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Trip Report Progress Report Thesis Plan

Trip Report Progress Report Thesis Plan. Kevin Pulo 2003-09-11. Overview. Brisbane Trip Report Griffith University University of Queensland Thesis plan Recent progress (in no particular order). Brisbane Trip Report – Griffith Uni.

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Trip Report Progress Report Thesis Plan

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  1. Trip ReportProgress ReportThesis Plan Kevin Pulo 2003-09-11

  2. Overview • Brisbane Trip Report • Griffith University • University of Queensland • Thesis plan • Recent progress (in no particular order)

  3. Brisbane Trip Report – Griffith Uni • Visited the Software Quality Institute (SQI), headed by Prof. Geoff Dromey • Software engineers • Invented Design Behaviour Trees (DBTs) and Genetic Software Engineering (GSE)

  4. DBTs • A method for designing software systems by defining “behaviours” of components from their requirements • These are then combined to form the overall behaviour of the system • Can then be used to generate skeletal code • Build the system out of the requirements, not a system which satisfies the requirements • Behaviours are naturally visually represented using trees

  5. Typical Component DBTs Requirement-R1: When the user opens the door the light goes on Requirement-R2: When the user closes the door the light goes off

  6. Integrating Component DBTs Requirement-R1: When the user opens the door the light goes on Requirement-R2: When the user closes the door the light goes off

  7. Integrating Component DBTs Satisfies both R1 and R2

  8. Overall DBTs

  9. Very Large DBTs

  10. User Navigation Data • They have issues visualising large DBTs • Installed my code on their machines • General code cleanup • Interface simplification • Animated undo/redo • Logging facilities to record user navigation • Will be useful in devising quality measures • Will provide a benchmark suite / corpus for running the measures

  11. DBT Improvements • Tip-over convention instead of inclusion layout (basically the same algorithm) • Some other misc features • Send updated version to Griffith researchers

  12. Brisbane Trip Report - UQ • Visited Advanced Computational Modelling Centre (ACMC) at UQ • Bernard Pailthorpe, co-director (former director of Sydney Vislab, SDSC’s Vislab) • Research mainly in Scientific Visualisation, collaborations with many wide fields (biotech, medical, psychology, physics, maths, chem, marine, etc) • Visited ViSAC - Visualisation Laboratory

  13. ViSAC photos

  14. Thesis Outline (Working) Fancy Title: “Techniques for Structural Focus + Context Display and Navigation” • Introduction, Background, etc • Started literature survey • Models, Measures and Techniques • Application to Relational Data • Inclusion Trees • Clustered Graphs • Case Study 1: Design Behaviour Trees (DBTs) • Case Study 2: FADE clustered graphs • Case Study 3: Citation networks • Conclusion, etc

  15. Data Sources - Trees • Design Behaviour Trees – Data #1 • Inclusion and tip-over layouts • Mostly done • Philogenetic Trees – ??? • Neither inclusion or tip-over seem appropriate • Problem is length of edge usually indicates time • How to represent this in inclusion layout?

  16. Data Sources – Clustered Graphs • FADE clustered graphs – Data #2 • Uses my work from first year (extending to Recursive Voronoi Diagrams (RVDs)) • Generally graphs of various views of software • Relatively sparse • From Aaron Quigley’s thesis or use SE tools to generate my own – or maybe even arbitrary graphs • Citation networks – Data #3 • From any/all of Citeseer, Web-of-Science, IEEE, ACM, etc • Clustered according to hierarchical topic (where available) • Relatively dense

  17. Edge Routing • Research possible algorithms • Attempt implementation of simple/naïve one first • Attempt harder ones only if simple one doesn’t suffice • Develop edge animations • Topology changes are hard

  18. Evaluation – Empirical Measures • Devise 5-7 good measures of the quality of a Smooth Structural Zooming technique • Eg: number of different animation directions, number of objects moving concurrently, amount of overlap between objects, etc • Assertion is that these measures are a good representation of reality • Apply the measures to a corpus of test data

  19. Test Data • Require test data of both graphs/trees AND navigation through them • Hence the Griffith usage data • Other possibilities: • Generated (random) • Hand-constructed specific cases (eg. best/worst, “typical”)

  20. Evaluation – User Experiments • Devise tasks to test some hypothesis • Considering not doing them • Require a lot of time and work: • Ethics approval • Logistics • Many unknown details: • Hypothesis = ? • Task(s) = ? • Measurements (eg. time, accuracy)

  21. Backups • Thesis/PhD work • ~ 900 Mb • 3 machines: Uni, home, laptop • Synchronised using rsync and rdiff-backup • Fast transfers, incremental backups • Alternatives include rsync, file-unison, cvs, etc • Also weekly CDs...? • Laptop • Daily/weekly rdiff-backup of majority of system (20 Gb) at uni and home

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