Inferring Expected Runtimes Using Sizes


KoAT2 Proof WORST_CASE( ?, 2*Arg_0 {O(n)})

Initial Complexity Problem (after preprocessing)

Start:f
Program_Vars:Arg_0
Temp_Vars:
Locations:f, g
Transitions:
f(Arg_0) -{0}> g(Arg_0)
g(Arg_0) -> 1/2:g(Arg_0-1) :+: 1/2:g(Arg_0-2) :|: 2<=Arg_0

G f f g g f->g t₀ ∈ g₀ {0} g->g t₁ ∈ g₁ p = 1/2 η (Arg_0) = Arg_0-1 τ = 2<=Arg_0 g->g t₂ ∈ g₁ p = 1/2 η (Arg_0) = Arg_0-2 τ = 2<=Arg_0

Timebounds:

Overall timebound:max([0, Arg_0])+max([1, 1+Arg_0]) {O(n)}
0,0: f->g: 1 {O(1)}
1,1: g->g: max([0, Arg_0]) {O(n)}
2,1: g->g: max([0, Arg_0]) {O(n)}

Expected Timebounds:

Overall expected timebound: 1+2*Arg_0 {O(n)}
0: f->[1:g]: 1 {O(1)}
1: g->[1/2:g; 1/2:g]: 2*Arg_0 {O(n)}

Costbounds:

Overall costbound: inf {Infinity}
0,0: f->g: inf {Infinity}
1,1: g->g: inf {Infinity}
2,1: g->g: inf {Infinity}

Expected Costbounds:

Overall expected costbound: 2*Arg_0 {O(n)}
0: f->[1:g]: 0 {O(1)}
1: g->[1/2:g; 1/2:g]: 2*Arg_0 {O(n)}

Sizebounds:

0,0: f->g, Arg_0: Arg_0 {O(n)}
1,1: g->g, Arg_0: Arg_0 {O(n)}
2,1: g->g, Arg_0: Arg_0 {O(n)}

ExpSizeBounds:

(0: f->[1:g], g), Arg_0: Arg_0 {O(n)}
(1: g->[1/2:g; 1/2:g], g), Arg_0: Arg_0 {O(n)}