Start: start
Program_Vars: Arg_0, Arg_1
Temp_Vars:
Locations: eval, start
Transitions:
0:eval(Arg_0,Arg_1) -> eval(Arg_0-1,Arg_1):|:1<=Arg_0 && Arg_0<=Arg_1
1:eval(Arg_0,Arg_1) -> eval(Arg_1,Arg_1):|:1<=Arg_0 && Arg_1+1<=Arg_0
2:start(Arg_0,Arg_1) -> eval(Arg_0,Arg_1)
Start: start
Program_Vars: Arg_0, Arg_1
Temp_Vars:
Locations: eval, start
Transitions:
0:eval(Arg_0,Arg_1) -> eval(Arg_0-1,Arg_1):|:1<=Arg_0 && Arg_0<=Arg_1
1:eval(Arg_0,Arg_1) -> eval(Arg_1,Arg_1):|:1<=Arg_0 && Arg_1+1<=Arg_0
2:start(Arg_0,Arg_1) -> eval(Arg_0,Arg_1)
knowledge_propagation leads to new time bound 1 {O(1)} for transition 1:eval(Arg_0,Arg_1) -> eval(Arg_1,Arg_1):|:1<=Arg_0 && Arg_1+1<=Arg_0
new bound:
Arg_0 {O(n)}
MPRF:
eval [Arg_0 ]
Overall timebound:Arg_0+2 {O(n)}
0: eval->eval: Arg_0 {O(n)}
1: eval->eval: 1 {O(1)}
2: start->eval: 1 {O(1)}
Overall costbound: Arg_0+2 {O(n)}
0: eval->eval: Arg_0 {O(n)}
1: eval->eval: 1 {O(1)}
2: start->eval: 1 {O(1)}
0: eval->eval, Arg_0: Arg_0+Arg_1 {O(n)}
0: eval->eval, Arg_1: 2*Arg_1 {O(n)}
1: eval->eval, Arg_0: Arg_1 {O(n)}
1: eval->eval, Arg_1: Arg_1 {O(n)}
2: start->eval, Arg_0: Arg_0 {O(n)}
2: start->eval, Arg_1: Arg_1 {O(n)}