ICSEA 2007 - Environment for UI Evolution
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Transcript of ICSEA 2007 - Environment for UI Evolution
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Software Environment for Research on Evolving User Interfaces
Juan Quiroz, Anil Shankar, Sergiu M. Dascalu, Sushil J. Louis
Department of Computer Science and Engineering
University of Nevada, Reno
USA
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Outline
• Motivation
• Background
• Evolution environment
• Improving research productivity
• Transitioning from research to end-user tool
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Motivation
• User interface design is a complex, expensive, time consuming process
• Iterative process
• Users and contexts of use are numerous
• Streamline and improve UI design
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IGA for UI Evolution
• IGA to explore the space of UIs– Creativity and insight
• Evolution is guided by both the user preferences and coded guideline metrics
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Genetic Algorithms
• Population based search technique– Natural selection– Survival of the fittest
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Interactive Genetic Algorithms (IGAs)
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Implementation Details
• Python
• GUI – wxPython
• Target language – XUL
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XUL User Interfaces
• XML User Interface Language
• Mark-up language for UIs– Buttons, textboxes, sliders
menubars, toolbars
• <button label=“Hello World” />
Poor XUL rendering support in python
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Investing Time on Development
vs.
Research Experimentation
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Research Environment Improvements
• wxPython integration
• Experiment runs manager
• Data manager
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wxPython Integration
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Experiment Runs Manager
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Data Manager
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Future Productivity Improvements
• GUI definition in wxGlade or NetBeans
• Integration of user interface definition in the environment
• Higher level user interface specification
• Code generation
• User interface editing
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Transitioning from Research to End-User Tool
• Users– Researchers– UI designers
• Environment Modes– End-user mode– Researcher mode
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User Modes
• End-user mode– Minimalist interface– Reduce technical jargon
• “Variety”• “Creativity”
– Subset of functionality of researcher mode
• Researcher mode– Advanced configuration
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Use CaseEnd-User Mode
Researcher Mode
1 Define user interface √ √
2 Load user interface definition √
3 Customize high level IGA details √ √
4 Customize low level IGA details √
5 Start IGA √ √
6 Stop IGA √ √
7 Open IGA state √ √
8 Save IGA state √ √
9 Select best and worst UI √ √
10 Undo evolution step √ √
11 Redo evolution step √ √
12 Edit evolved UI √ √
13 Run batch mode √
14 Extended help √
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Summary
• UI evolution
• Investing time on environment development– Improves productivity– Less error prone– Reduces tedious tasks
• Transition from end-user to research tool