Transcript Designing Effective Algorithm Visualizations Sami Khuri

Designing Effective Algorithm
Visualizations
Sami Khuri
Department of Mathematics
and Computer Science
San José State University
www.mathcs.sjsu.edu/faculty/khuri
Outline
• Definition
• History
• Design process:
– Analysis phase
– Design phase
• Evaluation
• Concluding remarks
1. Definition
Algorithm Visualization
– is the process of abstracting a program’s data,
operations, and semantics, and creating
dynamic views of those abstractions.
– is a depiction of an algorithm using an
integrated set of multimedia tools, such as
graphics, text, color, sound, code, animation
and video.
2. History
1980s:
Visualizations can serve as
effective learning aid for students.
–
–
–
–
Balsa (Marc Brown, 1988)
Zeus (Marc Brown, 1991)
Tango (John Stasko, 1990), Xtango, Polka
Later: Leonardo (Crescenzi et al., 1997)
History
1990s:
Empirical studies: Do algorithm
animations really help?
– Results are unsatisfactory...
• Badre (1991)
• Hundhausen (1997)
• Stasko (1998)
History
Today:
Algorithm visualizations do
enhance learning,
– if existing visualizations are effectively used
• Naps (2000)
• Faltin (1999)
• Stasko and Lawrence (1998)
– if new visualizations are better designed
• Hansen, Narayanan, Schrimpsher
3. Design Process
• Good algorithm visualization is not simply
a matter of mimicking paper-based tasks or
doing what is technically easy.
• Even simple tools can improve algorithm
understanding, if they are the right ones.
• A lot of time and effort can be wasted
implementing a system that is not needed or
is unusable.
Design Process
• We advocate:
a user-centered approach
(What do we NEED to show?), instead of
a designer-centered approach
(What CAN we show?)
• Start with an analysis of the users, their needs,
tasks, information, and resources.
3.1. Analysis Phase
•
•
•
•
•
•
Users’ analysis
Needs analysis
Task analysis
Information analysis
Domain analysis
Resources analysis
3.1.1. Users’ Analysis
Who are they?
– No algorithm visualization will be universally
superior across all kinds of users.
– Understanding who the users are allows us to
determine content, organization, depth, breadth,
interaction and presentation methods.
Users’ Analysis
Algorithm visualization system might be
used by:
–
–
–
–
Students
Teaching Staff
Researchers
Visualization developers
Users’ Analysis
Students
– Will watch and interact with algorithm
visualizations.
– Will need a lot of help information.
– Will need a system that is forgiving to their
invalid input.
– Will need facilities for setting up desired speed
and detail level, and for reversing actions.
Users’ Analysis
Another possible approach is to
divide users into:
– Novice users
– Expert users
Users’ Analysis
Novice users
– Need a system that is very easy to use.
• For example, if the algorithm visualization system
requires the user to annotate his/her program to call
animation routines, the novice might not have the
skills to do so.
– Need clear and detailed help files.
– Do not need a system displaying many
different views of an algorithm.
Users’ Analysis
Expert users
– Need a system that complements and
supplements their thinking, rather than mimics
internal representations.
– Need a very flexible system allowing to see
different levels of details
• if they try to improve performance of an algorithm,
for example.
3.1.2. Needs Analysis
Do the users need algorithm
visualization?
– An assessment should be made as to whether
presenting an algorithm by visualizing it is the
most effective way to do so.
• For example, instructors can use a phonebook to
illustrate binary search.
• If instructors do not have access to the WWW in
class, they cannot use a web-based visualization
system.
3.1.3. Task Analysis
What will the users do with the algorithm
visualization tool?
– Create new animations.
– Interact with existing visualization to understand
the behavior of an algorithm.
– Debug their program.
– Each task demands a different kind of visualization
tool. It is difficult to build a system that satisfies
them all.
Task Analysis
How will the algorithm visualization fit
into the existing curricula?
–
–
–
–
–
–
Classroom demos
Assignments
Hands-on laboratories
Self-directed work outside of class
Office hours
Distance learning
Task Analysis
Classroom demos
– Algorithm visualizations should function well as
demonstrations.
– They will not need a lot of written explanations.
– They need a facility for adjusting the speed and
reversing previous steps.
– They should run smoothly to avoid unpleasant
situations where they “freeze”:
• Web-based tools are not always the best for this task.
Task Analysis
Homework assignments
– Algorithm visualizations have to run smoothly
on different platforms for everyone.
• Better to create Java applications, not applets:
– Web-based Java execution is unpredictable at this point.
– One has to test all the applications on the actual equipment
(under different environments) ahead of time.
Impossible to do!
– They should be available for download
• running them on the web server can be too slow.
3.1.4. Information Analysis
What are we trying to convey?
– Do we want to emphasize the data structures
rather than the algorithm or vice-versa?
– Create a profile of resource utilization.
– Search through an execution trace.
– Contrast two algorithms.
Information Analysis
Which aspects of an algorithm should
we illustrate?
–
–
–
–
–
Source code
Data
Data structures
Execution
The trend is toward the ability to visualize all
aspects of an algorithm.
Information Analysis
Source code visualization
– View the source code through a flowchart.
– View the code by displaying the pseudocode and
highlighting lines currently being executed.
– Present currently executing portion of the code
in a window.
Data visualization
– Extract and display only scalar variables such as
values held in an array.
Information Analysis
How should information be
represented?
–
–
–
–
–
Direct representation
Structural representation
Synthesized representation
Analytical representation
Explanatory representation
Information Analysis
Direct representation
– At any given instant, the data structure could be
constructed from the display, and the display could
be constructed from the data structure.
Information Analysis
Structural representation
– Only the important aspects are represented.
• For example, a computation running on a network of
processes, where each process is either “active” or
“inactive”. All other attributes of the processes are
concealed since they are not relevant to the viewer.
Information Analysis
Do we display current information or
illustrate history of what has
happened?
– Displaying history:
• helps explain the algorithm like a textbook example,
• lets users become familiar with the algorithm’s
dynamic behavior at their own speed.
Information Analysis
How will we move from one display to
the next one?
– Incremental transition
– Discrete transition
There is no pedagogical advantage of either
technique.
Information Analysis
Incremental transition
– Transition occurs smoothly.
– It is effective when users (especially novice)
are examining an algorithm running on a small
set of data.
– This type of transition is difficult and tedious to
implement.
– Developers need to decide how slow or fast the
transition should occur.
Information Analysis
What is the largest data set the
algorithm visualization should be able
to handle?
– Limit the size of input data.
– Large input files are allowed.
Information Analysis
Limit the size of input data
– If visualizations are used to explain steps of
algorithms.
• For example, viewing visualizations of large trees
will require scrolling to see the entire tree and might
confuse more than educate.
– If visualizations are used by novice users.
– If visualizations are used in homework
assignments.
Information Analysis
Very large size of input data
– Is useful for researchers or instructors in
classroom when comparing running times and
behavior of different algorithms.
– Cluttering the screen with information is not a
problem.
– Data items should be presented in the simplest
form, dots, for example.
3.1.5. Domain Analysis
What is the scope of the algorithm
visualization?
– General-purpose algorithm visualization
system
– Specialized algorithm visualization system
– Single-purpose algorithm visualizations
Domain Analysis
General-purpose algorithm
visualization systems
– Systems that can (ideally) animate any
algorithm.
– These type of systems should provide a large set
of ready-made pieces of visualizations and
general tools to create them.
– The greater the number of algorithms that can
be animated, the more desirable the result.
Domain Analysis
General-purpose algorithm
visualization systems
– Some of the general-purpose systems are
BALSA, TANGO and XTango, Zeus.
– Although general-purpose algorithm
visualization systems are becoming more
powerful, the task of using these tools to create
visualizations of algorithms still involves a lot
of work.
Domain Analysis
Specialized algorithm visualization
systems
– Systems that specialize in visualizing
algorithms from a certain field of computer
science, such as computational geometry.
– Restricting algorithm visualization system to
one field only eases the process of creating
visualizations, since graphical representation of
data structures will be implemented once only.
Domain Analysis
Single-purpose algorithm visualizations
– Programs that visualize one algorithm or a
group of related algorithms in detail.
– They are coded from scratch for each
algorithm.
– They are easier to create, understand and
maintain.
Domain Analysis
Is there a potential for the domain to
enlarge over time?
– Design for growth.
– Use object-oriented design.
– Provide extensive documentation.
3.1.6. Resources’ Analysis
Given the above information, do we
have the necessary resources to
create the algorithm visualization?
– Time.
– Human resources.
– Computer resources.
Resources’ Analysis
Time
– Designing and implementing algorithm
visualizations takes longer than expected.
Human resources
– Need a team of developers with skills in
context, graphical design, networks, etc.
Resources’ Analysis
Computer resources
– CPU speed, RAM, monitor size and resolution,
audio/video input and output, color display
panel and projection.
– If the prepared visualization will be available
over the internet, it might need large amounts
of storage space, and more importantly, highspeed connection to the net.
3.2. Design Phase
• Choosing specification method.
• Choosing techniques for visual
representation of information.
3.2.1. Specification Methods
Choices available to the developers:
– Predefinition (hand-coded visualization)
– Annotation
– Declaration (animation by demonstration)
3.2.1. Specification Methods
Predefinition (hand-coded visualization)
– Mainly used in application-specific visualization.
– Fixed or highly constrained mapping of the steps
of the algorithm to the graphical views.
• The information and its representation cannot be
changed after the implementation.
– The main advantage is the execution speed.
– Can be easily distributed.
– Can be very interactive and visually attractive.
Specification Methods
Annotation
– Important steps of an algorithm are annotated
with interesting events.
– These events call graphical operations from an
existing library.
• For example, move rectangles, change colors, etc.
– The main advantage of this approach is the
animators ability to define events at any suitable
level.
Specification Methods
Annotation
– The most significant shortcoming of this
method, is the need to access and modify the
code of the program.
– The first major system with interesting events
was BALSA by Brown.
– Other examples: Zeus and Tango.
Specification Methods
Declaration
– The developer defines mappings from program
states to graphical objects.
– During program execution, changes in the
program state trigger updates to the graphical
view of the program.
– This paradigm is instantiated in the Pavane
animation system by Roman, Cox, Wilcox and
Plun.
3.2.2. Techniques
Some techniques for visual
representation of information about
algorithms.
–
–
–
–
–
Selection of default visualizations.
Screen design and multiple views.
Color and Sound.
3-Dimension.
Interaction .
Selection of Default Visualization
Design appropriate default
visualizations
– How much complexity does the user of algorithm
visualization need?
• The complexity of visual presentations is generally
proportional to the amount of information being
conveyed.
• Start with relatively small problem instances and
gradually introduce larger ones for the users who
begin to understand the meaning of the visual patterns.
Selection of Default Visualization
Design appropriate default
visualizations
– For pedagogical purposes, the following input
data should be provided as default visualizations:
• Pathological input data
• Cooked input data
Screen Design
• The screen on which the visualization
occurs can easily get cluttered with the
many visual representations of control
constructs or data items.
• The user may get lost in the details and not
see the overall picture.
Screen Design
The solution to reducing the graphical
overload is abstraction:
– Condense complicated parts of the scene into
simpler items.
– Omit several phases of an algorithm and present
only the final result of several program steps.
– Use semantic zooming.
– Use step-wise refinement.
Screen Design
Stepwise Refinement
– Give the basic idea first and then progressively
add more detail.
– How many details do we want to display?
• Too many levels can have a counterproductive effect
and difficulty to the learning task.
• A rule of thumb: a given line of pseudocode should be
expandable to a maximum of three levels.
• The fully expanded pseudocode should fit on one
screen without scrolling.
Screen Design
Some recommendations
– Divide the screen into functional areas, each
containing a different type of information.
– Consistently display each type of information in
its assigned area.
– Place important information near the top and to
the left.
• Eye-motion studies show that our gaze goes to the
upper left of a rectangular display first and then
moves clockwise.
Screen Design
Recommendations for designing user
interface
– Don’t make the user guess where to click to
perform an action.
• For example, unlabeled graphics as controls (buttons,
links, etc.) are confusing.
– Try not to have two or more buttons that perform
the same action.
– Keep the interface uniform. Have the same
controls perform the same action everywhere.
Multiple Views
Multiple views
– Each view displays only a few aspects of the
algorithm.
– Each view must be easy to comprehend in
isolation.
– They are conceptually simpler and easier to
implement than monolithic views.
– They eliminate the possibility of forcing the
viewer to remember algorithm states no longer
on display.
Multiple Views
Multiple Views
Multiple views
– The important design question is how to
synchronize the views. Some possibilities are:
• Display related objects in different views in the
same color.
• Display related objects in different views using the
same shape (circle, triangle, etc.).
• Display related objects in different views in the
same size.
Multiple Views
Segmentation is a useful extension of
the multiple views idea
– If the user selects a physical region in one of
the views, the display would immediately
highlight the corresponding values in other
views.
Multiple Views
Multiple Views
Some recommendations
– If multiple views are needed to visualize a
concept, allow the users to page them so that
only one or the other can be seen at a time.
Color
Color offers the following advantages
– It calls attention to specific data or information.
– It identifies elements of structures and
processes.
– It can portray time.
– It increases appeal, believability, memorability,
and comprehensibility.
– It reduces errors of legibility and interpretation.
Color
Advantages of using color
– It allows denser presentation of information:
• fewer pixels are needed to make a color change
visible than to make a change in the shape of an
object visible.
– It increases the number of dimensions for
coding data:
• one can encode information in both the shape and
the color of objects.
Color
Drawbacks or disadvantages
– It requires more expensive and complicated
design equipment.
– It may not account for color deficiency among
some users:
• about eight percent of Caucasian males.
– It can cause visual fatigue and afterimages
induced by strong colors.
Color
Drawbacks or disadvantages
– It can invoke negative cultural associations to
some or all colors.
– Establishing general rules or specifications for
color use is very difficult:
• We still lack some important understanding of color
vision.
– Color is subjective:
• Different users have different preferences.
Color
Color can be used
– To draw attention,
• through highlighting, for example.
– To communicate organization.
– To indicate status.
– To establish relationships,
• in multiple views, for example.
– To increase user satisfaction.
Color
To draw attention
– temporarily paint a small region of interest with
a transparent, contrasting color:
• The highlight color should be transparent.
• It should not interact visually with the data elements
on the screen, but simply draw the eye to them.
• Highlight must be temporarily and should be
removed quickly when the scene changes. Think
about double-buffering in Java to avoid flickering.
Color
Color
Some recommendations for using
color
– It is better to be conservative.
• Use a maximum of five, plus or minus two colors.
– This allows extra room for short-term memory (about 20
seconds) which can store five words or shapes, six letters,
seven colors and eight digits.
• For novice viewers, four distinct colors are
appropriate.
Color
– Use fovea (center) and peripheral colors
appropriately.
• Use blue for large areas, such as background, not for text,
thin lines or small shapes.
– Blue-sensitive cones are the least numerous of the color receptors
in the retina, and the eye’s central focusing area, the fovea,
contains relatively few of these blue-sensitive cones.
• Use red and green in the center of the visual field, not in
the periphery.
– The edges of retina are not particularly sensitive to these colors.
• If red or green are used at the periphery, some signal to
the viewer must be given to capture attention (size
change, blinking, etc.)
Color
Some recommendations for using
color
– Do not use high-chroma, spectrally extreme
colors simultaneously.
• Strong contrasts of red/green, blue/yellow,
green/blue, and red/blue create vibrations, illusions
of shadows and afterimages.
Color
Some recommendations for using
color
– Use familiar, consistent color coding with
appropriate references. Some common Western
denotations are the following:
•
•
•
•
•
Red refers to stop, danger, hot, fire.
Yellow refers to caution, slow, test.
Green refers to O.K., clear.
Blue refers to cold, water.
Gray and white refer to neutrality.
Color
Some recommendations for using
color
– Carefully select colors that will be displayed
across media with different techniques for
generating color.
• Note, that CRT display screens use additive color
mixtures which combine into white, while most hard
copy devices use subtractive color mixtures which
combine into black.
Color
Some recommendations for using
color
– Use color to enhance black and white information.
– With respect to learning and comprehension, color is
superior to black and white in terms of viewers
emotional reactions.
• There is no difference in the viewer’s ability to interpret
information. People do not learn more from a color
display, although they may say they do.
• The crucial factor is that color is more enjoyable and color
information is easier to remember.
Color
Some recommendations for using
color
– Keep in mind that many people are color blind.
• Any time color is used to convey information, the
secondary cues should also be used.
• Secondary cues can consist of anything from the
subtlety of gray scale differentiation to having a
different graphic or different text label associated
with each color presented.
Sound
Why use sound in algorithm
visualizations?
– Sound has the potential to convey information
that is difficult or awkward to display
graphically.
– Sound can help reduce the visual clutter of
current graphic interfaces.
– Sound can be redundant with visual
information to reinforce the concepts.
Sound
Some problems when using sound
– Sound is more difficult to use than color.
• Most people do not have the same level of
sophistication and training aurally as they do
visually.
• What happens when more than one computer is
using audio in the same room?
• What happens when more than one “view” uses
audio?
• What if there are no audio output?
Sound
Some problems when using sound
– Sound is difficult to master:
•
•
•
•
•
frequency
volume
attack and decay rates
duration
timbre
– Poor use of sound is less forgiving than poor
use of color or 3-D.
Sound
Some problems when using sound
– Many aspects of sound perception are not yet
well understood. More research is needed to
determine the best sonic representation of data.
– There is no standard sound hardware and
software platform.
Sound
Some recommendations for using
sound in algorithm visualization
– Carefully consider the number of sounds.
• Use only a few sounds for the most important or
difficult events/commands.
• The threshold for learning and remembering sounds
is between 7 and 9 different sounds.
Sound
Some recommendations for using
sound in algorithm visualization
– Test your algorithm visualization with a range
of users to ensure that the selected sounds are
effective.
– Graphical display results should be
synchronized with the audio.
3-D
• Do not use 3D for enhancing the beauty of a
picture that is easily shown in 2D.
• Use 3D displays to:
– represent the 3-dimensional data some
algorithms manipulate
– provide an extra dimension to represent more
information about two-dimensional data.
3-D
3-D can give us one more dimension
12
5
3
10
7
4
9
9
2
12
2-D Display
8
5
10
5
7
15
10
5
0
1
2
3
4
5
3-D Display:
direct visual comparison
of the elements
3-D
Some techniques that may be used in
crafting 3-dimensional visualizations
–
–
–
–
Rotation
Transparency
Navigation
Exploration of objects
3-D
Attention should be paid to choosing:
– the axis of rotation,
– the speed of rotation.
The orientation and rotation speed should be
saved each time there is a pause in animation.
3-D
Transparency
– Very complicated 3D objects may be best
understood if the user can interact with them
and inspect their contents.
– Make the object transparent.
– Use transparency with care, otherwise, there
may be too much detail.
3-D
Transparency
– To avoid overload, make only selected portions
of an object transparent. We can draw the
viewer’s attention only to the important parts of
an object.
– An ideal interface will allow the user to look
inside an object by:
• cutting it open
• slicing it along a selected plane
• breaking it apart at natural boundaries and
separating pieces for further examination.
Interaction
• Visualizations are more effective when the
user can steer them in appropriate
directions.
• Algorithm visualizations should allow for
interactive controls.
• Users should be forced to interact with the
system at least every 45 seconds.
Interaction
Some of the varieties of interaction an
algorithm visualization system can utilize:
– Allowing the user to step through the execution or
set its speed,
– Allowing the user to design input data for the
algorithm
• tools for inputting data should be simple so as not to
overwhelm the user,
• input tools should do error checking and report any
invalid input to the user.
Interaction
Other forms of interaction
– Allowing the user to control the presentation and
amount of information:
• Facility to hide one or more of the multiple views.
• Facilities to zoom in and out.
• Means for changing the data while the algorithm runs,
e.g., by dragging a data point to a different location
and watching the effect of this change,
– not suitable for some algorithms, e.g. sort algorithms
Interaction
Other forms of interaction
– Allowing the user to simultaneously run several
algorithms to compare and contrast them.
• This capability is useful for comparing the execution
times of two algorithms by running a race.
• Note, that modern windowing environments and
operating systems will allow almost any window-based
visualization system to be run in parallel.
– Running two versions of algorithm visualization in different
windows would not qualify under this category because there
is no centralized control or synchronization between both
running visualizations.
Interaction
Other forms of interaction
– Allowing the user to step back in the algorithm
visualization.
– Allowing the user to design his/her own
visualizations.
Interaction
Other forms of interaction
– Allowing the user to check his/her
understanding by answering stop-and-think
questions:
• if the feedback from the interaction is sluggish such
that users’ actions and their feedback become
unrelated, then this type of interaction fails.
4. Evaluation
Over one hundred different algorithm
visualization tools have been built in the last
twenty years, yet very few of these were
systematically evaluated.
Evaluation
There are some difficulties which arise
when performing a formal evaluation
study:
–
–
–
–
–
Obviously, evaluation takes time.
Which visualization should we use for testing?
How do we measure program understanding?
Which criteria should we use?
How do we properly and fairly conduct the study?
Conclusion
• So far, we have only informal evidence that
applications of algorithm visualizations are
useful - we need controlled studies:
– need to conduct formal studies of applications
in classroom settings and use the result to
influence the next generation of tools.
Conclusion
• Creating good educational algorithm
visualizations is time consuming and
generally requires a team of developers with
different skills.
• Think about distribution and maintenance of
your new algorithm visualization system.
Conclusion
Distribution issues
– Make it possible for other educators to try your
tool.
• Put the tool on the web.
– Educational algorithm visualizations are shifting
toward web-based design:
• It simplifies installation and platform compatibility.
• It provides immediacy of access.
• It allows them to be incorporated into electronic
textbooks.
Conclusion
Maintenance issues
– There is increasing demand for more
functionality in algorithm visualizations which
results in larger programs.
– Turnover in the development and support
community is great; development tools become
obsolete; source code is even lost.
– All this makes maintenance very difficult and
important.
Conclusion
• Color, sound, and 3-D graphics do not
merely enhance the beauty of presentation;
they can be used to give fundamental
information.
• Designing effective dynamic algorithm
visualizations is a craft, not a science.
Kiitos!