WORST_CASE(Omega(1),?)

### Pre-processing the ITS problem ###

Initial linear ITS problem
   Start location: __init
      0: f1_0_main_New -> f73_0_m_GE : arg1'=arg1P_1, arg2'=arg2P_1, [ arg1P_1>1 && 0==arg2P_1 ], cost: 1
      1: f73_0_m_GE -> f73_0_m_GE : arg1'=arg1P_2, arg2'=arg2P_2, [ arg2<10 && arg2>-1 && -1+arg1P_2<=arg1 && arg1>0 && arg1P_2>0 && 2+arg2<=arg1 && 1+arg2==arg2P_2 ], cost: 1
      2: __init -> f1_0_main_New : arg1'=arg1P_3, arg2'=arg2P_3, [], cost: 1

Checking for constant complexity:
   The following rule is satisfiable with cost >= 1, yielding constant complexity:
      2: __init -> f1_0_main_New : arg1'=arg1P_3, arg2'=arg2P_3, [], cost: 1

Simplified all rules, resulting in:
   Start location: __init
      0: f1_0_main_New -> f73_0_m_GE : arg1'=arg1P_1, arg2'=0, [ arg1P_1>1 ], cost: 1
      1: f73_0_m_GE -> f73_0_m_GE : arg1'=arg1P_2, arg2'=1+arg2, [ arg2<10 && arg2>-1 && -1+arg1P_2<=arg1 && arg1>0 && arg1P_2>0 && 2+arg2<=arg1 ], cost: 1
      2: __init -> f1_0_main_New : arg1'=arg1P_3, arg2'=arg2P_3, [], cost: 1

### Simplification by acceleration and chaining ###

Accelerating simple loops of location 1.
   Accelerating the following rules:
      1: f73_0_m_GE -> f73_0_m_GE : arg1'=arg1P_2, arg2'=1+arg2, [ arg2<10 && arg2>-1 && -1+arg1P_2<=arg1 && arg1>0 && arg1P_2>0 && 2+arg2<=arg1 ], cost: 1

   Accelerated rule 1 with backward acceleration, yielding the new rule 3.
   Accelerated rule 1 with backward acceleration, yielding the new rule 4.
[accelerate] Nesting with 2 inner and 1 outer candidates
   Removing the simple loops: 1.

Accelerated all simple loops using metering functions (where possible):
   Start location: __init
      0: f1_0_main_New -> f73_0_m_GE : arg1'=arg1P_1, arg2'=0, [ arg1P_1>1 ], cost: 1
      3: f73_0_m_GE -> f73_0_m_GE : arg1'=arg1P_2, arg2'=10, [ arg2>-1 && -1+arg1P_2<=arg1 && arg1>0 && 10-arg2>=1 && 11<=arg1P_2 ], cost: 10-arg2
      4: f73_0_m_GE -> f73_0_m_GE : arg1'=arg1P_2, arg2'=-1+arg1P_2, [ arg2>-1 && -1+arg1P_2<=arg1 && arg1>0 && arg1P_2>0 && -1-arg2+arg1P_2>=1 && -2+arg1P_2<10 ], cost: -1-arg2+arg1P_2
      2: __init -> f1_0_main_New : arg1'=arg1P_3, arg2'=arg2P_3, [], cost: 1

Chained accelerated rules (with incoming rules):
   Start location: __init
      0: f1_0_main_New -> f73_0_m_GE : arg1'=arg1P_1, arg2'=0, [ arg1P_1>1 ], cost: 1
      5: f1_0_main_New -> f73_0_m_GE : arg1'=arg1P_2, arg2'=10, [ 11<=arg1P_2 ], cost: 11
      6: f1_0_main_New -> f73_0_m_GE : arg1'=arg1P_2, arg2'=-1+arg1P_2, [ -1+arg1P_2>=1 && -2+arg1P_2<10 ], cost: arg1P_2
      2: __init -> f1_0_main_New : arg1'=arg1P_3, arg2'=arg2P_3, [], cost: 1

Removed unreachable locations (and leaf rules with constant cost):
   Start location: __init
      6: f1_0_main_New -> f73_0_m_GE : arg1'=arg1P_2, arg2'=-1+arg1P_2, [ -1+arg1P_2>=1 && -2+arg1P_2<10 ], cost: arg1P_2
      2: __init -> f1_0_main_New : arg1'=arg1P_3, arg2'=arg2P_3, [], cost: 1

Eliminated locations (on linear paths):
   Start location: __init
      7: __init -> f73_0_m_GE : arg1'=arg1P_2, arg2'=-1+arg1P_2, [ -1+arg1P_2>=1 && -2+arg1P_2<10 ], cost: 1+arg1P_2

### Computing asymptotic complexity ###

Fully simplified ITS problem
   Start location: __init
      7: __init -> f73_0_m_GE : arg1'=arg1P_2, arg2'=-1+arg1P_2, [ -1+arg1P_2>=1 && -2+arg1P_2<10 ], cost: 1+arg1P_2

Computing asymptotic complexity for rule 7
   Resulting cost 0 has complexity: Unknown

Obtained the following overall complexity (w.r.t. the length of the input n):
   Complexity:  Constant
   Cpx degree:  0
   Solved cost: 1
   Rule cost:   1
   Rule guard:  []

WORST_CASE(Omega(1),?)