A mapping reduction from a problem to a problem is a computable function such that .

means is (mapping) reducible to .

Theorem: if and is decidable, then is also decidable

Proof:

  1. Suppose that and is decidable.
  2. From (i), there is some computable function such that
  3. From (ii) there is some sound, complete, and terminating machine such that
  4. Hence, we can construct a sound, complete, and terminating algorithm for . It follows that: As required.
Theorem: The Accepting Problem is undecidable

Proof:

  1. Since is undecidable, it is sufficient to show that .
  2. Given any input machine , we construct a new machine prime that accepts when accepts and rejects, or otherwise when it does not terminate. Hence we have that .
  3. Hence, Therefore our computable function for our reduction is given by Which we formalise as:
Theorem: The non-Emptiness Problem is undecidable

Proof:

  1. Since is undecidable, it is sufficient to show that
  2. Given any input machine and input word , we construct a new machine as:

\text{Language}(M_w) \neq \emptyset &= 1 \Leftrightarrow M(w) = 1 \end{aligned}\langle code(M), w \rangle \in A_{TM} \Leftrightarrow code(M_w) \in E_{TM}f(\langle code(M), w \rangle) = code(M_w)f(u) = \begin{cases} code(M_w) &\text{if } u = \langle code(M), w \rangle \ \epsilon &\text{otherwise} \end{cases}$$