softvis 2005: saint louis, missouri, usa michael burch, stephan diehl, peter weißgerber: visual...
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![Page 1: SOFTVIS 2005: Saint Louis, Missouri, USA Michael Burch, Stephan Diehl, Peter Weißgerber: Visual data mining in software archives Martin Pinzger, Harald](https://reader034.vdocument.in/reader034/viewer/2022051619/56649d435503460f94a1ebad/html5/thumbnails/1.jpg)
SOFTVIS 2005: Saint Louis, Missouri, USA
Michael Burch, Stephan Diehl, Peter Weißgerber: Visual data mining in software archives
Martin Pinzger, Harald Gall, Michael Fischer, Michele Lanza: Visualizing multiple evolution metrics
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Data Mining Terminology
• Association rules: Item changed at the same time (related item)
• Sequence rules: order of these changes
• Binary Association Rules: how often 2 items changed together
• Support: Number of transaction containing the item
• Confidence: Number of Changes for pair item over single item
• Outliers: unbalance datasets or abnormal distance
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Introduction
• What is visualize
- Binary association rules
- n-ary association rules
- Sequence rules
- distribution, support and confidence –histogram
• Tool EPOSee: Integrates different view
• Purpose: detect clusters, inspect rules, zoom and
filters
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EPOSee InterfacePixelmap
Support Graph
3D Bar Chartfilter
Search keywordColors
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Parallel Coordinates View Decision Tree
3D branch view
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Rule matrix
Item list
Rule detail Support & confidence
n-ary association rules
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3D bar charts
• Strong dependecies: High Support & confidence
• Use color and heights
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Visualize binary association rule only
Pixelmap
File ordering: hierarchical
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Stronger related
Pixelmap Example
File coupling atdifferent directorylevel
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Edges: related items
Outliers: blue
Clusters: sets of items
Support Graph
Nodes: Items
Red:high
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Association Rule Matrix
y-axis: Items
x-axis: Rules
Red, blue & white pixels
Support:length
Confidencecolor
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Parallel Coordinates View
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VisualizeSequence
Rules
Parallel CoordinatesView
Nodes Color: Support Values
Edges Color: Confidences
Cluster on samesubdirectory
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Parallel Coordinates View
Green edges: high confidence
But, no edges with high confidence is coming into these 2 nodes
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Pinzger, Gall, Fischer, Lanza:Visualizing multiple evolution metrics
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• Objective: Communicate the evolution of metrics of source code entities and their relationships
Kiviat Diagram
M1, M2..,M6 = 6 metrics
increasing
decreasing
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Metrics
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Logical Coupling
Edge: Coupling relationship
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A module from Mozilla
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