Writing for Computer ScienceWriting for Computer Science is an introduction to doing and describing - search. For the most part the book is a discussion of good writing style and effective research strategies. Some of the material is accepted wisdom, some is controversial, and some is my opinions. Although the book is brief, it is designed to be comprehensive: some readers may be interested in exploring topics further, but for most readers this book should be suf?cient. The ?rst edition of this book was almost entirely about writing. This e- tion, partly in response to reader feedback and partly in response to issues that arose in my ownexperiences as an advisor, researcher, and referee, is also about research methods. Indeed, the two topics—writing about and doing research— are not clearly separated. It is a small step from asking how do I write? to askingwhatisitthatIwriteabout? As previously, the guidance on writing focuses on research, but much of the material is applicable to general technical and professional communication. Likewise, the guidance on the practice of research has broader lessons. A pr- titioner trying a new algorithm or explaining to colleagues why one solution is preferable to another should be con?dent that the arguments are built on robust foundations. And, while this edition has a stronger emphasis on research than did the ?rst, nothing has been deleted; there is additional material on research, but the guidance on writing has not been taken away. |
Contents
Introduction | 1 |
Kinds of publication | 2 |
Writing science and skepticism | 3 |
Using this book | 4 |
Spelling and terminology | 6 |
Good style | 7 |
Economy | 8 |
Tone | 9 |
Performance of algorithms | 124 |
Asymptotic complexity | 126 |
Editing | 129 |
Consistency | 130 |
Proofreading | 131 |
Choice of wordprocessor | 133 |
An editing checklist | 134 |
Writing up | 137 |
Examples | 12 |
Motivation | 13 |
Balance | 14 |
The upper hand | 16 |
Analogies | 17 |
Straw men | 18 |
Reference and citation | 19 |
Quotation | 24 |
Acknowledgements | 26 |
Grammar | 27 |
Style specifics | 29 |
Titles and headings | 30 |
The opening paragraphs | 31 |
Variation | 33 |
Ambiguity | 34 |
Sentence structure | 36 |
Tense | 40 |
Emphasis | 42 |
Definitions | 43 |
Qualifiers | 45 |
Misused words | 46 |
Spelling conventions | 50 |
Jargon | 51 |
Cliché and idiom | 52 |
Overuse of words | 53 |
Padding | 54 |
Plurals | 56 |
Abbreviations | 57 |
Sexism | 58 |
Punctuation | 59 |
Stops | 60 |
Commas | 61 |
Colons and semicolons | 62 |
Apostrophes | 63 |
Hyphenation | 64 |
Quotations | 65 |
Parentheses | 66 |
Citations | 67 |
Mathematics | 69 |
Theorems | 71 |
Readability | 72 |
Notation | 74 |
Ranges and sequences | 75 |
Alphabets | 76 |
Numbers | 77 |
Percentages | 79 |
Units of measurement | 80 |
Graphs figures and tables | 83 |
Visualization of results | 93 |
Diagrams | 99 |
Tables | 100 |
Captions and labels | 111 |
Algorithms | 115 |
Formalisms | 117 |
Level of detail | 118 |
Figures | 119 |
Notation | 123 |
The scope of a paper | 138 |
Telling a story | 140 |
Organization | 143 |
The first draft | 149 |
From draft to submission | 150 |
Prepublication | 152 |
Theses | 153 |
A writingup checklist | 155 |
Doing research | 157 |
Beginnings | 158 |
Shaping a research project | 159 |
Students and advisors | 162 |
Finding research literature | 163 |
Reading | 165 |
Research planning | 167 |
Hypotheses | 169 |
Defending hypotheses | 173 |
Evidence | 175 |
Good and bad science | 177 |
Reflections on research | 180 |
A research checklist | 182 |
Experimentation | 185 |
Designing experiments | 186 |
Measurements and coding | 189 |
Describing experiments | 191 |
Variables | 192 |
Statistics | 198 |
Intuition | 203 |
An experimentation checklist | 204 |
Refereeing | 205 |
Responsibilities | 206 |
Evaluation of papers | 208 |
Referees reports | 210 |
A refereeing checklist | 213 |
Ethics | 215 |
Plagiarism | 217 |
Selfplagiarism | 219 |
Misrepresentation | 221 |
Authorship | 222 |
Confidentiality and conflict of interest | 223 |
An ethics checklist | 224 |
Giving presentations | 225 |
Content | 226 |
Organization | 228 |
The introduction | 229 |
The conclusion | 230 |
Delivery | 231 |
Question time | 233 |
Slides | 234 |
Text slides | 236 |
Figures | 237 |
Examples of slides | 238 |
Afterword | 249 |
251 | |
Exercises | 253 |
263 | |
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Common terms and phrases
acceptable advisor algorithm Amdahl's law analysis appropriate asymptotic analysis audience authors B-tree behaviour Big-O notation chapter citation common complete complexity analysis compression computer science consider consistent correct cost data sets data structure database describe detail diagram discussed disk documents edit distance elements errors evaluation example experimental experiments explain external sorting figure font graph hash hash function hash table hypothesis ideas identify improvement input interesting issues material mathematical means method notation outcomes paper paragraph parameters particular plagiarism points possible presentation problem programming language proof pseudocode pseudoscience published query questions reader reason referee reference relevant revision scientific scientists sentence slides sorting sorting algorithm Soviet navy space specific statements strings student style symbols talk technical theorem thesis tion topic typical variables words write-up writing
References to this book
Computational Linguistics and Intelligent Text Processing: Second ... Alexander Gelbukh No preview available - 2001 |