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7. Implementation
Plan
•   Firing a transition
•   Evaluating a state predicate
•   Managing the state space
•   Organizing search
•   Detecting strongly connected components
Firing transitions
Marking changed via list of pre-, list of post-
places  effort does not depend on size of
net
After firing, only some transitions are checked
for enabledness
   previously enabled transitions that lost
   tokens
   previously disabled transitions that gained
   tokens
      ... managed through explicitly stored lists


   
         
       
   
         
     
   

Checking state predicates
• predicate = boolean combination of
     • p {><=≤≥≠} k

• stored in negation-free normal form

                                            φ



  φ                                     φ
            φ          φ

      
        

Managing the state space
1st state = bit vector

     




















   






   



   




   























   







other states = bit vector +decision record
 
               

Managing the state space
  find/insert a marking: one integrated process



  




















   






   



   




   























   





  dive down into decision tree
  on mismatch:
                  at decision point: switch to next vector
                  at end: found, no insert

        

                  between decision points: insert at point of mismatch




  decision records form tree
Organizing search
   General remarks

Search consists of

 - fire transitions ✔

 - find/insert marking ✔
 
 - backtracking: fire transition backwards

 
          only „constant“ time

 
         search stack consists of reference to
   transition +

 
            list of enabled transitions

 
          state space is „write-only“ memory
Organizing search
b) Depth-first search: ability to detect SCC
c) Breadth-first search:

Simulated by bounded depth-first search with
   incrementally increased bound

 Update of current marking, list of enabled
  transitions, etc. through sequence of transition
  occurrences
Detecting strongly connected
            components
    • Traditional approach: Tarjan‘s algorithm
         4                                         
        

4            6            21
5                                            
 
        
                 
 
 
 

             44                






 
               
                
      

    33               11        






 
 
     
                
          
     
   


             00                        
 
         
                
   
 

     

                                                                
             

             

                 

         

Detecting strongly connected
            components
    • LoLA approach: simplified lowlink

         4                                           
        

4            6            21
5                                            
 
          
             
 
 
 

             41                






 
                 
            
      

    31               11        






 
 
       
                
      
     
            


             00                         
 
                       
   
           
   
 

     

                                    
            
                

             

                                             
       
                    
   
             

                 

                               
                     

         

Reduction techniques
Stubborn Sets
  • Crucial: Core principle
  • Simple method:
     – If t enabled, add conflicting transitions
     – If t disabled, add pre-transitions of some
       unmarked pre-place

 place       pre-transitions

             must be included
transition   conflicting

             updated at enabledness check
The sweep-line method
• constant change  successors lie in a small window of
  progress values
                                      





        

                                                  

                                                      

Calculation of Symmetries
     7 5                          0 2        A1 ∪.... ∪ An = V
A1                                      B1
              9               4              B1 ∪....∪ Bn = V

A2 1 4                        3
                  2               6 B2       σ satisfies C        iff
     6                        9 8
                                             σ(Ai) = Bi (for all i)
                                                    07
      3                       7         B3          13
A3            0                                     29
                                   5                35
                                                    48
                      .....                         50
                                                    66
An                                      Bn
          8                        1                74
                                                    81
                                                    92
                       C
Abstract Permutation – Examples
Abstract Permutation – Examples

PP                      all permutations that
TT                      respect node type
Abstract Permutation – Examples

PP                              all permutations that
TT                              respect node type



{p1}  {p1}
   ......         Elements of some orbit
{pi-1}  {pi-1}   wrt. Ui in Ui-1
{pi}  {pk}
others1  others2
Abstract Permutation – Examples

 PP                                   all permutations that
 TT                                   respect node type



  {p1}  {p1}
     ......         Elements of some orbit
  {pi-1}  {pi-1}   wrt. Ui in Ui-1
  {pi}  {pk}
  others1  others2

New problem: given.: abstract permutation C
compute an automorphism that satisfies C

... equivalent to graph isomorphism
REFINE
        Choose A-B, A’-B’ and arc multiplicity c

    # c-neighbors in A’                           #c-neighbors in B’
    3    2     1        0                         0     1       2                    3
A                                                                                        B
                         8        9                        8           6
             6                                1
                     0                             5                        4    2
    1            2           4       3                 7       0




                                                               8           7
                     2           5                     4                        B’
        A’       1                                                 0
                          3
REFINE
         Choose A-B, A’-B’ and arc multiplicity c

     # c-neighbors in A’                           #c-neighbors in B’
     3    2     1        0                         0     1       2                    3
A                                                                                         B
                          8        9                        8           6
              6                                1
                      0                             5                        4    2
     1            2           4       3                 7       0




                                                                8           7
                      2           5                     4                        B’
         A’       1                                                 0
                           3
    Every automorphism that satisfies A-B, satisfies all resulting
    constraints
DEFINE
Choose A-B,
p ∈A          2 5        1 2
               3 8       4 5
DEFINE
Choose A-B,
p ∈A          2 5        1 2
               3 8       4 5



 2 5          1 2             2 5    1 2
  3 8         4 5              3 8   4 5



 2 5          1 2             2 5    1 2
  3 8         4 5              3 8   4 5
DEFINE
Choose A-B,
p ∈A               2 5                 1 2
                    3 8                4 5



  2 5              1 2                  2 5    1 2
   3 8             4 5                   3 8   4 5



  2 5              1 2                  2 5    1 2
   3 8             4 5                   3 8   4 5

Every automorphism tat satisfies A-B,
satisfies one of the new constraints
Computation tree

                                     4                   3
                                                 2

poly
                                 1       8           1
                                     6                   7 8
                                                               5


                                     a       b           f a
                                         e                c



                                                 R*
                                                 D
               R*                                R*                         R*
               D                                 D
   R*            R*         R*                   R*                R*

                        2            3                         2        3


                        3            8                         3        8



                        c            c                         c        c



                                                 exp
 = #Ai ! #Bi          is rare. That is, often polynomial run time
Combination of techniques
                               
 
      

                   
       



        







 
         
 
           
   

        















       
       
 

        















          

    
   
















        








        















 
               
 
     

        















            
 

        















 

        
























        

        
























          
     


       
















        

























        





        







More information
•   LoLA: ICATPN 2000, Petri Nets 2007
     – www.informatik.uni-rostock.de/tpp/

•   Stubborn sets: ICATPN 1999, Fundamenta Informaticae 2000, FMSD 2006
•   Symmetries: Acta Informatica 2000, TACAS 2000
•   Linear Algebra: TACAS 2003
•   Sweep-Line: TACAS 2004, STTT

•   Coverability graphs: FMSD 1999

•   Services: BPM 2005
•   GALS: ASYNC Krstic et al, 2005
•   Bio-chemistry: Talcott & Dill, 2005
•   Workflow: BPM 2009

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Verification with LoLA: 7 Implementation

  • 2. Plan • Firing a transition • Evaluating a state predicate • Managing the state space • Organizing search • Detecting strongly connected components
  • 3. Firing transitions Marking changed via list of pre-, list of post- places  effort does not depend on size of net After firing, only some transitions are checked for enabledness previously enabled transitions that lost tokens previously disabled transitions that gained tokens ... managed through explicitly stored lists 
 
 
 
 
 
 
 

  • 4. Checking state predicates • predicate = boolean combination of • p {><=≤≥≠} k • stored in negation-free normal form φ φ φ φ φ 
 

  • 5. Managing the state space 1st state = bit vector 




















 






 



 




 























 


 other states = bit vector +decision record 
 

  • 6. Managing the state space find/insert a marking: one integrated process 




















 






 



 




 























 


 dive down into decision tree on mismatch: at decision point: switch to next vector at end: found, no insert 
 
 between decision points: insert at point of mismatch decision records form tree
  • 7. Organizing search General remarks Search consists of - fire transitions ✔ - find/insert marking ✔ - backtracking: fire transition backwards  only „constant“ time search stack consists of reference to transition + list of enabled transitions  state space is „write-only“ memory
  • 8. Organizing search b) Depth-first search: ability to detect SCC c) Breadth-first search: Simulated by bounded depth-first search with incrementally increased bound  Update of current marking, list of enabled transitions, etc. through sequence of transition occurrences
  • 9. Detecting strongly connected components • Traditional approach: Tarjan‘s algorithm 4 
 
 4 6 21 5 
 
 
 
 
 
 
 44 






 
 
 
 
 33 11 






 
 
 
 
 
 
 
 00 
 
 
 
 
 
 
 
 
 
 
 

  • 10. Detecting strongly connected components • LoLA approach: simplified lowlink 4 
 
 4 6 21 5 
 
 
 
 
 
 
 41 






 
 
 
 
 31 11 






 
 
 
 
 
 
 
 00 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

  • 12. Stubborn Sets • Crucial: Core principle • Simple method: – If t enabled, add conflicting transitions – If t disabled, add pre-transitions of some unmarked pre-place place pre-transitions must be included transition conflicting updated at enabledness check
  • 13. The sweep-line method • constant change  successors lie in a small window of progress values 
 
 
 

  • 14. Calculation of Symmetries 7 5 0 2 A1 ∪.... ∪ An = V A1 B1 9 4 B1 ∪....∪ Bn = V A2 1 4 3 2 6 B2 σ satisfies C iff 6 9 8 σ(Ai) = Bi (for all i) 07 3 7 B3 13 A3 0 29 5 35 48 ..... 50 66 An Bn 8 1 74 81 92 C
  • 16. Abstract Permutation – Examples PP all permutations that TT respect node type
  • 17. Abstract Permutation – Examples PP all permutations that TT respect node type {p1}  {p1} ...... Elements of some orbit {pi-1}  {pi-1} wrt. Ui in Ui-1 {pi}  {pk} others1  others2
  • 18. Abstract Permutation – Examples PP all permutations that TT respect node type {p1}  {p1} ...... Elements of some orbit {pi-1}  {pi-1} wrt. Ui in Ui-1 {pi}  {pk} others1  others2 New problem: given.: abstract permutation C compute an automorphism that satisfies C ... equivalent to graph isomorphism
  • 19. REFINE Choose A-B, A’-B’ and arc multiplicity c # c-neighbors in A’ #c-neighbors in B’ 3 2 1 0 0 1 2 3 A B 8 9 8 6 6 1 0 5 4 2 1 2 4 3 7 0 8 7 2 5 4 B’ A’ 1 0 3
  • 20. REFINE Choose A-B, A’-B’ and arc multiplicity c # c-neighbors in A’ #c-neighbors in B’ 3 2 1 0 0 1 2 3 A B 8 9 8 6 6 1 0 5 4 2 1 2 4 3 7 0 8 7 2 5 4 B’ A’ 1 0 3 Every automorphism that satisfies A-B, satisfies all resulting constraints
  • 21. DEFINE Choose A-B, p ∈A 2 5 1 2 3 8 4 5
  • 22. DEFINE Choose A-B, p ∈A 2 5 1 2 3 8 4 5 2 5 1 2 2 5 1 2 3 8 4 5 3 8 4 5 2 5 1 2 2 5 1 2 3 8 4 5 3 8 4 5
  • 23. DEFINE Choose A-B, p ∈A 2 5 1 2 3 8 4 5 2 5 1 2 2 5 1 2 3 8 4 5 3 8 4 5 2 5 1 2 2 5 1 2 3 8 4 5 3 8 4 5 Every automorphism tat satisfies A-B, satisfies one of the new constraints
  • 24. Computation tree 4 3 2 poly 1 8 1 6 7 8 5 a b f a e c R* D R* R* R* D D R* R* R* R* R* 2 3 2 3 3 8 3 8 c c c c exp = #Ai ! #Bi is rare. That is, often polynomial run time
  • 25. Combination of techniques 
 
 
 
 
 







 
 
 
 
 
 















 
 
 
 















 
 
 















 







 















 
 
 
 
 















 
 
 















 
 
























 
 
























 
 
 
 















 
























 




 







  • 26. More information • LoLA: ICATPN 2000, Petri Nets 2007 – www.informatik.uni-rostock.de/tpp/ • Stubborn sets: ICATPN 1999, Fundamenta Informaticae 2000, FMSD 2006 • Symmetries: Acta Informatica 2000, TACAS 2000 • Linear Algebra: TACAS 2003 • Sweep-Line: TACAS 2004, STTT • Coverability graphs: FMSD 1999 • Services: BPM 2005 • GALS: ASYNC Krstic et al, 2005 • Bio-chemistry: Talcott & Dill, 2005 • Workflow: BPM 2009

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