YES(?,O(n^1)) * Step 1: UnsatPaths WORST_CASE(?,O(n^1)) + Considered Problem: Rules: 0. start(A,B) -> eval(A,B) True (1,1) 1. eval(A,B) -> eval(A,-1 + B) [B >= 1 && 1 + B >= 0 && A >= B] (?,1) 2. eval(A,B) -> eval(A,0) [A >= 1 && B = 1] (?,1) 3. eval(A,B) -> eval(A,A) [B >= 1 && 1 + B >= 0 && B >= 1 + A] (?,1) 4. eval(A,B) -> eval(A,A) [0 >= A && B = 1] (?,1) Signature: {(eval,2);(start,2)} Flow Graph: [0->{1,2,3,4},1->{1,2,3,4},2->{1,2,3,4},3->{1,2,3,4},4->{1,2,3,4}] + Applied Processor: UnsatPaths + Details: We remove following edges from the transition graph: [(1,3) ,(1,4) ,(2,1) ,(2,2) ,(2,3) ,(2,4) ,(3,3) ,(3,4) ,(4,1) ,(4,2) ,(4,3) ,(4,4)] * Step 2: PolyRank WORST_CASE(?,O(n^1)) + Considered Problem: Rules: 0. start(A,B) -> eval(A,B) True (1,1) 1. eval(A,B) -> eval(A,-1 + B) [B >= 1 && 1 + B >= 0 && A >= B] (?,1) 2. eval(A,B) -> eval(A,0) [A >= 1 && B = 1] (?,1) 3. eval(A,B) -> eval(A,A) [B >= 1 && 1 + B >= 0 && B >= 1 + A] (?,1) 4. eval(A,B) -> eval(A,A) [0 >= A && B = 1] (?,1) Signature: {(eval,2);(start,2)} Flow Graph: [0->{1,2,3,4},1->{1,2},2->{},3->{1,2},4->{}] + Applied Processor: PolyRank {useFarkas = True, withSizebounds = [], shape = Linear} + Details: We apply a polynomial interpretation of shape linear: p(eval) = x2 p(start) = x2 Following rules are strictly oriented: [0 >= A && B = 1] ==> eval(A,B) = B > A = eval(A,A) Following rules are weakly oriented: True ==> start(A,B) = B >= B = eval(A,B) [B >= 1 && 1 + B >= 0 && A >= B] ==> eval(A,B) = B >= -1 + B = eval(A,-1 + B) [A >= 1 && B = 1] ==> eval(A,B) = B >= 0 = eval(A,0) [B >= 1 && 1 + B >= 0 && B >= 1 + A] ==> eval(A,B) = B >= A = eval(A,A) * Step 3: KnowledgePropagation WORST_CASE(?,O(n^1)) + Considered Problem: Rules: 0. start(A,B) -> eval(A,B) True (1,1) 1. eval(A,B) -> eval(A,-1 + B) [B >= 1 && 1 + B >= 0 && A >= B] (?,1) 2. eval(A,B) -> eval(A,0) [A >= 1 && B = 1] (?,1) 3. eval(A,B) -> eval(A,A) [B >= 1 && 1 + B >= 0 && B >= 1 + A] (?,1) 4. eval(A,B) -> eval(A,A) [0 >= A && B = 1] (B,1) Signature: {(eval,2);(start,2)} Flow Graph: [0->{1,2,3,4},1->{1,2},2->{},3->{1,2},4->{}] + Applied Processor: KnowledgePropagation + Details: We propagate bounds from predecessors. * Step 4: PolyRank WORST_CASE(?,O(n^1)) + Considered Problem: Rules: 0. start(A,B) -> eval(A,B) True (1,1) 1. eval(A,B) -> eval(A,-1 + B) [B >= 1 && 1 + B >= 0 && A >= B] (?,1) 2. eval(A,B) -> eval(A,0) [A >= 1 && B = 1] (?,1) 3. eval(A,B) -> eval(A,A) [B >= 1 && 1 + B >= 0 && B >= 1 + A] (1,1) 4. eval(A,B) -> eval(A,A) [0 >= A && B = 1] (B,1) Signature: {(eval,2);(start,2)} Flow Graph: [0->{1,2,3,4},1->{1,2},2->{},3->{1,2},4->{}] + Applied Processor: PolyRank {useFarkas = True, withSizebounds = [], shape = Linear} + Details: We apply a polynomial interpretation of shape linear: p(eval) = x2 p(start) = x2 Following rules are strictly oriented: [A >= 1 && B = 1] ==> eval(A,B) = B > 0 = eval(A,0) [B >= 1 && 1 + B >= 0 && B >= 1 + A] ==> eval(A,B) = B > A = eval(A,A) [0 >= A && B = 1] ==> eval(A,B) = B > A = eval(A,A) Following rules are weakly oriented: True ==> start(A,B) = B >= B = eval(A,B) [B >= 1 && 1 + B >= 0 && A >= B] ==> eval(A,B) = B >= -1 + B = eval(A,-1 + B) * Step 5: PolyRank WORST_CASE(?,O(n^1)) + Considered Problem: Rules: 0. start(A,B) -> eval(A,B) True (1,1) 1. eval(A,B) -> eval(A,-1 + B) [B >= 1 && 1 + B >= 0 && A >= B] (?,1) 2. eval(A,B) -> eval(A,0) [A >= 1 && B = 1] (B,1) 3. eval(A,B) -> eval(A,A) [B >= 1 && 1 + B >= 0 && B >= 1 + A] (1,1) 4. eval(A,B) -> eval(A,A) [0 >= A && B = 1] (B,1) Signature: {(eval,2);(start,2)} Flow Graph: [0->{1,2,3,4},1->{1,2},2->{},3->{1,2},4->{}] + Applied Processor: PolyRank {useFarkas = True, withSizebounds = [], shape = Linear} + Details: We apply a polynomial interpretation of shape linear: p(eval) = 2 + x2 p(start) = 2 + x2 Following rules are strictly oriented: [B >= 1 && 1 + B >= 0 && A >= B] ==> eval(A,B) = 2 + B > 1 + B = eval(A,-1 + B) [A >= 1 && B = 1] ==> eval(A,B) = 2 + B > 2 = eval(A,0) [B >= 1 && 1 + B >= 0 && B >= 1 + A] ==> eval(A,B) = 2 + B > 2 + A = eval(A,A) [0 >= A && B = 1] ==> eval(A,B) = 2 + B > 2 + A = eval(A,A) Following rules are weakly oriented: True ==> start(A,B) = 2 + B >= 2 + B = eval(A,B) * Step 6: KnowledgePropagation WORST_CASE(?,O(n^1)) + Considered Problem: Rules: 0. start(A,B) -> eval(A,B) True (1,1) 1. eval(A,B) -> eval(A,-1 + B) [B >= 1 && 1 + B >= 0 && A >= B] (2 + B,1) 2. eval(A,B) -> eval(A,0) [A >= 1 && B = 1] (B,1) 3. eval(A,B) -> eval(A,A) [B >= 1 && 1 + B >= 0 && B >= 1 + A] (1,1) 4. eval(A,B) -> eval(A,A) [0 >= A && B = 1] (B,1) Signature: {(eval,2);(start,2)} Flow Graph: [0->{1,2,3,4},1->{1,2},2->{},3->{1,2},4->{}] + Applied Processor: KnowledgePropagation + Details: The problem is already solved. YES(?,O(n^1))