Scientific Writing Some personal observations

1. Kim Guldstrand Larsen Scientific WritingSome personal observations UCb

2. Tools andBRICS Applications visualSTATE UPPAAL SPIN PVS HOL ALF TLP • Semantics • Concurrency Theory • Abstract Interpretation • Compositionality • Models for real-time • & hybrid systems • Algorithmic • (Timed) Automata Theory • Graph Theory • BDDs • Polyhedra Manipulation • Logic • Temporal Logic • Modal Logic • MSOL

3. A very complex system Klaus Havelund, NASA

4. Spectacular Software Bugs • ARIANE-5 • INTEL Pentium II floating-point division 470 Mill US $ • Baggage handling system, Denver 1.1 Mill US $/day for 9 months • Mars Pathfinder • Radiation theraphy, Therac-25 • …….

5. Embedded Systems • 80% of all existing software is embedded in interacting devices. • Demand on increasing functionality with minimal resources.

6. How? Unified Model=State Machine! b? y! a Output ports x Input ports b? y b a? x! Control states

7. Tamagotchi C A B ALIVE Passive Feeding Light Meal A B A Health:= Health-1 B A Snack Care Clean A Health=0 or Age=2.000 A A Medicine Discipline Play DEAD Tick A A Health:=Health-1; Age:=Age+1

8. Digital Watch Statechart=UML, David HAREL

9. SYNCmaster

10. SPIN, Gerald Holzmann AT&T

11. visualSTATE VVS w Baan Visualstate, DTU (CIT project) • Hierarchical state systems • Flat state systems • Multiple and inter-related state machines • Supports UML notation • Device driver access

12. Larsen et al UPPAAL

13. Tool Support System DescriptionA No! Debugging Information TOOL Yes, Prototypes Executable Code Test sequences RequirementF Tools:UPPAAL, visualSTATE, SPIN, ESTEREL, TeleLogic, Statemate, Formalcheck,..

14. Tool Support System DescriptionA No! Debugging Information TOOL Yes, Prototypes Executable Code Test sequences RequirementF • Mathematical Formalisms for modelling and specifying System Behaviour • Methods for Analysis Algorithms/Datastructures • Experiment/Implementation • Case Studies • Tool Building

15. Writing Scientific Paper(s)

16. Collaboration L. Aceto P. Bouyer A. Burgueno Hans Hüttel Jens C. Godskesen Michael Zeeberg U. Holmer Karlis Cerans J.H. Andersen J. Niederman F. Laroussinie P. Pettersson H.E. Jensen J.H. Andersen Kristian Lund Bodentien Nicky O. Vestergaard Jacob Friis Jakob T. Iversen M. Laursen R.G. Madsen S.K. Mortensen C.B. Thomasen F. Cassez Alexandre David Oliver Möller Ansgar Fehnker Judi Romijn Tobias Amnell Pedro R. D'Argenio Bertrand Jeannet Frits Vaandrager M. Hendriks Henning Dierks Radek Pelanek Zoltan Esik Anders Børjesson Wang Yi P. Pettersson C. Weise Justin Pearso J. Staunstrup H.R. Andersen H. Hulgaard G. Behrmann K. Kristoffersen J. Lind-Nielsen H. Leerberg N.B. Theilgaard T. Hune Bengt Jonsson J. Bengtsson W.O.D. Griffioen F. Larsson Arne Skou J. Stage K. Nørmark U.H. Engberg P.D. Mosses E. Brinksma W.R. Cleaveland T. Margari B. Steffen S. Skyum G. Winskel Mogens Nielsen Finn V. Jensen G. Boudol Bent Thomsen Liu Xinxin Robin Milner Klaus Havelund

17. Writing a Paper / Papers • Work on a (relevant) CS question • Write a scientific paper • Submit the paper to an appropriate journal/conference • Ifaccepted then • Add one line to CV • Present work at scientific meeting (and get ideas for the next papers) • Else: Go to Step 1. • In any case: Go to Step 1.

18. What is a Scientific Paper • A scientific paper is a written and published report describing original research results • Primary Publication, i.e. • the first publication of original research results • repeatable and testable • available • Technical report/web (I/we did it [first]) • Conference paper (It works, it’s neat, and there is more to come) • Journal • Textbooks or research monographs BRICS DBLP Bib Server 93 32 (10)

19. Why Do People Write Papers? • Idealist: Any scientific paper furthers our knowledge of the field. It is a contribution to the community of our peers. • Realist: My point of view is that “Our currency is reputation” (Moshe Vardi at our Research Evaluation). Good scientific papers are one of the means to increase reputation in our scientific community. Our peers decide the weight of a primary publication (citations is a possible measure).

20. ww.citeseer.com … 521. J. Ferrante: 1882522. M. Lee: 1882523. A. Cox: 1878524. R. Needham: 1878525. J. Foley: 1877526. F. Glover: 1877527. K. Larsen: 1873528. T. Dietterich: 1872529. J. Kubiatowicz: 1871530. D. Lenoski: 1871531. S. Geman: 1870532. D. Gelernter: 1869533. J. Kramer: 1869534. Y. Yang: 1861 ……….. 558. M. Lee: 1510559. M. Maher: 1509560. J. Jaffar: 1505561. J. Lenstra: 1504562. A. Swami: 1503563. Z. Li: 1502564. S. Hammarling: 1502565. G. Stewart: 1499566. D. Shmoys: 1499567. K. Larsen: 1495568. J. White: 1494569. G. Winskel: 1493570. L. Stockmeyer: 1491571. X. Wang: 1491 The 10.000 most cited CS authors out of 629.254

21. www.citeseer.com Context   Doc     132.2 128 (6):   K.G. Larsen and A. Skou. Bisimulation through probabilistic testing (preliminary report). In Proc. 16th ACM Symp. Princ. of Prog. Lang., pages 344--352, 1989. ContextDoc67.4 46 (3):   J. Bengtsson, K.G. Larsen, F. Larsson, P. Pettersson, and W. Yi. UPPAAL- a tool suite for the automatic verification of real-time systems. In Proceedings of Hybrid Systems III. LNCS 1066.pages 232-243. Spriger Verlag. 1996. Context   Doc     42.1 39 (10):   K. G. Larsen and L. Xinxin. Compositionality through an operational semantics of contexts. Journal of Logic and Computation, 1:761--795, 1991. ContextDoc41.4 31 (0):   K. G. Larsen, P. Pettersson, and W. Yi. Model-checking for real-time systems. In Horst Reichel, editor, Proceedings of the 10th International Conference on Fundamentals of Computation Theory, volume 965 of Lecture Notes in Computer Science, pages 62--88, Dresden, Germany, August 1995. Springer-Verlag. ContextDoc34.3 21 (3):   Larsen, K. G., P. Pettersson and , Y. Wang: "UPPAAL in a nutshell". To appear: International Journal on Software Tools for Technology Transfer, Springer Verlag, September 1997.

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25. How to write a scientific paper • The main message: The preparation of a scientific paper has almost nothing to do with literary skill. It is a question of collaboration and organization. • Rule of Thumb: In your presentation, follow a logical progression from problem to solution.

26. Typical Organization • Title / List of authors / Abstract • Introduction / compelling example / related work / overview • Development • Conclusion (if any) • Acknowledgments / references

27. Title • It should be informative • It should be concise • It should be catchy / memorable • It is best original, but it does not need to be funny • The title is a label, not a sentence

28. Title – examples • Gérard Boudol, Kim G. Larsen:``Graphical versus Logical Specifications'' • Kim G. Larsen, Arne Skou:"Bisimulation Through Probabilistic Testing“ • Klaus Havelund, Kim G. Larsen:``The Fork Calculus'' • K.G. Larsen, F. Laroussinie, C.Weise: ``From Timed Automata to Logic – and Back''

29. Titles – more examples • Kim G. Larsen, Carsten Weise, Wang Yi and Justin Pearson:``Clock Difference Diagrams.'' • J. Lind-Nielsen, H.R. Andersen, G. Behrman, H. Hulgaard, K. Kristoffersen and K.G. Larsen: ``Verification of Large State/Event Systems using Compositionality and Dependency Analysis” • F. Cassez, K.G. Larsen: ``The Impressive Power of Stopwatches'' • Kim G. Larsen, Gerd Behrmann, Ed Brinksma, Ansgar Fehnker, Thomas Hune, Paul Pettersson, Judi Romijn:``As Cheap as Possible: Efficient Cost-Optimal Reachability for Priced Timed Automata'' • G. Behrmann, K. G. Larsen, R. Pelanek: “To Store or Not to Store.”

30. The List of Authors • Alphabertically ordered • Ordered by degrees of contribution • Student first, supervisor second • Any other scheme • I have almost always used alphabetical order.

31. Authorship and Credits • An author of a paper should be defined as one who takes intellectual responsibility for the research results being reported. • Give lavish acknowledgments. (One feels miffed after reading a paper in which one has not been given proper credit.)Give credit where it is due. It does not cost anything, and it creates friends. Science is more of a social activity than you might think.

32. Introduction • A bad beginning makes a bad ending • FACT: The introduction often decides the destiny of a paper. The introduction is often the only part of your paper that will be read.The introduction should not be (too) technical.

33. Introduction • It should present and motivate first, and in all possible clarity, the nature and scope of the problem investigated. • It should review related literature (to orient reader and please reviewer). • Clearly state achievement of paper • Overview the rest of the paper • A compelling example is always good. • Link to the Introduction during the remainder of the paper.

34. Pitfalls • Exaggeration • Seeking the effect for the sake of seeking effect: “this paper bridges a much need gap”. • Misspelling (always use a splel-checker)

35. How to Present Your Results • Technical preliminaries/background (setting the scene) • Progressive development of the material (organized in logical sections). • Remember to state where your contribution lies. • Anticipate, and answer, the possible questions that a reader might have.

36. How to Present Your Results • Present your results in as logical a way as possible. If reader needs A to understand B, then first present A, then B. • Always introduce technical terms before using them.

37. On Formalization • Primary objective is clarity:be as formal as it takes to make your point – but no more!! • Lift your results to the most abstract/general level – I.e. convey main technique rather than mathematical fiddling.

38. Related Work • Mandatory • Situates the novelty and significance of your work. Answers at least the questions: • where do the ideas come from? • have similar ideas been published earlier • what is really new in the paper • Where: introduction or conclusion or stand-alone.

39. Conclusion • Option 1: None • Option 2: Minimal • recapitulate problem and the contribution • assesses the significance of the contribution • outline of future work

40. Submission The Actors • Author(s) • Editor(s) / program committee members • The referees • The intended audience, and • Time

41. Review • The task of a referee is to evaluate in a timely manner a paper for publication (in journal or conference proceedings) • Evaluation / Critical Judgment • Timeliness

42. Receiving a Referee Report Before reading a referee report • Take a deep breath • Remember that a good report is always valuable • somebody spent time reading your paper • Use the reports to improve In this job one needs a thick skin

43. To Remember • Our currency is reputation. It takes a lot of hard work and (scientific) socal skills to build one, but it takes very little to destroy it • Try to evaluate your own work using the standards you apply to somebody else’s, but do not be your own worst enemy.