Difference between revisions of "Jobs/M2 2015 ADL SAT-based Minimization"

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(Created page with "{{Job |Reference id=M2 2015 ADL SAT-based Minimization |Title=Minimization of Büchi automata using SAT-solving. |Dates=5-6 months in 2015 |Research field=Automata Theory |Rel...")
 
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To minimize a n-state deterministic Büchi automaton (an NP-complete problem) we encode its equivalence with a (n-1)-state deterministic
  
To minimize a n-state deterministic Büchi automaton (an NP-complete problem) we encode its equivalence with a (n-1)-state deterministic
 
Büchi automaton as a SAT problem, and let a SAT solver do the work of finding a solution. If such a solution is found, we try again, looking for a (n-2) state automaton, etc.
  
Büchi automaton as a SAT problem, and let a SAT solver do the work of finding a solution. If such a solution is found, we try again, looking for a (n-2) state automaton, etc.
−  
 
|Prerequisites=This internship targets students who:
  
|Prerequisites=This internship targets students who:
 
* have some experience in C++ programming and Unix development (experience with git would be a welcome bonus)
  
* have some experience in C++ programming and Unix development (experience with git would be a welcome bonus)
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* like to optimize
  
* like to optimize
 
* would like do get familiar with the amazing world of SAT-solvers and Büchi automata.
  
* would like do get familiar with the amazing world of SAT-solvers and Büchi automata.
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|Objectives=Presently, our first implementation saves the SAT problem as a huge file before calling the SAT-solver, and it does
  
|Objectives=Presently, our first implementation saves the SAT problem as a huge file before calling the SAT-solver, and it does
 
this for each iteration. The goal of this internship is to improve this situation in multiple ways:
  
this for each iteration. The goal of this internship is to improve this situation in multiple ways:
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In a second, step, we would like to generalize the existing technique to non-deterministic automata, or to different
  
In a second, step, we would like to generalize the existing technique to non-deterministic automata, or to different
 
types of acceptance conditions (i.e., not Büchi).
  
types of acceptance conditions (i.e., not Büchi).
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|References=* On the usage of a SAT-solver for minimization: https://www.lrde.epita.fr/~adl/dl/adl/baarir.14.forte.pdf
  
|References=* On the usage of a SAT-solver for minimization: https://www.lrde.epita.fr/~adl/dl/adl/baarir.14.forte.pdf
 
* For the present usage of SAT-based minimization in Spot: http://spot.lip6.fr/userdoc/satmin.html
  
* For the present usage of SAT-based minimization in Spot: http://spot.lip6.fr/userdoc/satmin.html
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|Contact=<adl at lrde . epita . fr>
  
|Contact=<adl at lrde . epita . fr>
 
|Compensation=1000 € gross/month
  
|Compensation=1000 € gross/month
  +
|Type=Master Internship
 
|Language=en
  
|Language=en
 
}}
  
}}

Revision as of 18:17, 29 October 2014

Minimization of Büchi automata using SAT-solving.
Reference id

M2 2015 ADL SAT-based Minimization

Dates

5-6 months in 2015

Research field

Automata Theory

Related project

Spot

Advisor

Alexandre Duret-Lutz

General presentation of the field

The Spot library (http://spot.lip6.fr/) contains many algorithms for translating LTL formulas into Büchi automata, and to simplify these formulas and automata. A recently added technique (in Spot version 1.2) allows us to minimize deterministic Büchi automata using a SAT-solver.

To minimize a n-state deterministic Büchi automaton (an NP-complete problem) we encode its equivalence with a (n-1)-state deterministic Büchi automaton as a SAT problem, and let a SAT solver do the work of finding a solution. If such a solution is found, we try again, looking for a (n-2) state automaton, etc.

Prerequisites

This internship targets students who:

  • have some experience in C++ programming and Unix development (experience with git would be a welcome bonus)
  • like to write clean and useful code (Spot is an open-source library used by other projects)
  • like to optimize
  • would like do get familiar with the amazing world of SAT-solvers and Büchi automata.
Objectives

Presently, our first implementation saves the SAT problem as a huge file before calling the SAT-solver, and it does this for each iteration. The goal of this internship is to improve this situation in multiple ways:

  • implement purely technical optimizations (like direct communication with the SAT solver, bypassing any temporary files)
  • take advantage of feature offered by modern SAT solvers (for instance an "incremental SAT-solver" can be given new constraints after it has found a solution, without needing to restart from scratch)
  • implement optimization to the encoding of the SAT-problem, based on structural properties of the automaton (we have some ideas)

In a second, step, we would like to generalize the existing technique to non-deterministic automata, or to different types of acceptance conditions (i.e., not Büchi).

Benefit for the candidate
References
Place LRDE: How to get to us
Compensation

1000 € gross/month

Future work opportunities
Contact

<adl at lrde . epita . fr> <adl at lrde . epita . fr>

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