Software Visualization (EVO 2008)

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    Software Visualization (EVO 2008) - Presentation Transcript

    1. Software visualization Tudor Gîrba www.tudorgirba.com
    2. Software Visualization is the use of typography, graphic design, animation, and cinematography with human-computer interaction and computer graphics to facilitate both the human understanding and effective use of software. 3 Price etal. 199
    3. Why visualization?
    4. A picture is worth a thousand words. Ano nymous
    5. 1854, London, cholera epidemic
    6. 1854, London, cholera epidemic
    7. 1946
    8. A picture is worth a thousand words. Ano nymous
    9. We are vis ual beings
    10. How many groups do you see?
    11. How many groups do you see?
    12. How many groups do you see?
    13. How many groups do you see?
    14. lt prin ciples Gesta proximity similarity enclosure connectivity
    15. lt principles More Gesta closure continuity
    16. Iconic memory < 1 second very fast automatic subconscious preattentive
    17. Iconic Short-term memory memory < 1 second couple of seconds very fast 3-9 chunks automatic subconscious preattentive
    18. Orientation Line Length Line Width Size Shape Curvature Added Marks Enclosure
    19. Line Length Line Width Size Shape Curvature Added Marks Enclosure
    20. Line Width Size Shape Curvature Added Marks Enclosure
    21. Size Shape Curvature Added Marks Enclosure
    22. Shape Curvature Added Marks Enclosure
    23. Curvature Added Marks Enclosure
    24. Added Marks Enclosure
    25. Enclosure
    26. How many times does 5 appear? 8789364082376403128764532984732984732094873290845 389274-0329874-32874-23198475098340983409832409832 049823-0984903281453209481-0839393947896587436598
    27. How many times does 5 appear? 8789364082376403128764532984732984732094873290845 389274-0329874-32874-23198475098340983409832409832 049823-0984903281453209481-0839393947896587436598
    28. ternal input 7 0% o f all ex ough t he eye com es thr
    29. A picture is worth a thousand words. Ano nymous
    30. it lite rally :) UM L took
    31. Example: what is ?
    32. What to visualize? How to visualize?
    33. What to visualize?
    34. What to visualize? Software structure
    35. System Complexity shows class hierarchies Ducas se 2003 Lanza,
    36. Polymetric views show up to 5 metrics Width metric Height metric Position metrics Color metric Lan za 2003
    37. 003 , Du casse 2 Lanza
    38. Distribution Map shows properties over structure 6 casse etal 200 Du
    39. Package Map shows who owns what classes 7 Gre evy 200
    40. 992 Shneid erman 1
    41. What to visualize? Software structure Software relationships
    42. Class Blueprint shows class internals Initialize Interface Internal Accessor Attribute invocation and access direction se, Lan za 2005 Ducas
    43. Class Blueprint has a rich vocabulary internal access Access external Attribute access Invocation Regular Constant invocations Overriding Delegating lines Method Extending Setter Abstract Getter se, Lan za 2005 Ducas
    44. se, Lan za 2005 Ducas
    45. 06 Holten 20
    46. Hierarchical edge bundles clarify dependencies 6 Hol ten 200
    47. 08 Holten 20
    48. Correlation Matrix reveals correlations user, run, load, message, file, buffer, util property, AWT, edit, show, update, sp, set start, buffer, end, text, length, line, count action, box, component, event, button, layout, GUI start, length, integer, end, number, pre, count XML, dispatch, microstar, reader, XE, register, receive current, buffer, idx, review, archive, endr, TAR BSH, simple, invocation, assign, untype, general, arbitrary maximum, label, link, item, code, put, vector Kuhn e tal 2006
    49. Arc diagrams show duplications 00 2 Watte nberg 2
    50. What to visualize? Software structure Software relationships Metaphors
    51. Software Map reveals software geography 8 Kuhn etal 200
    52. CodeCity reveals where software lives 7 We ttel 200
    53. 0 8 Wettel 20
    54. What to visualize? Software structure Software relationships Metaphors Interaction
    55. Softwarenaut discovers architecture tal 2006 Lungu e
    56. What to visualize? How to visualize?
    57. nderst anding t guara ntee u ation does no V isualiz
    58. Minimize non-data ink Tuf te, 1990
    59. Excel 2004 default
    60. Excel 2004 default Excel 2004 default + 6 actions
    61. 6 casse etal 200 Du
    62. Maximize data ink Tuf te, 1990
    63. InfoBug is cute and condensed 00 6 Chuah , Eick, 2
    64. s a la ngu age provide visual ization Each learnt s to be th at need
    65. System Complexity 1 node type 1 edge type 3 metrics Class Blueprint 3 node types 2 edge types 3 metrics 8 properties
    66. A small experiment
    67. 1, 13, 27, 4, 96
    68. What were the numbers?
    69. Easy!
    70. What’s the last advertisement you saw?
    71. Not so easy!
    72. s a la ngu age provide visual ization Each learnt s to be th at need
    73. tion is a rt, too V isualiza
    74. Tudor Gîrba www.tudorgirba.com creativecommons.org/licenses/by/3.0/

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