/export/starexec/sandbox2/solver/bin/starexec_run_complexity /export/starexec/sandbox2/benchmark/theBenchmark.koat /export/starexec/sandbox2/output/output_files -------------------------------------------------------------------------------- WORST_CASE(Omega(n^1), O(n^1)) proof of /export/starexec/sandbox2/benchmark/theBenchmark.koat # AProVE Commit ID: 48fb2092695e11cc9f56e44b17a92a5f88ffb256 marcel 20180622 unpublished dirty The runtime complexity of the given CpxIntTrs could be proven to be BOUNDS(n^1, max(1, 1 + Arg_0 + -1 * Arg_2) + nat(Arg_0 + -1 * Arg_1)). (0) CpxIntTrs (1) Koat2 Proof [FINISHED, 217 ms] (2) BOUNDS(1, max(1, 1 + Arg_0 + -1 * Arg_2) + nat(Arg_0 + -1 * Arg_1)) (3) Loat Proof [FINISHED, 545 ms] (4) BOUNDS(n^1, INF) ---------------------------------------- (0) Obligation: Complexity Int TRS consisting of the following rules: eval(A, B, C) -> Com_1(eval(A, B + 1, C)) :|: A >= B + 1 && C >= B + 1 eval(A, B, C) -> Com_1(eval(A, B, C + 1)) :|: A >= B + 1 && B >= C start(A, B, C) -> Com_1(eval(A, B, C)) :|: TRUE The start-symbols are:[start_3] ---------------------------------------- (1) Koat2 Proof (FINISHED) YES( ?, 1+max([0, Arg_0-Arg_2])+max([0, Arg_0-Arg_1]) {O(n)}) Initial Complexity Problem: Start: start Program_Vars: Arg_0, Arg_1, Arg_2 Temp_Vars: Locations: eval, start Transitions: eval(Arg_0,Arg_1,Arg_2) -> eval(Arg_0,Arg_1+1,Arg_2):|:Arg_1+1 <= Arg_0 && Arg_1+1 <= Arg_2 eval(Arg_0,Arg_1,Arg_2) -> eval(Arg_0,Arg_1,Arg_2+1):|:Arg_1+1 <= Arg_0 && Arg_2 <= Arg_1 start(Arg_0,Arg_1,Arg_2) -> eval(Arg_0,Arg_1,Arg_2):|: Timebounds: Overall timebound: 1+max([0, Arg_0-Arg_2])+max([0, Arg_0-Arg_1]) {O(n)} 0: eval->eval: max([0, Arg_0-Arg_1]) {O(n)} 1: eval->eval: max([0, Arg_0-Arg_2]) {O(n)} 2: start->eval: 1 {O(1)} Costbounds: Overall costbound: 1+max([0, Arg_0-Arg_2])+max([0, Arg_0-Arg_1]) {O(n)} 0: eval->eval: max([0, Arg_0-Arg_1]) {O(n)} 1: eval->eval: max([0, Arg_0-Arg_2]) {O(n)} 2: start->eval: 1 {O(1)} Sizebounds: `Lower: 0: eval->eval, Arg_0: Arg_0 {O(n)} 0: eval->eval, Arg_1: Arg_1 {O(n)} 0: eval->eval, Arg_2: Arg_2 {O(n)} 1: eval->eval, Arg_0: Arg_0 {O(n)} 1: eval->eval, Arg_1: Arg_1 {O(n)} 1: eval->eval, Arg_2: Arg_2 {O(n)} 2: start->eval, Arg_0: Arg_0 {O(n)} 2: start->eval, Arg_1: Arg_1 {O(n)} 2: start->eval, Arg_2: Arg_2 {O(n)} `Upper: 0: eval->eval, Arg_0: Arg_0 {O(n)} 0: eval->eval, Arg_1: Arg_1+max([0, Arg_0-Arg_1]) {O(n)} 0: eval->eval, Arg_2: Arg_2+max([0, Arg_0-Arg_2]) {O(n)} 1: eval->eval, Arg_0: Arg_0 {O(n)} 1: eval->eval, Arg_1: Arg_1+max([0, Arg_0-Arg_1]) {O(n)} 1: eval->eval, Arg_2: Arg_2+max([0, Arg_0-Arg_2]) {O(n)} 2: start->eval, Arg_0: Arg_0 {O(n)} 2: start->eval, Arg_1: Arg_1 {O(n)} 2: start->eval, Arg_2: Arg_2 {O(n)} ---------------------------------------- (2) BOUNDS(1, max(1, 1 + Arg_0 + -1 * Arg_2) + nat(Arg_0 + -1 * Arg_1)) ---------------------------------------- (3) Loat Proof (FINISHED) ### Pre-processing the ITS problem ### Initial linear ITS problem Start location: start 0: eval -> eval : B'=1+B, [ A>=1+B && C>=1+B ], cost: 1 1: eval -> eval : C'=1+C, [ A>=1+B && B>=C ], cost: 1 2: start -> eval : [], cost: 1 ### Simplification by acceleration and chaining ### Accelerating simple loops of location 0. Accelerating the following rules: 0: eval -> eval : B'=1+B, [ A>=1+B && C>=1+B ], cost: 1 1: eval -> eval : C'=1+C, [ A>=1+B && B>=C ], cost: 1 Accelerated rule 0 with backward acceleration, yielding the new rule 3. Accelerated rule 0 with backward acceleration, yielding the new rule 4. Accelerated rule 1 with metering function 1-C+B, yielding the new rule 5. Removing the simple loops: 0 1. Accelerated all simple loops using metering functions (where possible): Start location: start 3: eval -> eval : B'=A, [ A>=1+B && C>=1+B && C>=A ], cost: A-B 4: eval -> eval : B'=C, [ A>=1+B && C>=1+B && A>=C ], cost: C-B 5: eval -> eval : C'=1+B, [ A>=1+B && B>=C ], cost: 1-C+B 2: start -> eval : [], cost: 1 Chained accelerated rules (with incoming rules): Start location: start 2: start -> eval : [], cost: 1 6: start -> eval : B'=A, [ A>=1+B && C>=1+B && C>=A ], cost: 1+A-B 7: start -> eval : B'=C, [ A>=1+B && C>=1+B && A>=C ], cost: 1+C-B 8: start -> eval : C'=1+B, [ A>=1+B && B>=C ], cost: 2-C+B Removed unreachable locations (and leaf rules with constant cost): Start location: start 6: start -> eval : B'=A, [ A>=1+B && C>=1+B && C>=A ], cost: 1+A-B 7: start -> eval : B'=C, [ A>=1+B && C>=1+B && A>=C ], cost: 1+C-B 8: start -> eval : C'=1+B, [ A>=1+B && B>=C ], cost: 2-C+B ### Computing asymptotic complexity ### Fully simplified ITS problem Start location: start 6: start -> eval : B'=A, [ A>=1+B && C>=1+B && C>=A ], cost: 1+A-B 7: start -> eval : B'=C, [ A>=1+B && C>=1+B && A>=C ], cost: 1+C-B 8: start -> eval : C'=1+B, [ A>=1+B && B>=C ], cost: 2-C+B Computing asymptotic complexity for rule 6 Solved the limit problem by the following transformations: Created initial limit problem: C-B (+/+!), 1+C-A (+/+!), 1+A-B (+), A-B (+/+!) [not solved] removing all constraints (solved by SMT) resulting limit problem: [solved] applying transformation rule (C) using substitution {C==0,A==0,B==-n} resulting limit problem: [solved] Solution: C / 0 A / 0 B / -n Resulting cost 1+n has complexity: Poly(n^1) Found new complexity Poly(n^1). Obtained the following overall complexity (w.r.t. the length of the input n): Complexity: Poly(n^1) Cpx degree: 1 Solved cost: 1+n Rule cost: 1+A-B Rule guard: [ A>=1+B && C>=1+B && C>=A ] WORST_CASE(Omega(n^1),?) ---------------------------------------- (4) BOUNDS(n^1, INF)