Introduction to Finite Automata and model Questions to Students
1. Theory of Computation
V SEMESTER
Sunil Kumar K N
Department of ISE
Cambridge Institute of Technology
2. Course Overview: Theory of Computation
• Semester: V
• Course Code: BCS503
• Credits: 04
• CIE Marks: 50
• SEE Marks: 50
• Total Marks: 100
• Exam Hours: 3
3. Course Objectives
1. Introduce core concepts in Automata and Theory of Computation.
2. Identify different Formal Language Classes and their Relationships.
3. Learn concepts of Grammars and Recognizers for different formal languages.
4. Prove or disprove theorems in automata theory using their properties.
5. Determine the decidability and intractability of Computational problems.
5. Course Outcomes
1. Write DFA, NFA, Epsilon-NFA and perform conversions.
2. Prove properties of regular languages.
3. Design context-free grammars and pushdown automata.
4. Design Turing machines for computational problems.
5. Explain decidability and undecidability concepts.
6. Suggested Learning Resources
•John E Hopcroft, Rajeev Motwani, Jeffrey D. Ullman –
Introduction to Automata Theory, Languages and Computation, Pearson.
•Elain Rich – Automata, Computability, and Complexity, Pearson Education, 2018.
•K.L.P Mishra, N Chandrashekaran – Theory of Computer Science, PHI, 2012.
•Michael Sipser – Introduction to the Theory of Computation, Cengage Learning, 2013.
•John C Martin – Introduction to Languages and Theory of Computation, Tata McGraw-Hill,
2013.
•Padma Reddy - Finite Automata and Formal Languages
7. Module 1 : Introduction to Automata
•Introduction to Finite Automata.
•Structural Representations.
•Automata and Complexity.
•Deterministic Finite Automata, Nondeterministic
Finite Automata.
•Application: Text Search.
•Finite Automata with Epsilon-Transitions.
8. Introduction to Finite Automata
Why Study Automata Theory?
Core of Computer Science: Automata and complexity are fundamental concepts.
Provides a theoretical framework for analyzing computation.
Helps in understanding limitations of machines and computational problems.
Applications of Automata Theory
Hardware Design: Used to model and verify the behavior of digital circuits.
Compiler Design: The lexical analyzer breaks down input text into logical components like
identifiers and keywords.
Text Scanning: Automata help in searching for patterns in large text datasets, such as web
pages.
9. Introduction to Finite Automata
Finite Automata Overview
•Finite Automata: A system that is always in one of a finite number of
states.
•States represent the system's memory of important historical inputs.
•Used when a finite number of states are sufficient to describe system
behavior.
Advantages of Finite Automata
Fixed Resources: Requires a finite set of resources to implement, such as circuits or
simple programs.
Efficient Decision Making: Decisions are based on limited data or specific code
positions, leading to simple, reliable systems.
10. Model Questions for Students:
Example 1: On-Off Switch Finite Automaton
Q1: Explain how a finite automaton can model the behavior of an on-off switch.
Include the following in your explanation:
• The number of states in the automaton.
• How the input (button press) affects the transitions between states.
• The concept of a start state and accepting state (if any) in this example.
Example 2: Finite Automaton for Keyword Recognition
Q2: Design a finite automaton that recognizes the keyword "then."
Your design should:
•Include states corresponding to each prefix of the word "then."
•Show how the input (letters of the word) moves the automaton between states.
•Indicate which state is the accepting state and explain why it is important.
