Software Visualization
Information Visualization June 30, 2008
Carsten Görg
Slides adapted from John Stasko
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Housekeeping
• Assignment 5: Understanding Analytics
due this Wednesday, July 2nd • Poster Grading
• Remaining lectures:
− Animation + tips for exam (Wednesday)
− Visual Analytics (Monday)
− Final Exam (Wednesday)
− Wrap up (Monday)
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“The use of the crafts of typography, graphic design, animation, and cinematography with modern human-computer interaction and human-computer graphics technology to facilitate both the human understanding and effective use of computer software.”
Price, Baecker and Small, ‘98
Software Visualization
• Definition
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Challenge
• Software clearly is abstract data
• Unlike much information visualization, however, software is often dynamic, thus requiring our visualizations reflect the time dimension − History views − Animation − ... Summer term 2008 6
Subdomains
• Two main subareas of software visualization
− Program visualization - Use of visualization to help programmers, coders, developers.
Software engineering focus
− Algorithm visualization - Use of visualization to help teach algorithms and data structures. Pedagogy focus
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Subareas
• Program Visualization − Software engineering − Debugging − Program analysis − Systems/Architectures − Evolution • Algorithm Visualization − Pedagogy − Systems − Use in classroom − Empirical study Summer term 2008 8Lecture Focus
• This is a very big area, so this lecture will just give a flavor of the kinds of
techniques and systems that have been created
− Lots of figures
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ACM SoftVis
’03 – San Diego ’05 – St. Louis ’06 – Brighton ’08 – Germany Summer term 2008 10Algorithm Visualization
• Learning about algorithms is one of the most difficult things for computer science students
− Very abstract, complex, difficult to grasp
• Idea: Can we make the data and
operations of algorithms more concrete to help people understand them?
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Algorithm Animation
• Common name for area
• Dynamic visualizations of the operations and data of computer algorithm as it executes
− Abstraction is key concept
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Sorting Out Sorting
• Seminal work in area
• 30 minute video produced by Ron Baecker at Toronto in 1981
• Illustrates and compares nine sorting algorithms as they run on different data sets
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SoS Views
Video
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Balsa
• First main system in area
• Used in “electronic classroom” at Brown
• Introduced use of multiple views and interesting event model
M. Brown Computer ‘88
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Example Animation
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Tango
• Added smooth animation to algorithm animation
• Simplification of the design/programming process (easier programming model and framework)
• Formal model of the animation, the Path-Transition Paradigm
Stasko Computer ‘90
Summer term 2008 17 Multiple frames from bubblesort
Tango
Summer term 2008 18POLKA
• Improved animation design model
• Object-oriented paradigm
• Multiple animation windows
• Much richer visualization/animation capabilities
Stasko & Kraemer JPDC ‘93
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POLKA
Demo
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Evaluating Effectiveness
• Do algorithm animations actually help students learn?
− That’s the claim, but unproven
• Conducted a number of empirical studies to answer question
− Compare learning with animation to learning without
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Results
• Somewhat mixed, but some studies do show benefits
− -> Potential for pedagogical aid is there, but just can’t throw animation at algorithm and expect it to help
− Interaction is a key
Blindly watching algorithm animation not really helpful Student must interact with animation and be engaged
− Animations help motivation, can make algorithm less intimidating
Hundhausen, Douglas & Stasko JVLC ‘02
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Program Visualization
• Can be as simple as enhanced views of program source
• Can be as complex as views of the
execution of a highly parallel program, its data structures, run-time heap, etc.
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Enhanced Code Views
Primarily used as a documentation aid
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SeeSoft System
• Pulled-back, far away view of source code
• Map one line of source to one line of pixels
− Can indicate line indentation, etc.
• Like taping your source code to the wall, walking far away, then looking back at it
Eick, Steffen and Sumner IEEE ToSE ‘92
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System View
15,000 lines of code in 52 files Summer term 2008 26Use
• Tracking (typically means mapping this data attribute to color)
− Code modification (when, by whom)
− Bug fixes
− Code coverage or hotspots
• Interactive, can change color mappings, can brush views, and so on
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Tarantula
• System developed at GT
• Utilizes SeeSoft code view methodology
• Takes results of test suite run and helps developer find program faults
• Clever color mapping is the key
Eagan, Harrold, Jones & Stasko InfoVis ’01
Jones, Harrold & Stasko ICSE ‘02
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Tarantula View
Video
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Paper Recap
“CVSscan: Visualization of Code Evolution” Lucian Voinea, Alex Telea, Jarke J. van Wijk
SoftVis’05: Proceedings of the 2005 ACM Symposium on Software Visualization
Stefan Heinz
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Motivation
• Program and process understanding is an important aspect of software maintenance
• Most visualizations focus on high-level system abstractions or they don't consider the entire project duration
• Typical questions the tool helps to answer:
− What lines were added, removed, altered and when?
− Who performed this modifications?
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Technique
• Data set consists of tuples <id, author, date, code> • Usage of line-oriented displays
• Basic layout / color scheme:
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Technique/Application
interval selector code view, second layer code view, main layerversion centric filter
attribute selection view mode
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Case Studies
• Record and analyze the experiences of maintainers investigating completely new programs
− Analysis of a Perl script file (457 glp, 65 versions)
− Analysis of a C code file (2900 glp, 60 versions) • Results:
− Supports quick assessment of the important activites and produced artifacts
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Critique (Pros & Cons)
• Shows the whole file evolution at once • Different coloring schemes• Details are shown by the code view and the second layer supports a smooth file browsing • No visualization of project evolution or context
of a file in the project
• Two points of focus when browsing in the file (at least when used mouse-only)
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Stepping Up
• Next step in program visualization is to help debugging and performance
optimization by visualizing program executions
− Data, data structures, run-time heap,
memory, control flow, data flow, hot spots, ...
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Graph Visualization
• Area that we’ve already studied which is very important to SV
• Graphs pop up everywhere in software
• Common use: Visualize a call graph, visualize a flow chart, ...
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Sample CallGraph View
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Paper Recap
“Visualizing Java in Action”
Steven P. Reiss
Proc. IEEE Conference on Software Visualization, Mai 2003
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Motivation
• Dynamic software visualization aims to provide insights into a running system
• Most current dynamic visualizations based on traces or slow down program substantially
ÆNo real time information • JIVE
− Java visualization framework
− Minimal overhead
ÆSlowdown by factor 2 or less
− Emphasis on real time
− Informative & entertaining
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Information
• High-level program-specific information
− Executing classes
Number of method calls Execution time per class − Memory
Classes of allocated objects Memory consumption per class − Thread behavior
Thread state monitoring Synchronization and blocking
• Internal Java hooks too slow ÆPatching of target classes ÆAggregation for libraries
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Technique
• Compact & scalable display
• Needs to show large number of objects • Box display
− Simple
− Fast & easy to understand • One box per class
− Height: # method calls
− Width: # allocated objects by this class
− Hue: # allocated objects of this class
− Intensity: Usage within time interval • Stacked boxes per thread
− Height: % time in thread state
− Hue: Thread state
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Critique
+ Real time information with minimal overhead + Simple & compact display
+ Easy to use & fun to watch
- Patching time
- Artifacts caused by tracing code itself - Limited control over visualization
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Paper Recap
“Visualization of Program-Execution Data for Deployed Software”
Alessandro Orso, James Jones, Mary Jean Harold Proc. of SoftVis '03, May 2003, pp. 67-76
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Paper Recap
“Program Comprehension through Software Habitability” Richard Wettel and Michele Lanza
Faculty of Informatics - University of Lugano, Switzerland Daniel Lorig
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Motivation
• Widely used program comprehension is visualization • Many of the proposed visualizations fail at transmitting a sense of „habitability“ to the viewer
• in 2D visualizations, the viewer looks at a system like a picture, without notion of physical space
• 3D visualizations fail to produce a notion of locality because objects can be freely moved
→ Proposed 3D visualization supports habitability and locality
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The City Metaphor
• Display classes (and interfaces) as buildings in city districts (representing packages)
• height represents NOM, width and length represent NOA
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Refinement
• humans not good at distinguishing so many distinct shapes • map to a discrete number of shapes
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Application
change impact of an interface exploring a „suburb“
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Critique (Pros & Cons)
+ habitability and locality through navigable and interactive environment+ developers can talk about certain parts of the city as as actual physical place Æeases communication between people
- allows no exploration of concrete classes via the city metaphor (shows only the source code)
-relationships like inheritance and method invocations are not represented
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Commercial Systems
• A number of commercial program
development environments have begun to incorporate program visualization tools such as these
− Majority are PC-based
• Has not become as wide-spread as I would have anticipated
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Concurrent Programs
• Understanding parallel programs is even more difficult than serial
• Visualization and animation seem naturals for illustrating concurrency
• Temporal mapping of program execution to animation becomes critical
Kraemer & Stasko JPDC ‘93
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POLKA
• We developed a system, POLKA, that was designed to help people build
visualizations of concurrent programs − Used for both program and algorithm
visualization
− Used for different programming models: message passing, shared memory threads, ...
Stasko & Kraemer JPDC ‘93
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Message Passing Systems
PVM/Conch
Topol, Stasko, Sunderam IJPDSN ‘98
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Shared Memory Threads
Zhao & Stasko TR ‘95 Pthreads
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Current State of SV
• Research continues…
• Some use of algorithm animations as pedagogical aids
• Program visualization trickling into commercial tools
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What’s Needed? (PV)
• Better analysis of what software developers want and need
• Flexible displays providing overview and detail
• Improved tracing/monitoring/analysis capabilities
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What’s Needed? (AA)
• Focus on interactive tools
• Simpler animation construction
• Empirical validation of value
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References
• All referred to papers
