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Computer Science – Theory of Computation

Curriculum

  • 1 Section
  • 42 Lessons
  • 10 Weeks
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  • Computer Science - Theory of Computation
    42
    • 2.1
      What is theory of computation?
    • 2.2
      Introduction to finite automaton.
    • 2.3
      Finite automata continued, deterministic finite automata(DFAs),
    • 2.4
      Regular languages, their closure properties.
    • 2.5
      DFAs solve set membership problems in linear time, pumping lemma.
    • 2.6
      More examples of nonregular languages, proof of pumping lemma
    • 2.7
      A generalization of pumping lemma, nondeterministic finite automata (NFAs)
    • 2.8
      Formal description of NFA, language accepted by NFA, such languages are also regular.
    • 2.9
      Guess and verify-paradigm for nondeterminism.
    • 2.10
      NFAs with epsilon transitions.
    • 2.11
      Construction of a regular expression for a language given a DFA accepting it.
    • 2.12
      Closure properties continued.
    • 2.13
      Closure under reversal, use of closure properties.
    • 2.14
      Decision problems for regular languages.
    • 2.15
      About minimization of states of DFAs. Myhill-Nerode theorem.
    • 2.16
      Continuation of proof of Myhill-Nerode theorem.
    • 2.17
      Application of Myhill-Nerode theorem. DFA minimization.
    • 2.18
      DFA minimization continued.
    • 2.19
      Introduction to context free languages (cfls)
    • 2.20
      Languages generated by a cfg, leftmost derivation, more examples of cfgs and cfls.
    • 2.21
      Parse trees, inductive proof that L is L(G). All regular languages are context free.
    • 2.22
      Towards Chomsky normal forms: elimination of useless symbols
    • 2.23
      Simplification of cfgs continued, Removal of epsilon productions
    • 2.24
      Elimination of unit productions. Converting a cfg into Chomsky normal form.
    • 2.25
      Pumping lemma for cfls. Adversarial paradigm.
    • 2.26
      Completion of pumping lemma proof
    • 2.27
      Closure properties continued. cfls not closed under complementation.
    • 2.28
      Another example of a cfl whose complement is not a cfl. Decision problems for cfls.
    • 2.29
      More decision problems. CYK algorithm for membership decision.
    • 2.30
      Introduction to pushdown automata (pda).
    • 2.31
      pda configurations, acceptance notions for pdas. Transition diagrams for pdas
    • 2.32
      Equivalence of acceptance by empty stack and acceptance by final state.
    • 2.33
      Turing machines (TM): motivation, informal definition, example, transition diagram.
    • 2.34
      Execution trace, another example (unary to binary conversion).
    • 2.35
      Example continued. Finiteness of TM description
    • 2.36
      Notion of non-acce`ptance or rejection of a string by a TM. Multitrack TM
    • 2.37
      Simulation of multitape TMs by basic model. Nondeterministic TM (NDTM).
    • 2.38
      Counter machines and their equivalence to basic TM model.
    • 2.39
      TMs can simulate computers, diagonalization proof.
    • 2.40
      Existence of non-r.e. languages, recursive languages, notion of decidability.
    • 2.41
      Separation of recursive and r.e. classes, halting problem and its undecidability.
    • 2.42
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Application of Myhill-Nerode theorem. DFA minimization.
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Introduction to context free languages (cfls)
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