CMPSCI 501: Theory of Computation

Second Midterm Exam, Spring 2017

David Mix Barrington

11 April 2017

Directions:

• Answer the problems on the exam pages.
• There are eight problems (some with multiple parts) for 125 total points. Actual scale was A = 100, C = 64.
• If you need extra space use the back of a page.
• No books, notes, calculators, or collaboration.
• The first six questions are statements -- in each case say whether the statement is true or false and give a convincing justification of your answer -- a proof, counterexample, quotation from the book or from lecture, etc. You get five points for the correct boolean answer (so there is no reason not to guess if you don't know) and up to five for the justification.

  Q1: 10 points
  Q2: 10 points
  Q3: 10 points
  Q4: 10 points
  Q5: 10 points
  Q6: 10 points
  Q7: 30 points
  Q8: 35 points
 Total: 125 points

The set N of natural numbers is {0, 1, 2, 3,...}, not quite as defined in Sipser.

For this exam, the input alphabet of all machines will be Σ = {0, 1}.

A palindrome is a string that is equal to its own reversal. Let PAL = {w: w is a palindrome}.

If C is any class of things that have languages, such as DFA's, CFG's, TM's, strange variant TM's, etc., remember that (M) is the canonical string representing the thing M in C. We define the following languages:

• A_C = {(M, w): M is a computer in C and w ∈ L(M)}

• E_C = {(M): M is a computer in C and L(M) = ∅}

• ALL_C = {(M): M is a computer in C and L(M) = Σ^*}

• SING_C = {(M): M is a computer in C and L(M) has exacctly one element}

A language is Turing recognizable (TR) if it is equal to L(M) for some Turing machine M.

A language is Turing decidable (TD) if it is equal to L(M) for some Turing machine M that halts on every input.

A language is co-TR if and only if its complement is TR. (Similarly for co-NP, etc.)

A function f from strings to strings is Turing computable if there exists a Turing machine M such that for any string w, M when started on w halts with f(w) on its tape. It is poly-time computable if in addition, M always computes f(w) using time polynomial in the length of w.

Recall that if A and B are two languages, A is mapping reducible to B, written A ≤_m B, if there exists a Turing computable function f: Σ^* → Σ^* such that for any string w, w ∈ A ↔ f(w) ∈ B. A is poly-time reducible to B, written A ≤_p B, if in addition the function f is poly-time computable.

The language BPCP, for Bounded Post Correspondence Problem, is the set of pairs (P, m) were P is a sest of dominoes (as in the ordinary PCP), m is a number written in binary, and P has a match that uses at most m total dominoes. (Recall that a match can use the same domino multiple times, and we are counting them with multiplicity. For example, the same domino used 100 times counts as 100 dominoes.)

The following languages were proved to be NP-complete either in the text of Sipser or in the exercises. You may assume without proof that they are NP-complete.

• 3-SAT = {φ φ is a satisfiable formula in 3-CNF}

• 3-COLOR = {G: G is an undirected graph and the vertices of G may each be assigned one of three colors so that no edge connects two vertices of the same color}

• DHAMPATH = {(G, s, t): G is a directed graph in which there is a directed path from vertex s to vertex t such that the path visits each vertex of G exactly once}

• SUBSET-SUM = {(a₁,..., a_k, t): the a_i's and t are binary positive integers and there is a subset of the a_i's that adds to exactly t}

• CLIQUE = {(G, k): G is an undirected graph and G has a set S of k vertices such that every two distinct vertices in S have an edge between them}

• VERTEX-COVER = {(G, k): G is an undirected graph and G has a set S of k vertices such that every edge in G has at least one endpoint in S}

The following two languages are to be proved NP-complete on this exam:

• PIC = {(G, k): G is an undirected graph and the vertices of G may be partitioned into k disjoing subsets such that for each subset S, every two distinct vertices in S have an edge between them} (The name of the language abbreviates Partition Into Cliques.)

• KNAPSACK = {(w₁, v₁),..., (w_k, v_k), wt, vt): the w_i's, v_i's, wt, and vt are binary positive integers and there is subset of the i's such that the w_i's in the subset add to exactly wt, and the v_i's in the subset add to at least vt.} (Think of the input as defining k items, each with a weight and a value. We want a set of items for our knapsack that meets the weight target exactly, while meeting or exceeding the value taget.

• Question 1 (10): True or false with justification: The set {(M): (M) ∈ L(M)}, where the type of M is "Turing machine", is co-TR.

• Question 2 (10): True or false with justification: The language BPCP defined above is not TD.

• Question 3 (10): True or false with justification: The language SING_TM is either TR or co-TR, but not both.

• Question 4 (10): True or false with justification: The set of incompressible strings I = {x: K(x) ≥ |x|}, is TR.

• Question 5 (10): True or false with justification: Let A and B be any two languages. If A ∉ P, A ≤_p, and B ≤_p A, then both A and B must be NP-complete.

• Question 6 (10): True or false with justification: There exists a Turing machine R with the following property: For every string w, R accepts w if and only if w ∉ L(R).

• Question 7 (30): These two questions both deal with languages defined above.

  • (a, 15) Prove that the language PIC is NP-complete.

  • (b, 10) Prove that the language KNAPSACK is NP-complete.

• Question 8 (35): These three questions all deal languages of the form SING_C as defined above. If C is any class of things that have languages, then SING_C is the set of those things whose languages have exactly one element.
  • (a, 15) Prove that SINGTM is not TD.

  • (b, 10) Prove that SING_CFG is TD.

  • (c, 10) Prove that SING_NFA is in co-NP.

  Last modified 19 April 2017