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email: charles.hughes@ucf.edu

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Structure: TR 1330-1445 (1:30PM-2:45PM); HEC-103; 28 class periods, each 75 minutes long.
Go To Week 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16

Instructor: Charles Hughes; Harris Engineering Center 247C
Office Hours: TR 10:45AM-12:00PM
GTA:  Paniz Abedin; HEC-354, Cubicle 2
Office Hours: MW 3:00PM-4:30PM (starting January 20)

Required Reading: All class notes linked from here.

Recommended Reading:

• Cooper, Computability Theory 2nd Ed., Chapman-Hall/CRC Mathematics Series, 2003.
  
• Garey&Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness, W. H. Freeman & Co., 1979.
• Davis, Sigal&Weyuker, Computability, Complexity and Languages 2nd Ed., Acad. Press (Morgan Kaufmann), 1994.
  
• Papadimitriou & Lewis, Elements of the Theory of Computation, Prentice-Hall, 1997.
• Bernard Moret, The Theory of Computation, Addison-Wesley, 1998.
  
• Hopcroft, Motwani&Ullman, Intro to Automata Theory, Languages and Computation 3rd Ed., Prentice-Hall, 2006.
• Oded Goldreich, Computational Complexity: A Conceptual Approach, Cambridge University Press, 2008.
• Oded Goldreich, P, NP, and NP-Completeness: The Basics of Complexity Theory, Cambridge University Press, 2010.
• Arora&Barak, Computational Complexity: A Modern Approach, Cambridge University Press, 2009.
• Sipser, Introduction to the Theory of Computation 3rd Ed., Cengage Learning, 2013.

Web Pages:
Base URL: http://www.cs.ucf.edu/courses/cot6410/Spring2020
Notes URL: Introductory Notes; Formal Language and Automata Theory; Computability Theory; Complexity Theory

Assignments: Around 6 to 10; Paper + Presentation

Exams: midterm and a final.

Exam Dates (Tentative): Mid Term – Tuesday, March 3; Spring Break – March 9-14; Withdraw Deadline – Friday, March 20; Final – Tues., April 21, 1:00PM–3:50PM

Evaluation (Tentative):

1. Mid Term – 125 points; Final Exam – 125 points (balance between weights will be adjusted in your favor)
2. Assignments – 75 points; Independent Paper Reviews and Presentations – 125 points
3. Extra -- 50 points used to increase weight of best exam,  or maybe presentation, always to your benefit
4. Total Available: 500
5. Grading will be  A >= 90%, B+ >= 85%, B >= 80%, C+ >= 75%, C >= 70%, D >= 50%, F < 50%; minus grades might be used.
   

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1. Ground rules
2. Decision problems
3. Solving vs checking
4. Procedures vs algorithms
5. Introduction to theory of computation
6. Terminology, goals and some historical perspective
7. Review of automata (finite, pushdown, linear bounded, Turing machines)
8. Review of formal languages (regular, context free, context sensitive, phrase structured)
9. Review material created by Prof. Jim Rogers, Earlam College
10. Review material from Prof. Workman, UCF

Financial Aid (Assignment#1)

Survey at Webcourses

Due: Friday, January 10 at 11:59 PM

1. Continue Automata/Formal Languages Review
2. MyHill-Nerode as proof of min DFA uniqueness
3. Myhill-Nerode as a tool to show languages are not regular.
   
4. The chosen language is
   L = { aⁿ b^m | n is not equal to m}.
   This can be shown easily in an indirect manner by showing its complement is not regular, A direct approach is using right invariant equivalence classes as it is not amenable to the Pumping Lemma.
5. Review of reduced CFGs
6. Chomsky Normal Form (CNF)
   
7. The use of CNF in the Cocke-Kasami-Younger O(N³) parsing of CFLs generated by CNFs.

1. Pumping Lemma for CFLs
   
2. Show L = { ww | w is in {a,b}⁺ } is not a CFL
3. CSG for L
   
4. Non-closure of CFLs under intersection and complement
   
5. CFG for the complement of L
   { xy | |x| = |y| but x is not the same as y }
   can be first viewed as
   {x1 a x2 y1 b y2 | |x1|=|x2|, |y1|=|y2|} Union
     {x1 b x2 y1 a y2 | |x1|=|x2|, |y1|=|y2|}.
   But this can also be seen as
   {x1 a y1 x2 b y2 | |x1|=|x2|, |y1|=|y2|}.Union
     {x1 b y1 x2 a y2 | |x1|=|x2|, |y1|=|y2|}.
   The above is easy to show as a CFL. We then union this with odd length and we have L1 complement.
6. Closure of CFLs under substitution and intersection with Regular
7. Decision problems for CFLs: is L(G) empty or finite/infinite are fine;
   Checking ambiguity, equality to Sigma*,  equivalence and non-empty intersection with another CFL are not
   

Assignment #2

See Webcourses (Assignment # 2) for description
Sample of Similar Problems with Solutions

Due: 2/6 (Key)

1. Insights from intro to computability material
   
2. Basic notions of computability and complexity
3. Existence of unsolvable problems (counting and diagonalization)
4. Solved, solvable (decidable, recursive), unsolved, unsolvable, re, non-re
5. Hilbert's Tenth
6. Undecidable problems made a bit more concrete
7. Lots about problems and their complexity
8. Halting Problem (HALT) is re, not decidable
9. Set of algorithms (TOT) is non-re
10. Halting Problem seen as fun
11. Some consequences of non-re nature of algorithms
12. Models of computation
• Turing machines
  
• Register machines
• Factor replacement systems (FRS)
• Originally introduced by John Conway, "Unpredictable Iterations," Proceedings of the 1972 Number Theory Conference (1972), pp. 49-52
• Google Fractran for more information on Conway's fractional computation systems
  Weisstein, Eric W. "FRACTRAN." From MathWorld--A Wolfram Web Resource. http://mathworld.wolfram.com/FRACTRAN.html
• The 3x+1 problem http://arxiv.org/pdf/math/0309224.pdf
13. Systems related to FRS (Petri Nets, Vector Addition, Abelian Semi-Groups)
14. RM simulated by Ordered FRS
15. Primitive Recursive Functions (prf)
16. Initial functions
17. Closure under composition and recursion
18. Primitive recursive functions SNAP, TERM, STP and VALUE
19. Primitive Recursive Function in detail
20. Addition and multiplication examples
21. Sample functions and predicates
22. Closure under cases
23. Bounded minimization
24. Arithmetic fuctions that use bounded search
25. Pairing functions
26. Limitations of primitive recursive
27. mu-recursion and the partial recursive functions
28. Notions of instantaneous descriptions
29. Encodings
30. Equivalence of models
31. TMs to Register Machines
32. RM to Factor Replacement Systems

1. Factor Replacement to Recursive Functions
2. Gory details on FRS to REC
3. Universal machines
4. Recursive Functions to TMs
5. Consequences of equivalence
6. Review Undecidability (Halting Problem, shown by diagonalization)
7. RE sets and semidecidability
8. The set of all re sets W₀, W₁, W₂, ...
9. Enumeration Theorem
10. The set K = { n | n is in the n-th re set } = { n | n is in W_n } is re, non-recursive
11. The set K₀ = HALT = { <n,x> | x is in the n-th re set }
12. Alternative characterizations of re sets
13. Parameter Theorem (aka Sm,n Theorem)

Assignment #3

See Webcourses (Assignment # 3) for description
Sample of Similar Problems with Solutions

Due: 2/18 (Key)

1. Quantification and re sets
2. Quantification and Co-re sets
3. Diagonalization revisited (set of algorithms is non-re and K₀ (Lu) = HALT is non-rec)
4. Reduction
5. Classic sets Ko (Lu), NON-EMPTY (Lne), EMPTY (Le)
6. Reduction from Ko that shows undecidability of K, HasZero, IsNonEmpty
7. Complete re set (K and K₀ as examples)
8. Note: To be re-complete a set must be re
9. Reduction from Ko that shows undecidability of K, HasIndentity, TOTAL, IsZero, IsEmpty, IsIdentity
10. Equivalence of certain re sets (K, HasZero, IsNonEmpty, HasIndentity) to Ko
11. Equivalence of certain non-re sets (IsZero, IsEmpty, IsIdentity) to TOTAL
12. Quantification of Non-re, Non-Co-re sets
    
13. Reducibility and degrees (many-one, one-one, Turing)
14. Hierarchy or RE equivalence class (m-1 and 1-1 degrees)
15. Rice's Theorem

    Assignment #4


See Webcourses (Assignment # 4) for description
Sample with key


    Due: 2/25 (Key)

1. "Picture" proofs for Rice's Theorem
2. Constant Time and Mortal Machines
3. Introduction to rewriting systems (Thue, Post)
4. Union, intersection, complement for recursive, re and non-re sets (can be, cannot be)
5. Rewriting systems
6. Post Canonical Forms
7. Thue and Semi-Thue systems (relation to group theory)
   
8. Word problems (Seni-Thue and Thue) and equivalence problems (Thue)
9. Brief introduction to Post Correspondence Systems and Relation to Semi-Thue Systems
   

1. Simulating Turing Machine by Semi-Thue System
2. Simulating Turing Machines by Thue Systems
3. Grammars and re sets
4. Post Correspondence Problem (in detail)
   
5. Unsolvable problems related to context-free grammars/languages
6. Ambiguity of CFGs
7. Non-Emptiness of CFL Intersections
8. Context-Sensitive Grammars and Unsolvability Results
9. Valid (CSL) and Invalid Traces (CFL)
10. Intersection and Quotients of CFLs
11. Details on Valid (CSL) and Invalid Traces (CFL)
12. Intersection of CFLs revisited
13. Quotients of CFLs revisited
14. Type 0 grammars and Traces
15. L =  Sigma*  for L a Regular or CFL
16. L=L^2 for L a CFL
17. Summary of Grammar Results
18. Review session and sample exams
19. Exam Topics
    
20. Sample exam1; Sample exam1 key
    
21. Sample exam2; Sample exam2 key
22. Key to Samples from Notes
23. Yet Other Examples (Focused on Formal Languages and Automata Theory)
24. Yet Other Examples key (Focused on Formal Languages and Automata Theory)
25. Midterm Legal Cheat Sheet
    

Week#9: (3/3, 3/5) -- Complexity Theory

1. Midterm (Tuesday)
2. Basics of Complexity Theory
3. Decision vs Optimization Problems (achieving a goal vs achieving min cost)
4. Polynomial == Easy; Exponential == Hard
5. Polynomial reducibility
6. Verifiers versus solvers
7. P as solvable in deterministic polynomial time
8. NP as solvable in non-deterministic polynomial time
9. NP as verifiable in deterministic polynomial time
10. Concepts of NP-Complete and NP-Hard
11. Canonical NP-Complete problem: SAT (Satisfiability)
12. Some NP problems that do not appear to be in P: SubsetSum, Hamiltonian Path, k-Clique
13. Million dollar question: P = NP ?
14. Construction that maps every problem solvable in non-deterministic polynomial time on TM to SAT
15. SAT is polynomial reducible to (<=_P) 3SAT
16. 3SAT as a second NP-Complete problem
17. Integer Linear Programming
    

Week#10: SPRING BREAK

1. The Big Challenge we have is going online for the rest of the semester.
   
2. Note: 3/20 is the Withdraw Deadline
3. 3SAT <=_P SubsetSum
4. SubsetSum <=_P Partition
5. Partition equivalence to SubsetSum
6. Discussion of group presentations
7. Reduction of 3SAT to k-Vertex Cover
8. 3-SAT to 3-Coloring
9. Isomophism of k-Coloring with k-Register Aloocation of live variables
10. Scheduling problems introduced 
11. Scheduling on multiprocessor systems
12. Scheduling problems (fixed number of processors, minimize final finishing time)
13. N processors, M tasks, no constraints
14. Partition and scheduling problems
15. Greedy heuristics
16. 2-processor scheduling -- greedy based in list, sorted long to short, sorted short to long, optimal. Tradeoffs.
17. Scheduling anomalies, level strategy for UET trees, level strategy for UET dags
18. Precedences (lists, delays, preemption)
19. Anomalies (reducing precedence, increasing processors, reducing times)
20. Midterm Key
    

     Assignment #5
    

            See Webcourses (Assignment # 5) for description
            Sample with Key
    

 Due: 3/26 (Key)

1. Unit Execution Time: Trees, forest, anti forests
2. UET: DAGs and m=2
3. Hamiltonian Path
4. Traveling Salesman
5. Knapsack (relation to SubsetSum), Dynamic Programming Approach
6. Bin packing (fixed capacity, minimize number of bins)
7. Pseudo polynomial-time solution for Knapsack using dynamic programming with changed parameters, n*W versus 2^n
8. Tiling the plane and Bounded Tiling
9. Bounded PCP
   
10. Co-NP
11. Reduction techniques
12. P = co-P ; P contained in intersection of NP and co-NP
13. NP-Hard
14. QSAT as an example of NP-Hard, possibly not NP
15. NP-Hard problems are in general functional not necessarily decision problems
16. NP-Complete are decision problems as they are in NP
17. NP-Easy -- these are problems that are polynomial when using an NP oracle
18. NP-Equivalent is the class of NP-Easy and NP-Hard problems
• In essence this is functional equivalent of NP-Complete but also of co-NP Complete
  
• NP-Equivalent uses a Turing machine polynomial time reduction so just uses rather than accepts answers from oracle
19. Optimization versions of SubsetSum and of K-Color
    
20. I am now requiring that each of you to develop a paper and a presentation, based on a an existing research paper, just as if you had to present to your peers and advisors. In addition to presenting the results and the way in which these were proven, you should comment on  the paper's importance, readability, and replicability, and even its validity if you question that, just as if you were a journal or conference reviewer. The length of the paper is 6 to 12 pages double-spaced, 1" margins all around, using either Times Roman or Calibri 11 point, or Arial 10-point. The references are in addition to the narrative and appear on a separate page. Images may be used but if the total number of images exceeds a page, then all past that one page aggregate will lead to a requirement for additional text. The presentation must be designed as if you would be using it to be as part of a 12-minute discussion to your classmates. Note: For shorter papers you may (likely will) need to investigate some cited works.
    
21. I have placed over 50 sample papers out there at SampleTopics. You may choose from any of these except for ones that have already been taken. You may also choose your own separate from these with permission from me. In general, the minimum page length in IEEE 2-column format is 8 pages or 10 pages in single column, single-spaced layout. The prefix CLAIMED_NAME means NAME has already chosen that. Actually, the one case already Claimed is from someone who sent the paper my way. Please send me an email to assure you "claim."
    
22. Realize that many of these are from arXiv and, while arXiv is a fantastic source, it is not refereed so if you question the validity of some result, that is actually a reasonable outcome so long as you present their approach and your counterarguments just as if you were a reviewer.
    This folder contains some examples (papers and presentations) from past semesters.
    
23. Final Exam will need to be done at home. I need to know that each of you has a web cam so we can use some of the exam proctoring tools developed for remote exam taking. If you do not, let me know ASAP.
    

            Final Paper and PowerPoint
    

                 Read above. Its weight is now at least 125 points.
                 It goes higher if you attack a challenging topic and do really well on it.
                 Note that I increased the bonus weight to 50 and allow it on the Paper/Presentation
    

            Due: 4/23
    

            Assignment #6
    

                 See Webcourses (Assignment # 6) for description
                 Sample with Key
    

            Due: 4/7 (Key)

1. Clean-up (PSPACE, NPSPACE, CO-PSPACE, PSPACE-COMPLETE)
   
2. EXPSPACE, EXPTIME, NEXPTIME
3. ATM (Alternating NDTM)
4. QSAT. Petri Nets, Presburger
5. Validity of SubsetSum optimization reduction to SubsetSum Decision Problem Oracle
   
6. 2SAT (linear time complexity)
7. Uniform Min-1 is NP Equivalent
8. Propositional Calculus
   Axiomatizable Fragments
   Unsolvability for Membership in Fragments of Diadic Partial Implicational Propositional Calculus

1. Finite Convergence
   Finite Power Problem for CFLs
   Revisit Set Real-Time (Constant-Time)
   Real-Time and Mortal Machiness
2. FP is functional equivalent to P; R(x,y) in FP if can provide value y for input x via deterministic polynomial time algorithm
3. FNP is functional equivalent to NP; R(x,y) in FNP if can verify any pair (x,y) via deterministic polynomial time algorithm
4. TFNP is the subset of FNP where a solution always exists, i.e., there is a y for each x such that R(x,y).
• Task of a TFNP algorithm is to find a y, given x, such that R(x,y)
• Unlike FNP, the search for a y is always successful
  
• FNP properly contains TFNP contains FP (we don't know if proper)
  
5. Factoring is in TFNP, but is it in FP?
   
• If TFNP in FP then TFNP = FP
6. P = (NP intersect Co-NP) is interesting analogue to intersection of RE and co-RE but may not hold here
7. It appears that TFNP does not have any complete problems!!!
• The deal is that there is no known recursive enumeration of TFNP but there is of FNP
• This is similar to total versus partially recursive functions (analogies are everywhere)

Week#15: (4/14, 4/16)

1. Final Exam Topics
2. More stuff for final
   
3. Sample Final Exam (Key)
    

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Week#16:  (4/21 -- Final Exam)

1. All Project Papers and Presentations are Due on Wednesday, 4/23 by midnight
2. Final Exam will need to be done at home. It will be on Webcourses and you will be on your honor.