/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# AProVE Commit ID: 794c25de1cacf0d048858bcd21c9a779e1221865 marcel 20200619 unpublished dirty The runtime complexity of the given CpxIntTrs could be proven to be BOUNDS(n^1, max(1, 2 + Arg_0 + -1 * Arg_1)). (0) CpxIntTrs (1) Koat2 Proof [FINISHED, 124 ms] (2) BOUNDS(1, max(1, 2 + Arg_0 + -1 * Arg_1)) (3) Loat Proof [FINISHED, 110 ms] (4) BOUNDS(n^1, INF) ---------------------------------------- (0) Obligation: Complexity Int TRS consisting of the following rules: eval(A, B) -> Com_1(eval(A, B + 1)) :|: A >= B + 1 start(A, B) -> Com_1(eval(A, B)) :|: TRUE The start-symbols are:[start_2] ---------------------------------------- (1) Koat2 Proof (FINISHED) YES( ?, max([1, 2+Arg_0-Arg_1]) {O(n)}) Initial Complexity Problem: Start: start Program_Vars: Arg_0, Arg_1 Temp_Vars: Locations: eval, start Transitions: 0: eval->eval 1: start->eval Timebounds: Overall timebound: max([1, 2+Arg_0-Arg_1]) {O(n)} 0: eval->eval: max([0, 1+Arg_0-Arg_1]) {O(n)} 1: start->eval: 1 {O(1)} Costbounds: Overall costbound: max([1, 2+Arg_0-Arg_1]) {O(n)} 0: eval->eval: max([0, 1+Arg_0-Arg_1]) {O(n)} 1: 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)} 1: start->eval, Arg_0: Arg_0 {O(n)} 1: start->eval, Arg_1: Arg_1 {O(n)} `Upper: 0: eval->eval, Arg_0: Arg_0 {O(n)} 0: eval->eval, Arg_1: Arg_1+max([0, 1+Arg_0-Arg_1]) {O(n)} 1: start->eval, Arg_0: Arg_0 {O(n)} 1: start->eval, Arg_1: Arg_1 {O(n)} ---------------------------------------- (2) BOUNDS(1, max(1, 2 + 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 ], cost: 1 1: start -> eval : [], cost: 1 Checking for constant complexity: The following rule is satisfiable with cost >= 1, yielding constant complexity: 1: 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 ], cost: 1 Accelerated rule 0 with metering function A-B, yielding the new rule 2. Removing the simple loops: 0. Accelerated all simple loops using metering functions (where possible): Start location: start 2: eval -> eval : B'=A, [ A>=1+B ], cost: A-B 1: start -> eval : [], cost: 1 Chained accelerated rules (with incoming rules): Start location: start 1: start -> eval : [], cost: 1 3: start -> eval : B'=A, [ A>=1+B ], cost: 1+A-B Removed unreachable locations (and leaf rules with constant cost): Start location: start 3: start -> eval : B'=A, [ A>=1+B ], cost: 1+A-B ### Computing asymptotic complexity ### Fully simplified ITS problem Start location: start 3: start -> eval : B'=A, [ A>=1+B ], cost: 1+A-B Computing asymptotic complexity for rule 3 Solved the limit problem by the following transformations: Created initial limit problem: A-B (+/+!), 1+A-B (+) [not solved] removing all constraints (solved by SMT) resulting limit problem: [solved] applying transformation rule (C) using substitution {A==0,B==-n} resulting limit problem: [solved] Solution: 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 ] WORST_CASE(Omega(n^1),?) ---------------------------------------- (4) BOUNDS(n^1, INF)