• Source: Dynamic problem (algorithms)

      • Dynamic problems in computational complexity theory are problems stated in terms of changing input data. In its most general form, a problem in this category is usually stated as follows:

      Given a class of input objects, find efficient algorithms and data structures to answer a certain query about a set of input objects each time the input data is modified, i.e., objects are inserted or deleted.
      Problems in this class have the following measures of complexity:

      Space – the amount of memory space required to store the data structure;
      Initialization time – time required for the initial construction of the data structure;
      Insertion time – time required for the update of the data structure when one more input element is added;
      Deletion time – time required for the update of the data structure when an input element is deleted;
      Query time – time required to answer a query;
      Other operations specific to the problem in question
      The overall set of computations for a dynamic problem is called a dynamic algorithm.
      Many algorithmic problems stated in terms of fixed input data (called static problems in this context and solved by static algorithms) have meaningful dynamic versions.


      Special cases


      Incremental algorithms, or online algorithms, are algorithms in which only additions of elements are allowed, possibly starting from empty/trivial input data.
      Decremental algorithms are algorithms in which only deletions of elements are allowed, starting with the initialization of a full data structure.
      If both additions and deletions are allowed, the algorithm is sometimes called fully dynamic.


      Examples




      = Maximal element

      =
      Static problem
      For a set of N numbers find the maximal one.
      The problem may be solved in O(N) time.

      Dynamic problem
      For an initial set of N numbers, dynamically maintain the maximal one when insertion and deletions are allowed.
      A well-known solution for this problem is using a self-balancing binary search tree. It takes space O(N), may be initially constructed in time O(N log N) and provides insertion, deletion and query times in O(log N).

      The priority queue maintenance problem
      It is a simplified version of this dynamic problem, where one requires to delete only the maximal element. This version may do with simpler data structures.


      = Graphs

      =
      Given a graph, maintain its parameters, such as connectivity, maximal degree, shortest paths, etc., when insertion and deletion of its edges are allowed.


      See also


      Dynamization
      Dynamic connectivity
      Kinetic data structure


      References

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