cap 632

8/11/2019 cap 632

http://slidepdf.com/reader/full/cap-632 1/17

Lovely Professional University, Punjab

Course Code Course Title Course Planner Lectures Tutorials Practicals Credits

CAP632 FORMAL LANGUAGES AND AUTOMATIONTHEORY

12962::Harjinder Kaur 3.0 0.0 0.0 3.0

Course Category Courses with conceptual focus

TextBooks

Sr No Title Author Edition Year Publisher Name

T-1 THEORY OF COMPUTERSCIENCE :AUTOMATA,LANGUAGES & COMPUTATION

K.L.P MISHRA & N.CHANDRASEKRAN

1st PHI (PRETICE HALL INDIA)

Reference Books

Sr No Title Author Edition Year Publisher Name

R-1 INTRODUCTION TO LANGUAGES& THE THEORY OFCOMPUTATION

JOHN C MARTIN 1st TATA MCGRAW HILL

R-2 THEORY OF COMPUTATION KAVI MAHESH 1st WILEY INDIA PVT LTDR-3 AN INTRODUCTION TO FORMAL

LANGUAGES AND AUTOMATAPETER LINZ 4th 2010 NAROSA PUBLISHING HOUSE PVT. LTD

Other Reading

Sr No Journals articles as Compulsary reading (specific articles, complete reference)

OR-1 http://cs.fit.edu/~dmitra/FormaLang/ ,

OR-2 http://www.mywbut.com/syllabus.php?mode=VT&paper_id=14&dept_id=2 ,

OR-3 http://www.gobookee.net/formal-languages-and-automata-theory-by-krithivasan/ ,

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 throughremote experimentation

AV-2 http://www.cse.cuhk.edu.hk/~andrejb/csc3130/f08/ To provide various tools for learning, including web recources, videolectures, animated demonstration and seld evaluation

AV-3 http://www.nptel.iitm.ac.in/courses/106106049/ To provide various tools for learning, including web recources, videolectures, animated demonstration and seld evaluation

LTP week distribution: (LTP Weeks)

Weeks before MTE 7

8/11/2019 cap 632


WeekNumber

LectureNumber

Broad Topic(Sub Topic) Chapters/Sections ofText/referencebooks

Other Readings,Relevant Websites,Audio Visual Aids,software and VirtualLabs

Lecture Description Learning Outcomes Pedagogical ToolDemonstration/Case Study /Images /animation / ppt

etc. Planned

Live Examples

Week 1 Lecture 1 Automata(Definition) T-1:Ch-1 AV-1 Introductory Lecture Students will learnabout the need anduse of TOC in thefield of ComputerScience

Peer Learning,Case StudyDiscussion andDemonstration ofAnimation

Automata theoryis the basis forthe theory offormallanguages

Lecture 2 Automata(Description andtransition modes)

T-1:Ch-3 AV-2 Complexity theoryComputability theoryAutomata theory

Students will learnabout the transitionmodes


Accept andGenerate modes

Lecture 3 Automata(NDFA and DFA) T-1:Ch-3 DK-1 NDFA is a variation ofthe FSM that will makeit much easier to designFSMs

Makes it easy todesign FSMs


DFA can modelsoftware thatdecides whetheror not onlineuser-input suchas emailaddresses arevalid

Week 2 Lecture 4 Automata(Mealy and Mooremachine)

T-1:Ch-3 DK-3 Variants of Finiteautomata

Students learn aboutFinite automata withoutput


A simple Mealymachine has oneinput and oneoutput,complexMealy machines

can havemultiple inputsas well asmultiple outputs

Automata(Minimization ofFinite Automata)

T-1:Ch-3 AV-2 Deterministic finiteautomata and exampleof a finite automata

Students learn toreduce a ComplexFinite Automata


Select one statein each set of thepartition final astherepresentativefor the set.Theserepresentatives

are states ofminimum DFA

Detailed Plan For Lectures

Weeks After MTE 7

Spill Over 3

8/11/2019 cap 632


Week 2 Lecture 4 Automata(Constructingsimple automata)

T-1:Ch-4 DK-2 Formal definition of afinite automaton

Students learn toDesignfinite automata


Defining Initialand FinalStates,CreatingTransitions,Deleting States andTransitions,Running the FA onMultiple Strings

Lecture 5 Automata(Handling endonditions)

T-1:Ch-4 OR-1 Regular operations ofsimple automata

Students learn theimportance of FiniteAutomata

conditions

Peer Learning,Case StudyDiscussion and

Demonstration ofAnimation

Useful forspecifyingbehavior of

systems that arenot expected toterminate, suchas hardware,operatingsystems andcontrol systems

Automata(Handling rejectstates)

T-1:Ch-4 OR-2 Proof techniques ofautomata states

Students learn theimportance of FiniteAutomatastates


All states have atransition for allpossible inputsignals. If aninput signal is

considered'illegal' it cannotbe rejected

Automata(Step by stepmethod for constructingutomata)

T-1:Ch-4 OR-3 To construct and analyseautomata behaviour

Learn the importanceof construction ofAutomata


Defining Initialand FinalStates,CreatingTransitions,Deleting States andTransitions,Running the FA onMultiple Strings

Automata(States as

Memory)

T-1:Ch-5 OR-2 To construct states to

compute functions

Learn the importance

of correspondingstates

Peer Learning,

Case StudyDiscussion andDemonstration ofAnimation

An automaton

may also containsome extramemory in theform of a stackin whichsymbols can bepushed andpopped

Automata(Why finitenumber of states)

T-1:Ch-5 OR-1 Process and acceptinfinite sets if inputstrings

Students learn theimportance ofAutomata states

Peer Learning,Case StudyDiscussion andDemonstration of

Animation

vendingmachines,elevators,trafficlights

8/11/2019 cap 632


Week 2 Lecture 5 Automata(Limitations offinite automata)

T-1:Ch-5 DK-2 Constructing automatato solve computingproblems

Learn the Limitationsof finite automata


FA is that theyhave only afinite number ofstates. Hence, afinite automatacan only "count"a finite numberof inputscenarios.

Lecture 6 Automata(Non deterministicfinite automata)

T-1:Ch-5 DK-3 Formal definition of anon deterministic finite

automata

Learn the importanceof NDFA Closure

under the regularoperations

Peer Learning,Case Study

Discussion andDemonstration ofAnimation

Does not requireinput symbols

for statetransitions andis capable oftransitioning tozero or two ormore states for agiven start stateand inputsymbol

onstruction of FiniteAutomata(Construction ofFinite Automata equivalent

to Regular expression &vice versa)

T-1:Ch-5 AV-3 Relation between FiniteAutomata RegularExpressions

Any FSM can beconverted to a regularexpression, and every

regular expressioncan be converted intoa nondeterministicFSM



Worksrecursively bysplitting an

expression intoits constituentsubexpressions,from which theNFA will beconstructedusing a set ofrules

onstruction of FiniteAutomata(Pumping Lemmafor regular sets & itspplications)

T-1:Ch-5 DK-1 Non regular LanguagesThe pumping lemma forregular languages

The pumping lemmafor Regular sets is away to convincestudents that certain

sets are not Regular


Animation

To prove a factabout all infiniteregularlanguages that

will be helpfulin proving thatspecificlanguages arenonregular.

Week 3 Lecture 7 Pushdown Automata(Definition)

T-1:Ch-7 DK-2 Describing the basics ofPush Down Automata

A push downautomaton PDA or isa type of automatonthat uses a stack fortemporary datastorage


They are morecapable thanfinite-statemachines butless capable thanTuringmachines.

8/11/2019 cap 632


Week 3 Lecture 7 Pushdown Automata(Acceptance)

T-1:Ch-7 AV-2 Types of acceptance byPushdown Automata

Students learn aboutthe technique foracceptance of string


The firstacceptancemode uses theinternal memory(state), thesecond theexternalmemory (stack).

Pushdown Automata(Pushdown Automata and

ontext Free Languages)

T-1:Ch-7 OR-1 Relationship betweenPush down Automataand Context Free

Languages

Learn aboutConnection betweenPush down Automata

and Context FreeLanguages



When thegrammarrewrites a

nonterminal, thePDA takes thetopmostnonterminalfrom its stackand replaces itby the right-hand part of agrammaticalrule

Lecture 8 Pushdown Automata(Parsing and Pushdown

utomata)

T-1:Ch-7 OR-2 Purpose of Parsing inautomata

Learn about TopDown and Bottom

Up Parsing



Top down andbottom up

parsing

Pushdown Automata(Constructing PDAs)

T-1:Ch-7 DK-3 To teach about theconstruction of PDA

Students solve theexamples of pushdown automata


Regarded asbeing "pusheddown" like atray dispenser ata cafeteria, sincethe operationsnever work onelements otherthan the top

elementLecture 9 Pushdown Automata

(Converting CFGs to PDAs)T-1:Ch-7 AV-1 Designing PDAs from

context free grammarsWays to simplifyCFGs


For eachpushdownautomaton Mone mayconstruct acontext-freegrammar G suchthat N(M)=L(G)

Pushdown Automata(Converting PDAs to CFGs)

T-1:Ch-7 AV-3 Designing PDAs toCFGs

Ways to simplifyPDAs



using the toolsunder the“Convert ?

Convert toGrammar” menuoption usingJFLAP

8/11/2019 cap 632


Week 3 Lecture 9 ontext Free languages(Derivation trees)

T-1:Ch-6 DK-1 Other way ofrepresenting a CFG

Parse tree as a way torepresent thederivation of a stringfrom a grammar


if we used aproduction A : := X1X2...Xn (ineither top-downor bottom-upparsing) then weconstruct a treewith node A andchildrenX1X2...Xn

Week 4 Lecture 10 ontext Free languages(Ambiguity in Context free

rammars)

T-1:Ch-6 AV-3 To ambiguity in contextfree grammars

Students learn theimportance ofAmbiguity with thehelp of examples


When there's aword which hastwo differentderivation tree

ontext Free languages(Simplification of contextfree grammars)

T-1:Ch-6 AV-2 Equivalence withcontext free grammars

Students learn theways to equivalentcontext freegrammars


Precisemechanism fordescribing themethods bywhich phrases insome naturallanguage are

built fromsmaller blocks,capturing the"block structure"of sentences in anatural way

Lecture 11 ontext Free languages(Thehomsky & Greibach

Normal Forms)

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

AV-3 Describing CNF Students learn toreduce grammar to aCNF


Normalform usuallyused in algebraicspecifications

ontext Free Grammars(The

Kuroda Normal Form)

R-3:Ch-6 AV-1 DescribingKuroda

Normal Form

Students learn the

importance of KNF

Peer Learning,


Every context-

sensitivelanguage whichdoes notgenerate theempty string canbe generated bya grammar inKuroda normalform

Lecture 12 ontext Free Grammars(One sided Context

ensitive Grammars)

R-3:Ch-6 OR-1 Elaborates concept ofKNF

Learns about theimplementation ofKNF



Noncontractinggrammar or alinear bounded

automaton

8/11/2019 cap 632


Week 4 Lecture 12 ontext Free Grammars(Unrestricted Languages)

R-3:Ch-6 DK-2 Implementation formaking restrictions

Learn the usage ofrestrictions


Grammars makeno realdistinctionbetweennonterminal andterminalsymbols

Regular Languages andExpressions(Idea of formallanguages)

R-3:Ch-6 AV-1 Introduction to formallanguage

Learn the concept offormal language


Animation

Every nonemptystring that doesnot contain "+"or "=" and does

not start with"0" is in L.

Week 5 Lecture 13 Regular Languages andExpressions(Languages ofAutomata)

R-3:Ch-6 OR-1 Highlights on Automata Understands theconcept of automaton


Generativemodel ,languagemodel

Regular Languages andExpressions(Regularxpressions)

R-3:Ch-6 DK-2 Recursive definition Learn to constructsimple regularexpression


The set ofstrings over{0,1} that end in3 consecutive1's.

(0 | 1)* 111

Regular Languages andExpressions(ConvertingRegular expressions toutomata)

R-3:Ch-6 AV-2 Mapping from elementsof regular expression toNFA

Learn to convertregular expression toequivalent automata


JLex, is togenerate thetransition tablesor to synthesizethe scannerprogram given ascannerspecification

Lecture 14 uring Machines(Representation)

T-1:ch-9 AV-1 Ways to design TuringMachines

Understands aboutFormal definition of aTuring machine


It consists of aninfinitely-longtape which actslike the memoryin a typicalcomputer, or anyother form ofdata storage

8/11/2019 cap 632


Week 5 Lecture 14 uring Machines(Languagecceptability)

T-1:ch-9 AV-3 Examples of Turingmachines andcomputable functions

Learn to constructturing machines


A string x is saidto be acceptedby a Turingmachine* T = <Q , , , q0 , > if ( q0 , x ) * ( h,yaz ) for somesymbol a {} andsome strings yand z in ( {} )

uring Machines(Design &

escription of Turingmachines)

T-1:ch-9 OR-2 Constructing complex

turing machines

Learn techniques for

constructing turingmachines

Peer Learning,


Hypothetical

device thatmanipulatessymbols on astrip of tapeaccording to atable of rules

Lecture 15 Term Paper,Test 1

Week 6 Lecture 16 uring Machines(Variants ofuring machines)

T-1:ch-9 AV-1 Machines with stayoption,multi trackmachines,Semi infinitetape machines

Understand designvariation for turingmachines


read-only Turingmachine orTwo-waydeterministicfinite-stateautomaton

uring Machines(TuringMachines Construction)

T-1:ch-9 AV-3 Techniques used forconstructing turingmachines

Understands themethods used fordesigning turingmachines


( q , aababb )shows that theTuring machineis currently instate q, the tapercontents are thestring aababband the head isreading the lasta of the string.

uring Machines(Thehurch Turing thesis) T-1:ch-9 OR-2 Alogrithm for ChurchTuring thesis Learns about theconcept of churchturing


States that afunction isalgorithmicallycomputable ifand only if it iscomputable by aTuring machine.

Lecture 17 uring Machines(Universaluring Machine)

T-1:ch-9 OR-3 Stored programcomputer

Understands workingof UTM


ElectronicComputingInstrument" thatnow bears vonNeumann'sname: the vonNeumannarchitecture

8/11/2019 cap 632


Week 6 Lecture 18 yntax Analysis(Ambiguitynd the formal power Series)

T-1:ch-9 DK-1DK-2

Eliminating ambiguity Understands theprocedure to removeambiguity


Topology,Operations, Universalproperty

Week 7 Lecture 19 yntax Analysis(FormalProperties of LL(k) and LR(k) Grammars)

T-1:ch-9 DK-3 L19 Parsing strategies

L20 is revisionL21 is revision

Learns about thefeatures of LL andLR


They are easy toparse, either byLL parsers or byrecursivedescent parsers,and many

computerlanguages aredesigned to beLL(1) for thisreason

Lecture 20 yntax Analysis(FormalProperties of LL(k) and LR(k) Grammars)





They are easy toparse, either byLL parsers or byrecursivedescent parsers,and manycomputer

languages aredesigned to beLL(1) for thisreason

Lecture 21 yntax Analysis(FormalProperties of LL(k) and LR(k) Grammars)





They are easy toparse, either byLL parsers or byrecursivedescent parsers,and manycomputerlanguages are

designed to beLL(1) for thisreason

MID-TERMWeek 8 Lecture 22 Formal Languages(Chomsky

lassification of languages)R-2:ch-7 OR-1

AV-1AV-3

Definition of grammar Learn the differencebetween differenttypes of ets


ts terminals arethe letters of $ \Sigma$,its non-terminalsare the states ofthe automaton $ \cal {A}$,its start-symbolis the initialstate of $ \cal{A}$,

8/11/2019 cap 632


Week 8 Lecture 23 Formal Languages(Languages and theirelation)

R-2:ch-7 DK-2 Formal Language andtheir relation

Understand about therelation of formallanguages


Studiesprimarily thepurelysyntacticalaspects of suchlanguages—thatis, their internalstructuralpatterns.

Lecture 24 Formal Languages(Linearrammars and regular

Languages)

R-2:ch-7 OR-2 Linear grammar Understand theconcept of Linear

grammar



Left-linear andRight-linear

grammers

Week 9 Lecture 25 Formal Languages(RegularExpressions)

R-2:ch-5 OR-2OR-3

Definition of regularexpression

Learn to constructsimple regularexpression


regexp ?switches? expstring ?matchVar? ?subMatchVarsubMatchVar...?

Lecture 26 Formal Languages(Contextensitive Languages)

R-2:ch-5 OR-2 Context sensitiveLanguage

Learn about theconcept of CSL



The union,intersection,

concatenationand Kleene starof two context-sensitivelanguages iscontext-sensitive

Lecture 27 rammars(Parsing andDerivation)

R-2:ch-5 AV-1 Introduction to parsing Parse tree as a way torepresent thederivation of a stringfrom a grammar


Unambiguousand context-freegrammars canbe constructedthat produceparse trees that

obey all desiredoperatorprecedence andassociativityrules.

Week 10 Lecture 28 rammars(Closureroperties)

R-2:ch-5 DK-3 Union,concatenation,compliment , reversal

Learn to use closureproperties to obtainmore complexregular language


The regularoperations:union K \cup L,concatenation K \circ L, andKleene star L^*

8/11/2019 cap 632


Week 10 Lecture 29 rammars(Pigeonholerincipal and pumping

lemma)

R-2:ch-6 AV-1 Adversarial Game Learn to handleregular languageswith repeatingpatterns


Pumping lemmafor regularlanguages andthe pumpinglemma forcontext-freelanguages andOgden's lemma

Lecture 30 rammars(ConstructingRegular grammars)

R-2:ch-6 AV-2 Introduction to regulargrammars

Learn to constructregular expression foruser dat avalidation



If L is regulari.e. accepted byan NFA, then L

- {} is generatedby a regulargrammar.

Week 11 Lecture 31 Decidability(Decidablelanguages)

T-1:Ch-10 OR-2AV-2

Decidable problemsconcerning regularlanguages

Understands kinds ofproblems that areundecidable


Let A contain alleven-lengthstrings, plus anundecidablecollection ofodd-lengthstrings. Let Bcontain all odd-length strings

concatenationAB consists ofall strings andhence isdecidable

Lecture 32 Decidability(Unpredictablelanguages)

T-1:Ch-10 OR-3 Decidability andUnpredictable languages

Understand theconcept ofUnpredictablelanguages


Unpredictabilityapproach fordefiningrandomness inwhich thepreditions arecarried out by

finite-stateautomata.

Lecture 33 Decidability(Haltingroblems of Turing

machines)

T-1:Ch-10 OR-2DK-2

Problems in haltingTuring machines

Understanding thehalting problem ofturing machines


Given adescription of anarbitrarycomputerprogram, decidewhether theprogram finishesrunning orcontinues to runforever

Week 12 Lecture 34 omputability(Partialecursive functions) T-1:Ch-11 OR-1 Computability andturing model forcomputation

Understands variousfunctions performedby partial recursive


Addition,Subtraction,Operationson integers andrational numbers

8/11/2019 cap 632


Week 12 Lecture 35 omputability(Basiconcepts)

T-1:Ch-11 AV-3 Steps of Computability Understands aboutconcepts ofcomputability


Turing-computable andµ-recursivefunctions, andthe lambdacalculus

omputability(Recursivefunctions)

T-1:Ch-11 OR-1 ComputabilityRecursive functions

Understandscomputabilityrecursive functions


Tower of hanoi,factorial,fibnacci

omputability(PartialRecursion)

T-1:Ch-11 DK-1 Partial functions Understands conceptof partial recursivefunctions


1)Functionsymbols (forexample, f, g, h,etc.), (2)variables fornonnegativeintegers (forexample, x, y, z,etc.), (3) theconstant 0, and(4) the successorfunction S(x)=x

+1.Lecture 36 Term Paper,Test 2

Week 13 Lecture 37 omputers and the sciencef computing(Idea ofomputing)

R-2:ch-12 DK-1 Concept of computing Learn the importanceof Computingmachines


A variety ofminorenhancements tothis basicscheme arepossible, andthere are manyways to saveunnecessarycomputation

omputers and the sciencef computing(Computing

machines and languages)

R-2:ch-12 DK-2 Introduction ofcomputing machines

Understands theworking ofcomputing machines


Turingmachine,Finitesate machines

omputers and the sciencef computing(Programmingnd Data structures)

T-1:Ch-11 AV-2DK-1

Data structures used inprogramming

Understands theneed of datastructures


For exploringlarge patterns atgreat time-depths,sophisticatedalgorithms suchas Hashlife maybe useful.

8/11/2019 cap 632


Week 13 Lecture 38 he Chomsky Hierarchy(Diagonalization)

R-2:ch-11 OR-2DK-3

Chomsky Hierarchyproblems

Understand theconcept of ChomskyHierarchy


Let R be abinary relationon a set A andlet D = {a|a ? A,and (a, a) ? R}.For each a ? A,let Ra = {b|b ?A, and (a, b) ?R}. Then D isdistinct from Rafor all a ? A.

he Chomsky Hierarchy(Enumerable Languages)

R-2:ch-11 OR-1 Parsing with CNF Learns about thetechniques forparsing


Recognizable,partiallydecidable,semidecidableor Turing-acceptable

Lecture 39 he Chomsky Hierarchy(Acceptance andmembership)

R-2:ch-11 AV-3 Chomsky Acceptance Understands conceptof acceptance andmembership


A Streettautomaton is an?-automaton Athat uses thefollowingacceptance

condition, forsome set O ofpairs (Ei,Fi) ofsets of states

Week 14 Lecture 40 he Chomsky Hierarchy(Recursive languages)

R-2:ch-11 AV-3 L40Recursive languages inThe Chomsky Hierarchy


Understand the needof recursivelanguages


UniversalTuring Machineand LinearBoundedAutomata

Lecture 41 he Chomsky Hierarchy(Recursive languages)

R-2:ch-11 AV-3 L40Recursive languages in

The Chomsky Hierarchy


Understand the needof recursive

languages



UniversalTuring Machine

and LinearBoundedAutomata

Lecture 42 he Chomsky Hierarchy(Recursive languages)

R-2:ch-11 AV-3 L40Recursive languages inThe Chomsky Hierarchy


Understand the needof recursivelanguages


UniversalTuring Machineand LinearBoundedAutomata

SPILL OVER

Week 15 Lecture 43 Spill Over

Lecture 44 Spill Over

Lecture 45 Spill Over

8/11/2019 cap 632


Scheme for CA:

Component Frequency Out Of Each Marks Total Marks

Term Paper,Test 2 3 10 20

Total :- 10 20

Details of Academic Task(s)

8/11/2019 cap 632


AT No. Objective Topic of the Academic Task Nature of Academic Task(group/individuals/field

work

Evaluation Mode Allottment /submission Week

Term Paper,Test 1 To define the powerof any computationmodel that would bedetermined byanalysing formallanguages

Unit IAutomata : Definition, Description and transition modes, NDFAand DFA, Mealy andMoore machine, Minimization of Finite Automata, Constructingsimple automata,Handling end conditions, Handling reject states, Step by stepmethod for constructingautomata, States as Memory, Why finite number of states,

Limitations of finiteautomata, Non deterministic finite automataConstruction of Finite Automata : Construction of FiniteAutomata equivalent toRegular expression & vice versa, Pumping Lemma for regularsets & its applicationsPushdown Automata : Definition, Acceptance, PushdownAutomata and ContextFree Languages, Parsing and Pushdown automata, ConstructingPDAs, ConvertingCFGs to PDAs, Converting PDAs to CFGsUnit IIContext Free languages : Derivation trees, Ambiguity in Context

free grammars,Simplification of context free grammars, The Chomsky &Greibach Normal FormsContext Free Grammars : The Kuroda Normal Form, One sidedContext SensitiveGrammars, Unrestricted LanguagesRegular Languages and Expressions : Idea of formal languages,Languages of Automata, Regular expressions, Converting Regular expressionsto automataUnit IIITuring Machines : Representation, Language acceptability,

Design & description of Turing machines, Variants of Turing machines, Turing MachinesConstruction, TheChurch Turing thesis, Universal Turing MachineSyntax Analysis : Ambiguity and the formal power Series, FormalProperties of LL(k) and LR(k) Grammars

Individual Based on studentperformance(scores) Eachquestion will bemultiple of 5. Totalmarks will be 30.

5 / 6

T P T 2 T d d h U i IV I di id l B d d 11 / 12

8/11/2019 cap 632


Term Paper,Test 2 To understand theconcept of turingmachines as specialemphasis is laid ondesign andapplications ofTuring Machines

Unit IVFormal Languages : Chomsky classification of languages,Languages and theirrelation, Linear Grammars and regular Languages, RegularExpressions, ContextSensitive LanguagesGrammars : Parsing and Derivation, Closure properties,Pigeonhole principal andpumping lemma, Constructing Regular grammarsUnit VDecidability : Decidable languages, Unpredictable languages,Halting problems of Turing machinesComputability : Partial recursive functions, Basic concepts,Recursive functions,Partial RecursionComputers and the science of computing : Idea of computing,Computingmachines and languages, Programming and Data structuresUnit VIThe Chomsky Hierarchy : Enumerable Languages,Diagonalization, Acceptance andmembership, Recursive languages

Individual Based on studentperformance(scores) Eachquestion will bemultiple of 5. Totalmarks will be 30.

11 / 12

Term Paper,Test 3 To evaluate student

performance

As per given topics Individual 30 Marks (Mid

Term report- 5marks, End Termreport- 15 marks,Viva / presentation-10 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 Computability10 Context Free Languages

11 Grammars

12 T i M hi

8/11/2019 cap 632


12 Turing Machines

13 Chomsky Hierarchy

14 Computability and Undecidability

15 Deterministic Context Free Languages

cap 632

Documents