•  Completeness: A search algorithm is considered complete when it gives a solution or returns any solution for a given random input.
  •  Optimality: If a solution found is the best (lowest path cost) among all the solutions identified, then that solution is said to be optimal.
  •  Time complexity: The time taken by an algorithm to complete its task is called time complexity. If the algorithm completes a task in a shorter amount of time, then it is efficient.
  •  Space complexity: It is the maximum storage or memory the algorithm takes while searching.

These properties are also used to compare the efficiency of the different types of searching algorithms.