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2. DISCRETE MATHEMATICS
&
GRAPH THEORY
For
Computer Science
&
Information Technology
By
www.thegateacademy.com

3. Syllabus DMGT
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Syllabus for
Discrete Mathematics & Graph Theory
Connectivity; spanning trees; Cut vertices & edges; covering; matching; independent
sets; Colouring; Planarity; Isomorphism.
Analysis of GATE Papers
(DDiissccrreettee MMaatthheemmaattiiccss && GGrraapphh TThheeoorryy)
Year Percentage of marks Overall Percentage
2013 9.00
14.66 %
2012 10.00
2011 10.00
2010 7.00
2009 10.66
2008 18.00
2007 17.33
2006 16.67
2005 20.00
2004 19.33
2003 23.33

4. Content DMGT
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C O N T E N T S
Chapter Page No.
#1. Mathematical Logic 1 - 24
 Syntax 1
 Propositional Logic 1 - 4
 First order logic 5 - 7
 Disjunction Normal Form 7
 Solved Examples 8 - 16
 Assignment 1 17 - 18
 Assignment 2 19 - 20
 Answer Keys 21
 Explanations 21 - 24
#2. Combinatorics 25 - 52
 Introduction 25
 Permutations 26 – 29
 The Inclusion-Exclusion Principle 29 – 31
 Derangements 31 - 32
 Recurrence Relations 32 – 37
 Solved Examples 38 - 40
 Assignment 1 41 - 43
 Assignment 2 43 - 46
 Answer Keys 47
 Explanations 47 - 52
#3. Sets and Relations 53 - 92
 Sets 53 - 55
 Venn Diagram 55 - 58
 Poset 58 - 60
 Binary Relation 60 - 64
 Lattice 64 - 67
 Functions 67 - 68
 Groups 68 - 72
 Solved Examples 73 - 77

5. Content DMGT
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 Assignment 1 78 - 81
 Assignment 2 81 - 85
 Answer Keys 86
 Explanations 86 - 92
#4. Graph Theory 93 - 130
 Introduction 93 - 94
 Degree 94 – 95
 The Handshaking Theorem 95 – 97
 Some Special Graph 97 - 99
 Cut vertices & Cut Edges 99 - 100
 Euler Path & Euler Circuit 101
 Hamiltonian Path & Circuits 101 - 103
 Kuratowski Theorem 104
 Four Colour Theorem 104 - 106
 Rank & Nullity 107
 Solved Examples 108 - 113
 Assignment 1 114 - 117
 Assignment 2 118 - 123
 Answer Keys 124
 Explanations 124 - 130
Module Test 131 - 143
 Test Questions 131 - 137
 Answer Keys 138
 Explanations 138 - 143
Reference Books 144

6. Chapter 1 DMGT
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CHAPTER 1
Mathematical Logic
Logic is a formal language. It has syntax, semantics and a way of manipulating expressions in the
language.
Syntax
Set of rules that define the combination of symbols that are considered to be correctly
structured.
 Semantics give meaning to legal expressions.
 A language is used to describe about a set
 Logic usually comes with a proof system which is a way of manipulating syntactic
expressions which will give you new syntactic expressions
 The new syntactic expressions will have semantics which tell us new information about
sets.
 In the next 2 topics we will discuss 2 forms of logic
1. Propositional logic
2. First order logic
Propositional Logic
 Sentences are usually classified as declarative, exclamatory interrogative, or imperative
 Proposition is a declarative sentence to which we can assign one and only one of the truth
values “true” or “false” and called as zeroth-order-logic.
 Prepositions can be combined to yield new propositions
Assumptions about propositions
 For every proposition p, either p is true or p is false
 For every proposition p, it is not the case that p is both true and false.
 Propositions may be connected by logical connective to form compound proposition. The
truth value of the compound proposition is uniquely determined by the truth values of
simple propositions.
 An algebraic system ({F, T}, V, ∧, -) where the definitions of components are.
-A tautology corresponds to the constant T and a contradiction corresponds to constant F.
The definitions of ∧, V and  are given below.
V F T ∧ F T 
F F T F F F F T
T T T T F T T F
 The negation of a propositions p can be represented by the algebraic expression p
 The conjunction of two propositions p and q can be represented as an algebraic expression
“p∧q”

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Truth Table
 The disjunction of two propositions p and q can be represented as an algebraic expression
“pVq”
 Compound propositions can be represented by a Boolean expression
The truth table of a compound proposition is exactly a tabular description of the value of the
corresponding Boolean expression for all possible combinations of the values of the atomic
propositions.
Example-1
“I will go to the match either if there is no examination tomorrow or if there is an examination
tomorrow and the match is a championship tournament”
Solution
p = “there is an examination tomorrow”
q = “the match is a championship tournament”
∴ I will go the match if the position p V (p ∧ q)is true
 A proposition obtained from the combination of other propositions is referred to as a
compound propositions.
 Let p and q be two propositions, then define the propositions as “p then q”, denoted as
(p→q) is (“p implies ”q)
 This is true, if both p and q are true or if p is false.
 It is false if p is true and q is false specified as in the table
Truth Table
p
T
q
T
T
F
F
T
F F
p ⟶ q
T
F
T
T
p
T
q
T
T
F
F
T
F F
p ∨ q
T
T
T
F
p
T
q
T
T
F
F
T
F F
p q
T
F
F
F

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Example-2
“The temperature exceeds 700C” and “The alarm will be sounded” denoted as p and q
respectively.
 “If the temperature exceeds 700C then the alarm will be sounded “ = r i.e. it is true if the
alarm is sounded when the temperature exceeds 700C (p & q are true) and is false if the alarm
is not sounded when the, temperature exceeds 700C. (p is true & q is false).
 p ↔ q is true if both p and q are true or If both p and q are false
 It is false if p is true while q is false and if p is false while q is true.
 If p and q are 2 propositions then “p bi implication q” is a compound proposition denoted by
Truth Table
Example-3
p = “a new computer will be acquired”
q = “additional funding is available”
Consider the proposition, “A new computer will be acquired if and only if additional funding is
available” = r.
- ‘‘r’’ is true if a new computer is indeed acquired when additional funding is available (p
and q are true)
- the proposition r is also true if no new computer is acquired when additional funding is
not available (p and q are false)
- The r is false if a new computer acquired. Although no additional funding is available. (P is
true & q is false)
- “r” is false if no new computer is acquired although additional funding is available (p is
false & q is true)
 Two compound propositions are said to be equivalent if they have the same truth tables.
Replacement of an algebraic expressions involving the operations ⇢ and ↔ by equivalent
algebraic expressions involves only the operations ∧, V and
Equation
p q p→ q ~p ~p V q
T T T F T
T F F F F
F T T T T
F F T T T
∴ p → q = p v q
Similarly p ↔ q = (p∧q) V (~p ∧ ~q)
p
T
q
T
T
F
F
T
F F
p q
T
F
F
T

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Example-4
p → q = (~p v q)
= ~ ~ (q) v ~p
= ~q → ~ p
Given below are some of the equivalence propositions.
~(~( ))
~( ∨ ) ~ ∧ ~
~( ∧ ) ~ ∨ ~
⟶ ~ ∨
(~ ∨ ) ∧ (~ ∨ ) ( ∧ ) ∨ ( ∧ ) ( → ) ∧ ( → )
 A propositional function is a function whose variables are propositions
 A propositional function p is called tautology if the truth table of p contains all the entries
as true
 A propositional function p is called contradiction if the truth table of p contains all the
entries as false
 A propositional function p which is neither tautology nor contradiction is called
contingency.
 A proposition p logically implies proposition q. If ⟶ is a tautology.
 Inference will be used to designate a set of premises accompanied by a suggested
conclusion.
(p ∧ p ∧ p p ) ⟶ Q
Here each p is called premise and Q is called conclusion.
 If (p ∧ p ∧ p p ) ⟶ Q is tautology then we say Q is logically derived from p ∧ p p
i.e., from set of premises, otherwise it is called invalid inference.
Rules of Inference for Propositional Logic
Inference rule Tautology Name
∴ (p∧(p→q)) → q Modus ponens (mode that affirms)
∴

→

(q∧(p→q))→p Modus tollens (mode that denies)
∴
→
→
→
((p→q) ∧(q→r)) →(p→r) Hypothetical syllogism
∴
∨
 ((p∨q)∧(p))→q Disjunctive syllogism
∴
∨q
p→(p ∨ q) Addition
∴
∧
(p ∧ q)→p Simplification
∴
∧
((p) ∧(q)) →(p∧q) Conjunction
∴
∨
 ∨
∨
((p ∨q) ∧(p∨r) →(q∨r) Resolution

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First Order Logic
1. Let A be a given set. A propositional function (or an open sentence or condition) definedon A
is an expression p(x) which has the property that p(a) is true or false for each ‘a’ in A. That
is, p(x) becomes a statement (with a truth value) whenever any element a ∈ A is
substituted for the variable x.
2. The set A is called the domain of p(x), and the set Tp of all elements of A for which p(a) is
true is called the truth set of p(x).
Tp = {x | x ∈ A, p(x) is true} or Tp = {x | p(x)}.
3. Frequently, when A is some set of numbers, the condition p(x) has the form of an equation
or inequality involving the variable x.
4. The symbol ∀ which reads “for all” or “for every” is called the universal quantifier.
5. The expression (∀x∈A) p(x) or ∀x p(x)is true if and only if p(x)is true for all x in A.
6. The symbol ∃ which reads “there exists” or “for some” or “for at least one” is called the
existential quantifier.
7. The expression (∃x ∈ A)p(x) or ∃x, p(x) is true if and only if p(a) is true for at least one
element x in A.
Sentence Abbreviated Meaning
∀ x, F(x) all true
∃x, F(x) at least one true
~,∃x, F(x)] none true
∀ x, ,~F(x)- all false
∃x, ,~F(x)- at least one false
- (∃x,[~F(x)]) none false
~(∀ x,,F(x)-) not all true
~(∀ x, ,~F(x)-) not all false
“all true” ∀x, F(x)=~,∃x,~F(x)- “none false”
“all false” (∀x, ,~F(x)-+=*~, ∃x, F(x)-) “none true”
“not all true” (~,∀x, F(x)-)=(∃x, ,~F(x)) “at least one false”
“not all false” (~,∀x,~F(x)])= ∃x, F(x) “at least one true”
Statement Negation
“all true” ∀x, F(x) ∃x, ,~F(x)- “ at least one is false”
“at least one is false” ∃x, ,~F(x)- ∀x, F(x) “all true”
“all false” ∀x, ,~F(x)- ∃x, F(x) “at least one is true”
“at least one is true” ∃x, F(x) ∀x, ,~F(x)- “all false”

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We see that to form the negation of a statement involving one quantifier, we need to only change
the quantifier from universal to existential, or from existential to universal and negate the
statements which it quantifies.
Sentences with Multiple Quantifiers
In general if P (x, y) is any predicate involving the two variables x and y, then the following
possibilities exist
(∀x)(∀y)P (x,y)
(∃x)(∀y)P (x,y) (∃x)(∃y) P (x,y)
(∀y)(∀x)P (x,y)
(∀y)(∃x)P (x,y)
Rules of Inference For Quantified Propositions
“Universal Instantiation”
If a statement of the form ∀x, P(x) is assumed to be true then the universal quantifier can be
dropped to obtain that P(c) is true for any arbitrary object c in the universe. This rule may be
represented as
∀ , ( )
∴ P(C)
“Universal Generalization”
If a statement P(c) is true for each element c of the universe, then the universal quantifier may
be prefixed to obtain ∀x, P(x), In symbols, this rule is
( )
∴ ∀ , ( )
This rule holds provided we know P(c) is true for each element c in the universe.
“Existential Instantiation”
If ∃x, P(x) is assumed to be true, then there is an element c in the universe such that P(c) is true
This rule takes the form.
∃ , ( )
∴ ( ) c
“Existential Generalization”
If P(c) is true for some element c in the universe, then ∃x, P(x) is true In symbols, we have
P(c)for some c
∴ ∃x, P(x)
Generally speaking, in order to draw conclusions from quantified premises, we need to remove
quantifiers properly, argue with the resulting propositions, and then properly prefix the correct
quantifiers.