P-complete

Iterated Shuffle (SHUF)

Input

A language $L$ over a finite alphabet $\Sigma$ described in terms of the operators $\cdot$, $*$, $\cup$, $\cap$, $\Delta$, and $\dagger$; which denote concatenation, Kleene star, union, intersection, shuffle, and iterated shuffle, respectively; plus a designated word $w \in \Sigma^\ast$.

Problem

Is $w \in L$?

Definitions

The shuffle of two languages $L_1$ and $L_2$, denoted $L_1 \Delta L_2$, is $$\{x_1 y_1 x_2 y_2 \cdots x_m y_m \mid x_1 x_2 \cdots x_m \in L_1, y_1 y_2 \cdots y_m \in L_2 \text{ and } x_i, y_i \in \Sigma^\ast \text{ for } i = 1, \ldots, m\}.$$ The iterated shuffle denoted $L^\dagger$ is $$\{\epsilon\} \cup L \cup (L \Delta L) \cup (L \Delta L \Delta L) \cup \cdots.$$

Status

$\P$-complete (Shoudai [1]).

Remarks

Certain restrictions must be placed on $L$ in order for this problem to be in $\P$. The reduction to show hardness is from a variant of NORCVP.

It is known that there are two deterministic context-free languages whose shuffle is $\NP$-complete (Ogden, Riddle, and Rounds [2]). Here the intersection operation is used to force the problem into $\P$ [1].

References

  1. T. Shoudai (1992). A P-complete language describable with iterated shuffle.
  2. W. F. Ogden, W. E. Riddle, and W. C. Rounds (1978). Complexity of expressions allowing concurrency.
  3. Greenlaw, R., Hoover, H. J., and Ruzzo, W. L. (1995). Limits to Parallel Computation: P-Completeness Theory. Oxford University Press. Problem A.7.15.