1. CSC 4170
Theory of Computation
The class P
Section 7.2

2. The definition and importance of P
Definition P is the class of languages that are decidable in
polynomial time on a deterministic (single-tape) TM. In other words,
P = TIME(n1)  TIME(n2)  TIME(n3)  TIME(n4)  …
Importance
1. P is invariant for all models of computation that are polynomially
equivalent to the deterministic single-tape TM.
Here polynomial equivalence means equivalence with only a
polynomial difference in running time.
Thus, P is a mathematically robust class, not affected by the
particulars of the model of computation that we are using.
2. P roughly corresponds to the class of problems that are
realistically solvable on a computer.
Thus, P is relevant from a practical standpoint.

3. Analyzing polynomial-time algorithms
7.2.b
1. When we only care about polynomiality, algorithms can be described at high
level without reference to features of a particular implementation model. Doing so
avoids tedious details of tapes and head motions.
2. We describe algorithms with numbered stages. The notion of a stage is
analogous to a step of a TM, though of course, implementing one stage will usually
require many TM steps. Asymptotic analysis allows us to ignore this difference.
3. To show that an algorithm runs in polynomial time, it is sufficient to show that:
a) There is a polynomial upper bound (usually in big-O notation) on the number
of stages that the algorithm uses when it runs on an input of length n, and that
b) Each stage takes a polynomial number of (actual TM) steps on a reasonable
deterministic model.
4. The underlying (and usually non-specified) encoding of objects should be
reasonable, and polynomially equivalent to other reasonable encodings. E.g.,
encoding 12 as is unreasonable as it is exponentially bigger than
the binary (or decimal) encoding.
5. Among the reasonable encodings for graphs are encodings of their adjacency
matrices. Since the size of such a matrix only polynomially differs from the number
of nodes, it is OK if we show the polynomiality of an algorithm in the number of
its nodes rather than in the size of its adjacency matrix.

4. The PATH problem
7.2.c
PATH = {<G,s,t> | G is a directed graph that has a directed path from s to t} 2 3 1 4 5 8 s 7 6 t 9 12 10 11 14 15 13 16

5. A polynomial-time algorithm for the PATH problem
7.2.d
M = “On input <G,s,t> where G is a directed graph and s,t are nodes of G:
1. Mark s.
2. Repeat until no additional nodes are marked:
Scan all the edges of G. If an edge (a,b) is found going from a marked
node a to an unmarked node b, mark node b.
4. If t is marked, accept. Otherwise reject.” 2 3 1 4 5 8 s 7 6 t 9 12 10 11 14 15 13 16

6. RELPRIME = {<x,y> | x and y are relatively prime}
The RELPRIME problem
7.2.e
Two numbers are said to be relatively prime iff 1 is the largest integer that evenly
divides both of them.
Are the following numbers relatively prime?
15 and 27
8 and 9
11 and 19
No, - both divisible by 3
Yes
Yes: two different prime numbers are always relatively prime
RELPRIME = {<x,y> | x and y are relatively prime}
Is RELPRIME decidable?
What is the time complexity of an ad hoc decision algorithm (TM)?
But there is a smarter algorithm that runs in polynomial time. It is based on the
Euclidean algorithm for finding the greatest common divisor.

7. Interlude: A polynomial-time algorithm for the finding the GCD
The Euclidean algorithm:
E = “On input <x,y>, where x and y are natural numbers, x>y:
1. Repeat until y=0.
2. Assign x  x mod y.
3. Exchange x and y.
4. Output x.”
Testing on <33,15>:
What is the time complexity of this algorithm?

8. A polynomial-time algorithm for the RELPRIME problem
The following algorithm R solves RELPRIME in polynomial time:
R = “On input <x,y>, where x and y are natural numbers:
1. Swap x and y if necessary so that x>y.
2. Run E on <x,y>.
3. If the result is 1, accept. Otherwise reject.

9. The time complexity of context-free languages
Theorem Every context-free language is a member of P.
Specifically, is of complexity O(n3).
Proof omitted (and will not be asked).