Transcript Increasing Interaction and Visualization in the Computability Course

A Visual & Interactive Computability
Course Emphasizing Breadth of
Automata
Rakesh Verma
Computer Science Department
University of Houston
http://www.cs.uh.edu/~rmverma
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Outline
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The problem
Proposed solution
Teaching experience summary
Conclusions & future work
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The Problem
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Learning and teaching Automata Theory
are challenging tasks
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Abstract, difficult material
Considerable creativity required
Slow feedback in traditional format
Student perceptions make it worse
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Dated material, of little use
Dry at best and boring/frustrating at worst
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Challenges Specific to UH
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Large, urban institution with a mature
and diverse student population
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Some loss of mathematical knowledge
Significant number of working students
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In-school tutorial sessions difficult
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Goals
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Enhance learning and learning
experience by increasing: visualization,
interaction, and faster feedback
Expose students to:
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A variety of automata
Applications, especially recent ones
Historical background and development
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Proposed Solution
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Complete revision of course contents
and teaching with:
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integration of enhanced JFLAP (Duke U.)
and LRR (UH)
variety of automata, e.g., tree and DAG
automata
recent and classical applications of
automata
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Solution (contd.)
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We have developed:
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Power point slides for lectures including
JFLAP animations (LRR animations in F05)
New problem sets requiring use of these
tools
Notes on tree automata and DAG automata
Web site:
http://www2.cs.uh.edu/~rmverma/3340ne
w/html/index.html
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LRR and its advantages
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LRR – input is a set of rules and an
expression
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Each rule is l  r, where l and r are expressions
with variables and operators
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Example: x + 0  x and x + -x  0
Applies rules via matching to given expression
LRR can implement any computation
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A Turing machine can be encoded via just one
rule!
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Visualizing Tree Automata
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Instead of developing another package
we use LRR with RuleMaker – a
graphical interface
DFA example:
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a(q0)  q0
b(q0)  q1
Final(q0)  true
Final(b(a(q0))?
a(q1)  q1
b(q1)  q0
Final(q1)  false
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Examples (contd.)
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NFA can be simulated as below:
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a(a(q1))  q2 (string) q0  q1 (epsilon)
Tree automaton example:
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true  q0
and(q0, q0)  q0
and(q1, q0)  q1
false  q1
and(q0, q1)  q1
and(q1, q1)  q1
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UH Enhancements to JFLAP
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“Debug” feature – students can
generate strings at random and find the
results for all the strings
Equivalence checking for DFA’s (this is
now part of JFLAP version 4.0)
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Preliminary Results
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Students participating in special
problems and projects on automata
5
4
3
Students
2
1
0
1990-98 (7s.)
2002-04 (5s.)
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Prel. Results (contd.)
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Positive feedback on surveys regarding
JFLAP/JFLAP++ and web-site materials
Students from this course showed
improved performance on subsequent
compilers course compared to
traditional versions taught by other
faculty
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Conclusions
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Automata theory can be made
interesting and easier
Visualization is helpful
Interaction is key – during lectures and
outside class
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Future Work
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Rigorous comparison with “traditional”
automata courses
Further development of materials on
breadth and applications of automata
A drastic revision of course contents …
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Acknowledgements
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Students
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Saquib Hakim (JFLAP++ and slides)
Mohammad Anwar (web site)
Pavan Podila and Patrick Sharkey (RuleMaker)
James Thigpen (integration with LRR)
Sponsor: National Science Foundation
The students who have enjoyed/suffered
through my course!
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Thank You!
?’s or !’s
For more info:
http://www2.cs.uh.edu/~rmverma/334
0new/html/index.html
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