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Visualizing Software Ecosystems as Living Cities

Visualizing Software Ecosystems as Living Cities. Clint Jeffery University of Idaho. Outline. Motivation & Background Visualizing Software as (Static) Cities “Living” Cities Implementation Conclusions. Motivation. Motivation. Millions of lines of code

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Visualizing Software Ecosystems as Living Cities

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  1. Visualizing Software Ecosystems as Living Cities Clint Jeffery University of Idaho

  2. Outline • Motivation & Background • Visualizing Software as (Static) Cities • “Living” Cities • Implementation • Conclusions

  3. Motivation

  4. Motivation • Millions of lines of code • Still perceived as boring and solitary • “Software visualization” promised a fix • Time to just go do it

  5. Visualizing Software as Cities • Wettel and Lanza proposed CodeCity • Swiss, SmallTalk, treemap rendering • Static view of a software repository

  6. Outliers Among 8000+ Classes

  7. Topography

  8. 2D Minimap – Initial Layout

  9. Software Maps Kuhn, Loretan, Nierstrasz

  10. CrocoCosmos

  11. Depicting Associations?

  12. The “Living City” Metaphor • 3D Representation of Running System • City Structure: Depicts Code of Multiple Programs • Denizens of the City: the users, the running instances of the programs they are using, and finer-grained objects • Convey a projection of cyber-reality • Stronger man-machine connection • Users stroll, chat, write code, shoot bugs

  13. Roadways • Street, arterial, and freeway

  14. Buildings • Dimensions convey class size • Texture conveys date of origin

  15. Building Interiors • One storey per method • Building directory and central elevator

  16. Method Details • Walls show code, profile information • Space holds activation records

  17. Time Model • Wall clock vs. “CPU Time” per thread

  18. Executions

  19. Procedures

  20. Bugs

  21. Unicon City? • 570,000 LOC; 195,000 is C code • ~350,000 LOC .icn written by 60 authors • 142 directories, ~half have payload

  22. Unicon City, Take #2

  23. Implementation Notes • Collaborative virtual environment • Initial “world” generation from codebase • Incremental algorithms for code changes • Rich source of high performance dynamic data • Heaps of NPC AI • Piles of gameplay mechanics • Enthusiastic user base • Big iron

  24. Conclusions • Large project • Yes, we now can implement Neuromancer • Need volunteers, partners, and a grant/sponsor • Will take ~3 years, culmination of 20+ • Some of you will still be here to enjoy it at that time

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