of''

      usually vague

    </li>
  • ``based on'', ``X-based'', ``as the basis of''

      careful; can be vague

    </li>
  • ``different''

      Does not mean ``various''; different than what?

    </li>
  • ``in light of''

      colloquial

    </li>
  • ``lots of''

      vague & colloquial

    </li>
  • ``kind of''

      vague & colloquial

    </li>
  • ``type of''

      vague & colloquial

    </li>
  • ``something like''

      vague & colloquial

    </li>
  • ``just about''

      vague & colloquial

    </li>
  • ``number of''

      vague; do you mean ``some'', ``many'', or ``most''? A quantative statement
      is preferable.

    </li>
  • ``due to''

      colloquial

    </li>
  • ``probably''

      only if you know the statistical probability (if you do, state it
      quantatively

    </li>
  • ``obviously, clearly''

      be careful: obvious/clear to everyone?

    </li>
  • ``simple''

      Can have a negative connotation, as in ``simpleton''

    </li>
  • ``along with''

      Just use ``with''

    </li>
  • ``actually, really''

      define terms precisely to eliminate the need to clarify

    </li>
  • ``the fact that''

      makes it a meta-sentence; rephrase

    </li>
  • ``this'', ``that''

      As in ``This causes concern.'' Reason: ``this''
      can refer to the subject of the previous
      sentence, the entire previous sentence, the
      entire previous paragraph, the entire previous
      section, etc. More important, it can be
      interpreted in the concrete sense or in the
      meta-sense. For example, in: ``X does Y. This means ...''
      the reader can assume ``this'' refers to Y or
      to the fact that X does it. Even when
      restricted (e.g., ``this computation...''), the
      phrase is weak and often ambiguous.

    </li>
  • ``You will read about...''

      The second person has no place in a formal dissertation.

    </li>
  • ``I will describe...''

      The first person has no place in a formal
      dissertation. If self-reference is essential,
      phrase it as ``Section 10 describes...''

    </li>
  • ``we'' as in ``we see that''

      A trap to avoid. Reason: almost any sentence
      can be written to begin with ``we'' because
      ``we'' can refer to: the reader and author, the
      author and advisor, the author and research
      team, experimental computer scientists, the
      entire computer science community, the science
      community, or some other unspecified group.

    </li>
  • ``Hopefully, the program...''

      Computer programs don't hope, not unless they
      implement AI systems. By the way, if you are
      writing an AI thesis, talk to someone else:
      AI people have their own system of rules.

    </li>
  • ``...a famous researcher...''

      It doesn't matter who said it or who did it.
      In fact, such statements prejudice the reader.

    </li>
  • Be Careful When Using ``few, most, all, any, every''.

      A dissertation is precise. If a sentence
      says ``Most computer systems contain X'', you
      must be able to defend it. Are you sure you
      really know the facts? How many computers
      were built and sold yesterday?

    </li>
  • ``must'', ``always''

      Absolutely?

    </li>
  • ``should''

      Who says so?

    </li>
  • ``proof'', ``prove''

      Would a mathematician agree that it's a proof?

    </li>
  • ``show''

      Used in the sense of ``prove''. To ``show'' something,
      you need to provide a formal proof.

    </li>
  • ``can/may''

      Your mother probably told you the difference.

    </li>


Voice:




    Use active constructions. For example, say ``the operating system starts
    the device'' instead of ``the device is started by the operating system.''



Tense:




    Write in the present tense. For example, say
    ``The system writes a page to the disk and then uses the frame...''
    instead of
    ``The system will use the frame after it wrote the page to disk...''


Define Negation Early:




    Example: say ``no data block waits on the output queue'' instead of
    ``a data block awaiting output is not on the queue.''


Grammar And Logic:




    Be careful that the subject of each sentence really does what the verb
    says it does. Saying
    ``Programs must make procedure calls using the X instruction''
    is not the same as saying
    ``Programs must use the X instruction when they call a procedure.''
    In fact, the first is patently false! Another example:
    ``RPC requires programs to transmit large packets''
    is not the same as
    ``RPC requires a mechanism that allows programs to transmit large
    packets.''
    All computer scientists should know the rules of logic. Unfortunately
    the rules are more difficult to follow when the language of discourse is
    English instead of mathematical symbols. For example, the sentence
    ``There is a compiler that translates the N languages by...''
    means a single compiler exists that handles all the languages, while
    the sentence
    ``For each of the N languages, there is a compiler that translates...''
    means that there may be 1 compiler, 2 compilers, or N compilers. When
    written using mathematical symbols, the difference are obvious because
    ``for all'' and ``there exists'' are reversed.





Focus On Results And Not The People/Circumstances In Which They Were Obtained:





    ``After working eight hours in the lab that night, we realized...''
    has no place in the dissertation. It doesn't matter when you realized it
    or how long you worked to obtain the answer. Another example:
    ``Jim and I arrived at the numbers shown in Table 3 by measuring...''
    Put an acknowledgement to Jim in the dissertation, but do not include
    names (even your own) in the main body.
    You may be tempted to document a long series of experiments that
    produced nothing or a coincidence that resulted in success. Avoid
    it completely. In particular, do not document seemingly mystical
    influences (e.g., ``if that cat had not crawled through the hole in the
    floor, we might not have discovered the power supply error indicator
    on the network bridge''). Never attribute such events to mystical
    causes or imply that strange forces may have affected your results.
    Summary: stick to the plain facts. Describe the results without
    dwelling on your reactions or events that helped you achieve them.



Avoid Self-Assessment (both praise and criticism):




    Both of the following examples are incorrect:
    ``The method outlined in Section 2 represents a major breakthrough
    in the design of distributed systems because...''
    ``Although the technique in the next section is not earthshaking,...''


References To Extant Work:




    One always cites papers, not authors. Thus, one uses a singular verb
    to refer to a paper even though it has multiple authors. For example
    ``Johnson and Smith [J&S90] reports that...''
    Avoid the phrase ``the authors claim that X''. The use of ``claim'' casts
    doubt on ``X'' because it references the authors' thoughts instead of the
    facts. If you agree ``X'' is correct, simply state ``X'' followed by a
    reference. If one absolutely must reference a paper instead of a result,
    say ``the paper states that...'' or ``Johnson and Smith [J&S 90] presents
    evidence that...''.



Concept Vs. Instance:




    A reader can become confused when a concept and an instance of it
    are blurred. Common examples include: an algorithm and a particular
    program that implements it, a programming language and a compiler, a
    general abstraction and its particular implementation in a computer
    system, a data structure and a particular instance of it in memory.


Terminology For Concepts And Abstractions




    When defining the terminology for a concept, be careful to decide
    precisely how the idea translates to an implementation. Consider the
    following discussion:

    VM systems include a concept known as an address space. The system
    dynamically creates an address space when a program needs one, and
    destroys an address space when the program that created the space
    has finished using it. A VM system uses a small, finite number to
    identify each address space. Conceptually, one understands that
    each new address space should have a new identifier. However, if
    a VM system executes so long that it exhausts all possible address
    space identifiers, it must reuse a number.


    The important point is that the discussion only makes sense because it
    defines ``address space'' independently from ``address space identifier''.
    If one expects to discuss the differences between a concept and its
    implementation, the definitions must allow such a distinction.




Knowledge Vs. Data




    The facts that result from an experiment are called ``data''. The term
    ``knowledge'' implies that the facts have been analyzed, condensed, or
    combined with facts from other experiments to produce useful information.



Cause and Effect:




    A dissertation must carefully separate cause-effect relationships from
    simple statistical correlations. For example, even if all computer
    programs written in Professor X's lab require more memory than the
    computer programs written in Professor Y's lab, it may not have anything
    to do with the professors or the lab or the programmers (e.g., maybe the
    people working in professor X's lab are working on applications that
    require more memory than the applications in professor Y's lab).



Drawing Only Warranted Conclusions:




    One must be careful to only draw conclusions that the evidence supports.
    For example, if programs run much slower on computer A than on computer B,
    one cannot conclude that the processor in A is slower than the processor
    in B unless one has ruled out all differences in the computers' operating
    systems, input or output devices, memory size, memory cache, or internal
    bus bandwidth. In fact, one must still refrain from judgement unless one
    has the results from a controlled experiment (e.g., running a set of
    several programs many times, each when the computer is otherwise idle).
    Even if the cause of some phenomenon seems obvious, one cannot draw a
    conclusion without solid, supporting evidence.



Commerce and Science:




    In a scientific dissertation, one never draws conclusions about the
    economic viability or commercial success of an idea/method, nor does
    one speculate about the history of development or origins of an idea.
    A scientist must remain objective about the merits of an idea independent
    of its commercial popularity.
    In particular, a scientist never assumes that commercial success is a
    valid measure of merit (many popular products are neither well-designed
    nor well-engineered).
    Thus, statements such as ``over four hundred vendors make products using
    technique Y'' are irrelevant in a dissertation.


Politics And Science:




    A scientist avoids all political influence when assessing ideas.
    Obviously, it should not matter whether government bodies, political
    parties, religious groups, or other organizations endorse an idea. More
    important and often overlooked, it does not matter whether an idea
    originated with a scientist who has already won a Nobel prize or a
    first-year graduate student. One must assess the idea independent of
    the source.



Canonical Organization:




    In general, every dissertation must define the problem that motivated
    the research, tell why that problem is important, tell what others have
    done, describe the new contribution, document the experiments that
    validate the contribution, and draw conclusions.
    There is no canonical organization for a dissertation; each is unique.
    However, novices writing a dissertation in the experimental areas of CS
    may find the following example a good starting point:



    • Chapter 1: Introduction

        An overview of the problem; why it is important; a summary
        of extant work and a statement of your hypothesis or specific
        question to be explored. Make it readable by anyone.


      </li>
    • Chapter 2: Definitions

        New terms only. Make the definitions precise, concise,
        and unambiguous.


      </li>
    • Chapter 3: Conceptual Model

        Describe the central concept underlying your work. Make
        it a ``theme'' that ties together all your arguments. It should
        provide an answer to the question posed in the introduction at
        a conceptual level. If necessary, add another chapter to give
        additional reasoning about the problem or its solution.


      </li>
    • Chapter 4: Experimental Measurements

        Describe the results of experiments that provide
        evidence in support of your thesis. Usually experiments
        either emphasize proof-of-concept (demonstrating the
        viability of a method/technique) or efficiency (demonstrating
        that a method/technique provides better performance than
        those that exist).


      </li>
    • Chapter 5: Corollaries And Consequences

        Describe variations, extensions, or other applications of the
        central idea.


      </li>
    • Chapter 6: Conclusions

        Summarize what was learned and how it can be applied.
        Mention the possibilities for future research.


      </li>
    • Abstract:

        A short (few paragraphs) summary of the the dissertation.
        Describe the problem and the research approach. Emphasize
        the original contributions.

      </li>



Suggested Order For Writing:




    The easiest way to build a dissertation is inside-out. Begin by
    writing the chapters that describe your research (3, 4, and 5 in the
    above outline). Collect terms as they arise and keep a definition for
    each. Define each technical term, even if you use it in a conventional
    manner.
    Organize the definitions into a separate chapter. Make the
    definitions precise and formal. Review later chapters to verify that
    each use of a technical term adheres to its definition.
    After reading the middle chapters to verify terminology, write the
    conclusions. Write the introduction next. Finally, complete an
    abstract.




Key To Success:




    By the way, there is a key to success: practice. No one ever
    learned to write by reading essays like this. Instead, you
    need to practice, practice, practice. Every day.



Parting thoughts:




    We leave you with the following ideas to mull over. If they don't mean anything
    to you now, revisit them after you finish writing a dissertation.




      After great pain, a formal feeling comes.




            -- Emily Dickinson





      A man may write at any time, if he will set himself doggedly to it.




            -- Samuel Johnson





      Keep right on to the end of the road.




            -- Harry Lauder





      The average Ph.D. thesis is nothing but the transference of bones from
      one graveyard to another.




            -- Frank J. Dobie







Translations:


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