Writing Strategies for Computer Science Graduate Students

Transcription

1 Part 1a: Writing Professional Abstracts: samples for discussion Theories for TC0 and Other Small Complexity Classes Phuong Nguyen, University of Toronto Stephen Cook, University of Toronto Abstract We present a general method for introducing finitely axiomatizable "minimal" two-sorted theories for various subclasses of P (problems solvable in polynomial time). The two sorts are natural numbers and finite sets of natural numbers. The latter are essentially the finite binary strings, which provide a natural domain for defining the functions and sets in small complexity classes. We concentrate on the complexity class TC 0, whose problems are defined by uniform polynomial-size families of bounded-depth Boolean circuits with majority gates. We present an elegant theory VTC 0 in which the provably-total functions are those associated with TC 0, and then prove that VTC 0 is "isomorphic" to a different-looking singlesorted theory introduced by Johannsen and Pollet. The most technical part of the isomorphism proof is defining binary number multiplication in terms a bitcounting function, and showing how to formalize the proofs of its algebraic properties. A NEW RECURSION-THEORETIC CHARACTERIZATION OF THE POLYTIME FUNCTIONS Stephen Bellantoni and Stephen Cook Abstract. We give a recursion-theoretic characterization of FP which describes polynomial time computation independently of any externally imposed resource bounds. In particular, this syntactic characterization avoids the explicit size bounds on recursion (and the initial function 2jxj jyj) of Cobham. Key words. Recursion theory, Cobham, Polynomial Time Planning as Temporal Reasoning James F Allen, Department of Computer Science, University of Rochester Abstract This paper describes a reasoning system based on a temporal logic that can solve planning problems along the lines of traditional planning systems. Because it is cast as inference in a general representation,

2 however, the ranges of problems that can be described is considerably greater than in traditional planning systems. In addition, other modes of plan reasoning, such as plan recognition or plan monitoring, can be formalized within the same framework. ACL '96: A Robust System for Natural Spoken Dialogue James F. Allen, Bradford W. Miller, Eric K. Ringger, and Teresa Sikorski Abstract: This paper describes a system that leads us to believe in the feasibility of constructing natural spoken dialogue systems in task-oriented domains. It specifically addresses the issue of robust interpretation of speech in the presence of recognition errors. Robustness is achieved by a combination of statistical error post-correction, syntactically- and semantically-driven robust parsing, and extensive use of the dialogue context. We present an evaluation of the system using time-to-completion and the quality of the final solution that suggests that most native speakers of English can use the system successfully with virtually no training. From--How (and How Not) to Write a Good Systems Paper Roy Levin and David D. Redell Was an abstract written first? Does it communicate the important ideas of the paper? Abstracts in papers describing systems are sorely abused. The abstract is more often a prose table of contents than a precis of the technical content of the paper. It tends to come out something like this: A system based on Keysworth's conceptualization of user interaction [4] has been designed and implemented. Some preliminary results are presented and directions for future work considered. No reader skimming a journal is likely to keep reading after that. Avoid the passive voice (despite tradition) and include a simple statement of assumptions and results. We designed and implemented a user interface following the ideas of Keysworth and discovered that converting the space bar to a toe pedal increases typing speed by 15%. However, accuracy decreased dramatically when we piped rock music instead of Muzak (tm) into the office. Leave discussion and argument for the paper. It helps to write the abstract before the paper (despite tradition) and even the outline, since it focusses your attention on the main ideas you wants to convey. Page 2 of 6

3 Part 1b: Writing Professional Abstracts: general strategies 1 1. Function: An abstract summarizes, in one paragraph (usually), the major aspects of the entire paper. For science writing, here is the usual sequence: o the question(s) you investigated (or purpose) o state the purpose very clearly in the first or second sentence. the experimental design and/or methods used o clearly express the basic design of the study. o name or briefly describe the basic methodology used without going into excessive detail-- be sure to indicate the key techniques used. the major findings including key quantitative results, or trends o report those results which answer the questions you were asking o identify trends, relative change or differences, etc. a brief summary of your interpretations and conclusions o clearly state the implications of the answers your results gave you. The Abstract helps readers decide whether they want to read the rest of the paper, or it may be the only part they can obtain via electronic literature searches or in published abstracts. Therefore, enough key information (e.g., summary results, observations, trends, etc.) must be included to make the Abstract useful to someone who may to reference your work. How do you know when you have enough information in your Abstract? A simple rule-of-thumb is to imagine that you are another researcher doing a study similar to the one you are reporting. If your Abstract was the only part of the paper you could access, would you be happy with the information presented there? 2. Style: Use the active voice when possible, though some may require passive constructions. Write your Abstract using concise, but complete, sentences, and get to the point quickly. Do not mix past and present tenses. The Abstract SHOULD NOT contain: lengthy background information, references to other literature, elliptical (i.e., ending with...) or incomplete sentences, abbreviations or terms that may be confusing to readers, any sort of illustration, figure, or table, or references to them. Compare the two Eyegaze abstracts (handed out separately), both about the same article. Which one do you think represents best practices and why? 1 The information in Part 1b is adapted from the Biology Dept., Bates College, Lewiston, ME: Page 3 of 6

4 Part 2: Toward a Professional Writing Style 2 Make Sure Your Sentences are Coherent Use an Old-to-New Information Pattern Old information will be something familiar to your readers. Old info can be in the sentence or two before the one they re reading, or can be apparent within the context of the sentence, or can be part of readers general knowledge of a topic. Begin sentences with old information. When possible, shift new information something readers can t anticipate to the ends of sentences. Use Topic-Strings Ensure topics connect consistently from sentence to sentence. You should find the main topic of your sentence near the beginning, in the old information section. A set of focused sentences is essentially a coherent paragraph: a set of consistent topic threads. Find the topic-thread. If it s not apparent or it gets lost, revise your sentences according to an old/new information pattern. Use transitions & connectives where needed to indicate opposition, agreement or linkage, cause & effect, exemplification or illustration, degree & comparison. Here s a basic structural principle for reader-friendly professional sentences: The SENTENCE BEGINNING has Topic/Subject Given (old) information Shorter, simpler, familiar structures The SENTENCE ENDING has Action/ Verb New information New, longer, complex structures Stress or climax Use the Passive and Active Voices Wisely ACTIVE: The committee will investigate the high failure rates in these courses. AGENT (subject) ACTION (trans. verb) GOAL (object) PASSIVE: The high failure rates in these courses will be investigated [by the committee]. GOAL (object) ACTION AGENT (subject) The passive allows us to place the GOAL (object of the transitive verb) at the front of the sentence. We can also omit the agent (subject) altogether. STRATEGY: Choose the passive when the GOAL is clearly the most important part of the story (as in much journalistic and some scientific writing); or you don t know who did it; or your readers don t care who did it; or it isn t relevant who did it. 2 Material in Part 2 is adapted from Joseph M. Williams and Ira B. Nadel, Style: 10 Lessons in Clarity and Grace, Cdn ed. (Toronto: Pearson Longman, 2005). Page 4 of 6

5 CAUTION: Don t confuse the passive construction with the verb to be used as an auxiliary or main verb. Ex: The researchers are expecting to begin gathering data tomorrow is not a passive sentence. Here, simply rewrite to be + ing as one main verb. Use Plain Language Whenever Possible Human Resources and Social Development Canada: The Plain Language Association International: Using Plain Language in the Sciences: The ability to use plain language can be a career boost! Part 3: Recommended Follow-Up Resources General Writing and Other Graduate Student Resources The SFU Student Learning Commons follow-up appointments, links to online writing resources, hardcopy handouts, writing reference books The Purdue University Online Writing Lab general resources about writing, with attention to grammar, English as an additional language, and style "Time Management" by the University of Guelph Learning Commons ml University of Maryland University College: creating a writing plan and project schedule 02.shtml "Writing and Presenting Your Thesis or Dissertation" by S. Joseph Levine, Michigan State University The Dead Thesis Society: a Canadian graduate student support group Page 5 of 6

6 So long, and thanks for the PhD : a computer science graduate school survival guide Some Modest Advice for Graduate Students : Dept. of Integrative Biology, Graduate Student Handbook Computer Science-Specific Writing Resources Three Sins of Authors in Computer Science and Math Jonathan Shrewchuk How (and How Not) to Write a Good Systems Paper -- Roy Levin and David D. Redell Writing Bad Papers, Writing Good Papers Tamara Munzner Page 6 of 6