  This paper proposes a thought experiment to search for efficient bounded
algorithms of NPC problems by machine enumeration. The key contributions are:
  -- On Universal Turing Machines, a program's time complexity should be
characterized as: execution time(n) = loading time(n) + running time(n).
  -- Introduces the concept of bounded algorithms; proposes a comparison based
criterion to decide if a bounded algorithm is inefficient; and establishes the
length upper bound of efficient bounded programs.
  -- Introduces the growth rate characteristic function to evaluate program
complexity, which is more easily machine checkable based on observations.
  -- Raises the theoretical question: if there exists any bounded algorithm
with polynomial execution time for NPC problems.
