Introduction - Writing for Computer Science - page 5

of issues that working researchers need to consider. For experienced researchers, it
provides a reference point against which they can assess their own views and abili-
ties, and is an exposure to wider cultures of research. This topic is also intended to
encourage reflection; some chapters pose questions about research that a responsible
researcher should address. Nobody can learn to write or become a researcher just
by reading this topic, or indeed any topic. To become competent it is necessary to
practice, that is, to do research and write it up in collaboration with experienced
researchers. However, familiarity with the elements of writing and research is essen-
tial in scientific training.
Style is in some respects a matter of taste. The advice in this topic is not a code
of law to be rigidly obeyed; it is a collection of guidelines, not rules, and there are
inevitably situations inwhich the “correct” style will seemwrong. But generally there
are good reasons for writing in a certain way. Almost certainly you will disagree with
some of the advice in this topic, but exposure to another opinion should lead you
to justify your own choice of style, rather than by habit continue with what may be
poor writing. A good principle is: By all means break a rule, but have a good reason
for doing so.
Most computer scientists can benefit from reading a topic about writing and
research. This topic can be used as the principal text for a senior research meth-
ods subject, or for a series of lectures on the practice of research. Such a subject
would not necessarily follow this topic chapter by chapter, but instead use it as a
resource. In my own teaching of research methods, lectures on writing style seem to
work best as introductions to the key topics of good writing; talking students through
the detailed advice given here is less effective than getting them to read the topic
while they write and undertake research for themselves. That said, for a range of
topics—figures, algorithms, presentations, statistics, reading and reviewing, draft-
ing, ethics, and experimentation, for example—the relevant chapter can be used as
the basis of one or two lectures.
This topic covers the major facets of writing and experimentation for research in
computer science:

￿ Commencing a research program, including getting started on the research and the

writing (Chap. 2 ) , reading and reviewing (Chap. 3 ) , and principles of hypotheses,
research questions, and evidence (Chap. 4 ) .

￿ Organization of papers and theses, and the practice of writing (Chap. 5 ) .

￿ Good writing, including writing style (Chaps. 6 - 8 ) , mathematical style (Chap. 9 ) ,

presentation of algorithms (Chap. 10 ) , design of figures and graphs (Chap. 11 ) ,
expert writing for other professional contexts (Chap. 12 ) , and final editing
(Chap. 13 ) .

￿ Research methodology, including experimentation (Chap. 14 ) and statistical prin-

ciples (Chap. 15 ) .

￿ Presentations, including talks and posters (Chap. 16 ) .

￿ Ethics (Chap. 17 ) .

There are also exercises to help develop writing and research skills.