cap 632

Lovely Professional University, Punjab Course Code

Course Title

Course Planner

Lectures

CAP632

FORMAL LANGUAGES AND AUTOMATION THEORY

12962::Harjinder Kaur

Course Category

Courses with conceptual focus

Tutorials Practicals Credits

3.0

0.0

0.0

TextBooks Sr No

Title

Author

Edition

T-1

THEORY OF COMPUTER SCIENCE :AUTOMATA, LANGUAGES & COMPUTATION

K.L.P MISHRA & N. CHANDRASEKRAN

1st

Author

Edition

Year

Publisher Name

PHI (PRETICE HALL INDIA)

Reference Books Sr No

Title

R-1

INTRODUCTION TO LANGUAGES JOHN C MARTIN & THE THEORY OF COMPUTATION

R-2

THEORY OF COMPUTATION

R-3

AN INTRODUCTION TO FORMAL PETER LINZ LANGUAGES AND AUTOMATA

KAVI MAHESH

Year

1st

TATA MCGRAW HILL

1st 4th

Publisher Name

WILEY INDIA PVT LTD 2010

NAROSA PUBLISHING HOUSE PVT. LTD

Other Reading Sr No

Jour Journa nals ls arti articl cles es as Comp Compul ulsa sary ry read readin ing g (sp (spec ecif ific ic arti articl cles es,, com compl plet etee refe refere renc nce) e)

OR-1

http://cs.fit.edu/~dmitra/FormaLang/ ,

OR-2 OR-2

http http:/ ://w /www ww.m .myw ywbu but. t.co com/ m/sy syll llab abus us.p .php hp?m ?mod ode= e=VT VT&p &pap aper er_i _id= d=14 14&d &dep ept_ t_id id=2 =2 ,

OR-3 OR-3

http http:/ ://w /www ww.g .gob oboo ooke kee.n e.net et/f /for orma mall-la lang ngua uage gess-an andd-au auto tomat mata-t a-the heor oryy-by by-k -kri rith thiv ivas asan an// ,

Audio Visual Aids Sr No

(AV aids) (only if relevant to the course)

Salient Features

AV-1

http://www.ida.liu.se/~TDDA89/

To provide students in learning basic and advanced concepts through remote experimentation

AV-2

http://www.cse.cuhk.edu.hk/~andrejb/csc3130/f08/

To provide various tools for learning, including web recources, video lectures, animated demonstration and seld evaluation

AV-3

http://www.nptel.iitm.ac.in/courses/106106049/

To provide various tools for learning, including web recources, video lectures, animated demonstration and seld evaluation

LTP week distribution: (LTP Weeks)

3.0

Weeks After MTE

7

Spill Over

3

Detailed Plan For Lectures Week Number

Lecture Number

Broad Topic(Sub Topic)

Week 1

Lecture 1

Automata(Definition)

T-1:Ch-1

Lecture 2

Automata(Description and transition modes)

Lecture 3

Lecture 4

Week 2

Chapters/Sections of Other Readings, Text/reference Relevant Websites, books Audio Visual Aids, software and Virtual Labs

Lecture Description

Learning Outcomes Pedagogical Tool Demonstration/ Case Study / Images / animation / ppt etc. Planned

Live Examples

AV-1

Introductory Lecture

Students will learn about the need and use of TOC in the field of Computer Science

Peer Learning, Case Study Discussion and Demonstration of Animation

Automata theory is the basis for the theory of formal languages

T-1:Ch-3

AV-2

Complexity theory Computability theory Automata theory

Students will learn about the transition modes


Accept and Generate modes

Automata(NDFA and DFA)

T-1:Ch-3

DK-1

NDFA is a variation of Makes it easy to the FSM that will make design FSMs it much easier to design FSMs


DFA can model software that decides whether or not online user-input such as email addresses are valid

Automata(Mealy and Moore machine)

T-1:Ch-3

DK-3

Variants of Finite automata


A simple Mealy machine has one input and one output,complex Mealy machines can have multiple inputs as well as multiple outputs

Automata(Minimization of Finite Automata)

T-1:Ch-3

AV-2

Deterministic finite Students learn to automata and example reduce a Complex of a finite automata Finite Automata


Select one state in each set of the partition final as the representative for the set. These representatives are states of minimum DFA

Students learn about Finite automata with output

Week 2

Lecture 4

Automata(Constructing simple automata)

T-1:Ch-4

DK-2

Formal definition of a finite automaton

Students learn to Design finite automata


Defining Initial and Final States,Creating Transitions,Dele ting States and Transitions,Run ning the FA on Multiple Strings

Lecture 5

Automata(Handling end onditions)

T-1:Ch-4

OR-1

Regular operations of simple automata

Students learn the importance of Finite Automata conditions


Useful for specifying behavior of systems that are not expected to terminate, such as hardware, operating systems and control systems

Automata(Handling reject states)

T-1:Ch-4

OR-2

Proof techniques of automata states

Students learn the importance of Finite Automata states


All states have a transition for all possible input signals. If an input signal is considered 'illegal' it cannot be rejected

Automata(Step by step method for constructing utomata)

T-1:Ch-4

OR-3

To construct and analyse Learn the importance Peer Learning, automata behaviour of construction of Case Study Automata Discussion and Demonstration of Animation

Defining Initial and Final States,Creating Transitions,Dele ting States and Transitions,Run ning the FA on Multiple Strings

Automata(States as Memory)

T-1:Ch-5

OR-2

To construct states to compute functions

Learn the importance Peer Learning, of corresponding Case Study states Discussion and Demonstration of Animation

An automaton may also contain some extra memory in the form of a stack in which symbols can be pushed and popped

Automata(Why finite number of states)

T-1:Ch-5

OR-1

Process and accept infinite sets if input strings

Students learn the importance of Automata states

vending machines ,elevators,traffic lights


Week 2

Week 3

Lecture 5

Automata(Limitations of finite automata)

T-1:Ch-5

DK-2

Constructing automata to solve computing problems

Learn the Limitations Peer Learning, of finite automata Case Study Discussion and Demonstration of Animation

FA is that they have only a finite number of states. Hence, a finite automata can only "count" a finite number of input scenarios.

Lecture 6

Automata(Non deterministic finite automata)

T-1:Ch-5

DK-3

Formal definition of a non deterministic finite automata

Learn the importance of NDFA Closure under the regular operations


Does not require input symbols for state transitions and is capable of transitioning to zero or two or more states for a given start state and input symbol

onstruction of Finite Automata(Construction of Finite Automata equivalent to Regular expression & vice versa)

T-1:Ch-5

AV-3

Relation between Finite Any FSM can be Automata Regular converted to a regular Expressions expression, and every regular expression can be converted into a nondeterministic FSM


Works recursively by splitting an expression into its constituent subexpressions, from which the NFA will be constructed using a set of rules

onstruction of Finite Automata(Pumping Lemma for regular sets & its pplications)

T-1:Ch-5

DK-1

Non regular Languages The pumping lemma The pumping lemma for for Regular sets is a regular languages way to convince students that certain sets are not Regular


To prove a fact about all infinite regular languages that will be helpful in proving that specific languages are nonregular.

Pus hdown Automata (Definition)

T-1:Ch-7

DK-2

Describing the basics of A push down Push Down Automata automaton PDA or is a type of automaton that uses a stack for temporary data storage


They are more capable than finite-state machines but less capable than Turing machines.

Lecture 7

Week 3

Lecture 7

Lecture 8

Lecture 9

Pus hdown Automata (Acceptance)

T-1:Ch-7

AV-2

Types of acceptance by Pushdown Automata

Students learn about the technique for acceptance of string


The first acceptance mode uses the internal memory (state), the second the external memory (stack).

Pushdown Automata (Pushdown Automata and ontext Free Languages)

T-1:Ch-7

OR-1

Relationship between Push down Automata and Context Free Languages

Learn about Connection between Push down Automata and Context Free Languages


When the grammar rewrites a nonterminal, the PDA takes the topmost nonterminal from its stack and replaces it by the righthand part of a grammatical rule

Pushdown Automata (Parsing and Pushdown utomata)

T-1:Ch-7

OR-2

Purpose of Parsing in automata

Learn about Top Down and Bottom Up Parsing


Top down and bottom up parsing

Pushdown Automata (Constructing PDAs)

T-1:Ch-7

DK-3

To teach about the construction of PDA

Students solve the examples of push down automata


Regarded as being "pushed down" like a tray dispenser at a cafeteria, since the operations never work on elements other than the top element

Pushdown Automata (Converting CFGs to PDAs)

T-1:Ch-7

AV-1

Designing PDAs from context free grammars

Ways to simplify CFGs


For each pushdown automaton M one may construct a context-free grammar G such that N(M)=L(G)

Pushdown Automata (Converting PDAs to CFGs)

T-1:Ch-7

AV-3

Designing PDAs to CFGs

Ways to simplify PDAs


using the tools under the “Convert ? Convert to Grammar” menu option using

Week 3

Lecture 9

ontext Free languages (Derivation trees)

T-1:Ch-6

DK-1

Other way of representing a CFG

Week 4

Lecture 10

ontext Free languages (Ambiguity in Context free rammars)

T-1:Ch-6

AV-3

ontext Free languages (Simplification of context free grammars)

T-1:Ch-6

ontext Free languages(The homsky & Greibach Normal Forms)

Lecture 11

Lecture 12

Parse tree as a way to represent the derivation of a string from a grammar


if we used a production A : : = X1X2...Xn (in either top-down or bottom-up parsing) then we construct a tree with node A and children X1X2...Xn

To ambiguity in context Students learn the free grammars importance of Ambiguity with the help of examples


When there's a word which has two different derivation tree

AV-2

Equivalence with context free grammars

Students learn the ways to equivalent context free grammars


Precise mechanism for describing the methods by which phrases in some natural language are built from smaller blocks, capturing the "block structure" of sentences in a natural way

R-1:Ch-4 R-2:ch-6

AV-3

Describing CNF

Students learn to reduce grammar to a CNF


Normal form usually used in algebraic specifications

ontext Free Grammars(The Kuroda Normal Form)

R-3:Ch-6

AV-1

DescribingKuroda Normal Form

Students learn the importance of KNF


Every contextsensitive language which does not generate the empty string can be generated by a grammar in Kuroda normal form

ontext Free Grammars (One sided Context ensitive Grammars)

R-3:Ch-6

OR-1

Elaborates concept of KNF

Learns about the implementation of KNF


Noncontracting grammar or a linear bounded automaton

Week 4

Week 5

Lecture 12

ontext Free Gra mma rs (Unrestricted Languages)

R-3:Ch-6

DK-2

Implementation for making restrictions

Learn the usage of restrictions


Grammars make no real distinction between nonterminal and terminal symbols

Regular Languages and Expressions(Idea of formal languages)

R-3:Ch-6

AV-1

Introduction to formal language

Learn the concept of formal language


Every nonempty string that does not contain "+" or "=" and does not start with "0" is in L.

R-3:Ch-6

OR-1

Highlights on Automata U nderstands the Peer Learning, concept of automaton Case Study Discussion and Demonstration of Animation

Generative model ,language model

R-3:Ch-6

DK-2

Recursive definition

The set of strings over {0,1} that end in 3 consecutive 1's.

Lecture 13 Regular Languages and Expressions(Languages of Automata)

Regular Languages and Expressions(Regular xpressions)

Learn to construct simple regular expression


(0 | 1)* 111

Lecture 14

Regular Languages and Expressions(Converting Regular expressions to utomata)

R-3:Ch-6

AV-2

Mapping from elements Learn to convert Peer Learning, of regular expression to regular expression to Case Study NFA equivalent automata Discussion and Demonstration of Animation

JLex, is to generate the transition tables or to synthesize the scanner program given a scanner specification

uring Machines (Representation)

T-1:ch-9

AV-1

Ways to design Turing Machines

It consists of an infinitely-long tape which acts like the memory in a typical computer, or any other form of data storage

Understands about Peer Learning, Formal definition of a Case Study Turing machine Discussion and Demonstration of Animation

Week 5

Lecture 14

uring Machines(Language cceptability)

T-1:ch-9

AV-3

Examples of Turing machines and computable functions

Learn to construct turing machines


A string x is said to be accepted by a Turing machine* T = < Q , , , q0 , > if ( q0 , x ) * ( h, yaz ) for some symbol a {} and some strings y and z in ( {} )

uring Machines(Design & escription of Turing machines)

T-1:ch-9

OR-2

Constructing complex turing machines

Learn techniques for constructing turing machines


Hypothetical device that manipulates symbols on a strip of tape according to a table of rules

Lecture 15 Week 6

Lecture 16

Lecture 17

Term Paper,Test 1 uring Machines(Variants of uring machines)

T-1:ch-9

AV-1

Machines with stay option,multi track machines,Semi infinite tape machines

Understand design variation for turing machines


read-only Turing machine or Two-way deterministic finite-state automaton

uring Machines(Turing Machines Construction)

T-1:ch-9

AV-3

Techniques used for constructing turing machines

Understands the methods used for designing turing machines


( q , aababb ) shows that the Turing machine is currently in state q, the taper contents are the string aababb and the head is reading the last a of the string.

uring Machines(The hurch Turing thesis)

T-1:ch-9

OR-2

Alogrithm for Church Turing thesis

Learns about the concept of church turing


States that a function is algorithmically computable if and only if it is computable by a Turing machine.

uring Machines(Universal uring Machine)

T-1:ch-9

OR-3

Stored program computer

Understands working Peer Learning, of UTM Case Study Discussion and Demonstration of Animation

Electronic Computing Instrument" that now bears von Neumann's name: the von Neumann architecture

Week 6

Lecture 18

Week 7

Lecture 19

Lecture 20

Lecture 21

yntax Analysis(Ambiguity nd the formal power Series)

T-1:ch-9

DK-1 DK-2

Eliminating ambiguity

Understands the procedure to remove ambiguity


Topology,Opera tions, Universal property

yntax Analysis(Formal Properties of LL(k) and LR (k) Grammars)

T-1:ch-9

DK-3

L19 Parsing strategies

Learns about the features of LL and LR


They are easy to parse, either by LL parsers or by recursive descent parsers, and many computer languages are designed to be LL(1) for this reason


T-1:ch-9





T-1:ch-9




Learn the difference between different types of ets


ts terminals are the letters of $ \Sigma$, its non-terminals are the states of the automaton $ \cal {A}$, its start-symbol is the initial state of $ \cal {A}$,

L20 is revision L21 is revision

DK-3

L19 Parsing strategies L20 is revision L21 is revision

DK-3

L19 Parsing strategies L20 is revision L21 is revision

MID-TERM Week 8

Lecture 22 Formal Languages(Chomsky lassification of languages)

R-2:ch-7

OR-1 AV-1 AV-3

Definition of grammar

Week 8

Week 9

Lecture 23 Formal Languages (Languages and their elation)

R-2:ch-7

DK-2

Formal Language and their relation

Understand about the Peer Learning, relation of formal Case Study languages Discussion and Demonstration of Animation

Studies primarily the purely syntactical aspects of such languages—that is, their internal structural patterns.

Lecture 24

R-2:ch-7

OR-2

Linear grammar

Understand the concept of Linear grammar


Left-linear and Right-linear grammers

Lecture 25 Formal Languages(Regular Expressions)

R-2:ch-5

OR-2 OR-3

Definition of regular expression

Learn to construct simple regular expression


regexp ? switches? exp string ? matchVar? ? subMatchVar subMatchVar ...?

Lecture 26 Formal Languages(Context ensitive Languages)

R-2:ch-5

OR-2

Context sensitive Language

Learn about the concept of CSL


The union, intersection, concatenation and Kleene star of two contextsensitive languages is context-sensitive

Lecture 27

R-2:ch-5

AV-1

Introduction to parsing

Parse tree as a way to represent the derivation of a string from a grammar


Unambiguous and context-free grammars can be constructed that produce parse trees that obey all desired operator precedence and associativity rules.

R-2:ch-5

DK-3

Union,concatenation,co Learn to use closure mpliment , reversal properties to obtain more complex regular language


The regular operations: union K \cup L, concatenation K \circ L, and Kleene star L^*

Week 10 Lecture 28

Formal Languages(Linear rammars and regular Languages)

rammars(Parsing and Derivation)

rammars(Closure roperties)

Week 10 Lecture 29

rammars(Pigeonhole rincipal and pumping lemma)

R-2:ch-6

AV-1

Adversarial Game

Learn to handle regular languages with repeating patterns


Pumping lemma for regular languages and the pumping lemma for context-free languages and Ogden's lemma

rammars(Constructing Regular grammars)

R-2:ch-6

AV-2

Introduction to regular grammars

Learn to construct Peer Learning, regular expression for Case Study user dat avalidation Discussion and Demonstration of Animation

If L is regular i.e. accepted by an NFA, then L - {} is generated by a regular grammar.

T-1:Ch-10

OR-2 AV-2

Decidable problems concerning regular languages

Understands kinds of Peer Learning, problems that are Case Study undecidable Discussion and Demonstration of Animation

Let A contain all even-length strings, plus an undecidable collection of odd-length strings. Let B contain all oddlength strings concatenation AB consists of all strings and hence is decidable

Lecture 32 Decidability(Unpredictable languages)

T-1:Ch-10

OR-3

Decidability and Understand the Unpredictable languages concept of Unpredictable languages


Unpredictability approach for defining randomness in which the preditions are carried out by finite-state automata.

Lecture 33 Decidability(Halting roblems of Turing machines)

T-1:Ch-10

OR-2 DK-2

Problems in halting Turing machines

Understanding the halting problem of turing machines


Given a description of an arbitrary computer program, decide whether the program finishes running or continues to run forever

T-1:Ch-11

OR-1

Computability and turing model for computation

Understands various functions performed by partial recursive

Peer Learning, Case Study Discussion and

Addition,Subtra ction,Operations on integers and

Lecture 30

Week 11 Lecture 31 Decidability(Decidable languages)

Week 12 Lecture 34

omputability(Partial ecursive functions)

Week 12 Lecture 35

omputability(Basic oncepts)

T-1:Ch-11

AV-3

Steps of Computability

Understands about concepts of computability


Turingcomputable and µ-recursive functions, and the lambda calculus

omputability(Recursive functions)

T-1:Ch-11

OR-1

Computability Recursive functions

Understands computability recursive functions


Tower of hanoi ,factorial,fibnacc i

omputability(Partial Recursion)

T-1:Ch-11

DK-1

Partial functions

Understands concept Peer Learning, of partial recursive Case Study functions Discussion and Demonstration of Animation

1)Function symbols (for example, f, g, h, etc.), (2) variables for nonnegative integers (for example, x, y, z, etc.), (3) the constant 0, and (4) the successor function S(x)=x +1.

Lecture 36 Week 13 Lecture 37

Term Paper,Test 2 omputers and the science f computing(Idea of omputing)

R-2:ch-12

DK-1

Concept of computing

Learn the importance Peer Learning, of Computing Case Study machines Discussion and Demonstration of Animation

A variety of minor enhancements to this basic scheme are possible, and there are many ways to save unnecessary computation

omputers and the science f computing(Computing machines and languages)

R-2:ch-12

DK-2

Introduction of computing machines

Understands the Peer Learning, working of Case Study computing machines Discussion and Demonstration of Animation

Turing machine,Finite sate machines

T-1:Ch-11

AV-2 DK-1

Data structures used in programming

Understands the need of data structures

For exploring large patterns at great timedepths, sophisticated algorithms such as Hashlife may be useful.

omputers and the science f computing(Programming nd Data structures)


Week 13 Lecture 38

he Chomsky Hierarchy (Diagonalization)

R-2:ch-11

OR-2 DK-3

Chomsky Hierarchy problems

Understand the concept of Chomsky Hierarchy


Let R be a binary relation on a set A and let D = {a|a ? A, and (a, a) ? R}. For each a ? A, let Ra = {b|b ? A, and (a, b) ? R}. Then D is distinct from Ra for all a ? A.

he Chomsky Hierarchy (Enumerable Languages)

R-2:ch-11

OR-1

Parsing with CNF

Learns about the techniques for parsing


Recognizable, partially decidable, semidecidable or Turingacceptable

Lecture 39

he Chomsky Hierarchy (Acceptance and membership)

R-2:ch-11

AV-3

Chomsky Acceptance

Understands concept Peer Learning, of acceptance and Case Study membership Discussion and Demonstration of Animation

Week 14 Lecture 40

he Chomsky Hierarchy (Recursive languages)

R-2:ch-11

AV-3

L40 Understand the need Recursive languages in of recursive The Chomsky Hierarchy languages L41 is revision L42 is revision

Lecture 41


R-2:ch-11

AV-3


Lecture 42


R-2:ch-11

AV-3


SPILL OVER Week 15 Lecture 43

Spill Over

Lecture 44

Spill Over

A Streett automaton is an ?-automaton A that uses the following acceptance condition, for some set O of pairs (Ei,Fi) of sets of states


Universal Turing Machine and Linear Bounded Automata





Scheme for CA: Component

Term Paper,Test

Frequency

Out Of

2

3 Total :-

Details of Academic Task(s)

Each Marks Total Marks

10

20

10

20

AT No.

Objective

Term Paper,Test 1 To define the power of any computation model that would be determined by analysing formal languages

Topic of the Academic Task

Nature of Academic Task (group/individuals/field work

Unit I Individual Automata : Definition, Description and transition modes, NDFA and DFA, Mealy and Moore machine, Minimization of Finite Automata, Constructing simple automata, Handling end conditions, Handling reject states, Step by step method for constructing automata, States as Memory, Why finite number of states, Limitations of finite automata, Non deterministic finite automata Construction of Finite Automata : Construction of Finite Automata equivalent to Regular expression & vice versa, Pumping Lemma for regular sets & its applications Pushdown Automata : Definition, Acceptance, Pushdown Automata and Context Free Languages, Parsing and Pushdown automata, Constructing PDAs, Converting CFGs to PDAs, Converting PDAs to CFGs Unit II Context Free languages : Derivation trees, Ambiguity in Context free grammars, Simplification of context free grammars, The Chomsky & Greibach Normal Forms Context Free Grammars : The Kuroda Normal Form, One sided Context Sensitive Grammars, Unrestricted Languages Regular Languages and Expressions : Idea of formal languages, Languages of Automata, Regular expressions, Converting Regular expressions to automata Unit III Turing Machines : Representation, Language acceptability, Design & description of Turing machines, Variants of Turing machines, Turing Machines Construction, The Church Turing thesis, Universal Turing Machine Syntax Analysis : Ambiguity and the formal power Series, Formal Properties of LL (k) and LR(k) Grammars

Evaluation Mode

Allottment / submission Week

Based on student performance (scores) Each question will be multiple of 5. Total marks will be 30.

5/6

Term Paper,Test 2 To understand the concept of turing machines as special emphasis is laid on design and applications of Turing Machines

Unit IV Formal Languages : Chomsky classification of languages, Languages and their relation, Linear Grammars and regular Languages, Re gular Expressions, Context Sensitive Languages Grammars : Parsing and Derivation, Closure properties, Pigeonhole principal and pumping lemma, Constructing Regular grammars Unit V Decidability : Decidable languages, Unpredictable languages, Halting problems of Turing machines Computability : Partial recursive functions, Basic concepts, Recursive functions, Partial Recursion Computers and the science of computing : Idea of computing, Computing machines and languages, Programming and Data structures Unit VI The Chomsky Hierarchy : Enumerable Languages, Diagonalization, Acceptance and membership, Recursive languages

Individual

Based on student performance (scores) Each question will be multiple of 5. Total marks will be 30.

11 / 12

Term Paper,Test 3 To evaluate student performance

As per given topics

Individual

30 Marks (Mid Term report- 5 marks, End Term report- 15 marks, Viva / presentation10 marks)

4 / 10

List of suggested topics for term paper[at least 15] (Student to spend about 15 hrs on any one specified term paper) Sr. No.

Topic

1 Theory of Automata 2 Finite Automata 3 Regular Languages 4 Context Free Grammars 5 Push Down Automata 6 Turing Machines and Computability 7 NFA and Regular Expressions 8 Regular Grammar and Languages 9 Computability 10 Context Free Languages

12 Turing Machines 13 Chomsky Hierarchy 14 Computability and Undecidability 15 Deterministic Context Free Languages

cap 632

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