Complexity

4 definitions found

From The Collaborative International Dictionary of English v.0.48 [gcide]:

  Complexity \Com*plex"i*ty\, n.; pl. {Complexities}. [Cf. F.
     complexit['e].]
     1. The state of being complex; intricacy; entanglement.
        [1913 Webster]
  
              The objects of society are of the greatest possible


              complexity.                           --Burke.
        [1913 Webster]
  
     2. That which is complex; intricacy; complication.
        [1913 Webster]
  
              Many-corridored complexities
              Of Arthur's palace.                   --Tennyson.
        [1913 Webster]

From WordNet (r) 2.0 [wn]:

  complexity
       n : the quality of being intricate and compounded; "he enjoyed
           the complexity of modern computers" [syn: {complexness}]
           [ant: {simplicity}]

From Moby Thesaurus II by Grady Ward, 1.0 [moby-thes]:

  31 Moby Thesaurus words for "complexity":
     abstruseness, arduousness, bothersomeness, burdensomeness,
     complication, convolution, crabbedness, crampedness, deepness,
     difficultness, difficulty, esoterica, hairiness, hardness,
     inscrutability, intricacy, involvement, knottiness, laboriousness,
     onerousness, oppressiveness, profoundness, profundity,
     reconditeness, rigor, rigorousness, ruggedness, strenuousness,
     toilsomeness, toughness, troublesomeness
  
  

From The Free On-line Dictionary of Computing (27 SEP 03) [foldoc]:

  complexity
       
           The level in difficulty in solving mathematically
          posed problems as measured by the time, number of steps or
          arithmetic operations, or memory space required (called time
          complexity, computational complexity, and space complexity,
          respectively).
       
          The interesting aspect is usually how complexity scales with
          the size of the input (the "{scalability}"), where the size of
          the input is described by some number N.  Thus an {algorithm}
          may have computational complexity O(N^2) (of the order of the
          square of the size of the input), in which case if the input
          doubles in size, the computation will take four times as many
          steps.  The ideal is a constant time algorithm (O(1)) or
          failing that, O(N).
       
          See also {NP-complete}.
       
          (1994-10-20)