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# Theory of Computation by Puntambekar: A Comprehensive Guide for Students and Professionals

Theory of computation is a fascinating subject that explores the fundamental capabilities and limitations of computers. It deals with questions such as: What can computers do and what can they not do? How efficiently can computers solve certain problems? How can we design and analyze algorithms and data structures for various computational tasks?

## Introduction

### What is theory of computation?

Theory of computation is a branch of computer science and mathematics that studies the nature and properties of computational models, such as automata, formal languages, grammars, algorithms, complexity classes, computability, decidability, and undecidability. It also investigates the relationships between these models and their applications in various domains.

### Why is theory of computation important?

Theory of computation is important because it provides a theoretical foundation for understanding the power and limitations of computers and algorithms. It helps us to classify problems according to their difficulty and solvability, and to design efficient and correct solutions for them. It also helps us to appreciate the beauty and elegance of abstract mathematical concepts and their connections to real-world problems.

### What are the main topics covered in theory of computation?

Some of the main topics covered in theory of computation are:

• Strings, alphabets, languages, and operations on them.

• Finite automata, deterministic and non-deterministic automata, regular expressions, regular languages, and closure properties.

• Context-free grammars, context-free languages, pushdown automata, parsing techniques, and closure properties.

• Turing machines, variants of Turing machines, decidability, undecidability, reducibility, and Rice's theorem.

• Complexity theory, time complexity, space complexity, polynomial-time algorithms, NP-completeness, NP-hardness, Cook's theorem, and P versus NP problem.

### Who is the author?

The author of Theory of Computation is Anuradha A. Puntambekar. She is a former assistant professor in Vishwakarma Institute of Technology (VIT) and PES Modern College of Engineering, Pune. She has expertise in different topics like data structures, compiler design, theory of computation, design and analysis of algorithms, object-oriented programming, database management systems, and web technologies. She has also researched on heterogeneous clustering and published papers on it.

### What are the features of the book?

Some of the features of Theory of Computation by Anuradha A. Puntambekar are:

• It provides a comprehensive and consistent coverage of concepts of automata theory, formal languages, and computation.

• It explains the content in a simple and straightforward language, with examples and diagrams to illustrate the points.

• It includes a large number of solved problems and exercises to test the understanding of the readers.

• It covers all the GATE topics in detail without getting verbose.

• It is suitable for undergraduate and postgraduate students of computer science and engineering, as well as for professionals and researchers in the field.

### How is the book organized?

The book is organized into seven chapters, as follows:

• Chapter 1: Introduction to Automata Theory. This chapter gives an overview of the subject, its history, applications, and basic definitions.

• Chapter 2: Finite Automata. This chapter introduces finite automata, deterministic and non-deterministic automata, regular expressions, regular languages, and their properties and operations.

• Chapter 3: Context-Free Grammars and Languages. This chapter introduces context-free grammars, context-free languages, pushdown automata, parsing techniques, and their properties and operations.

• Chapter 4: Turing Machines. This chapter introduces Turing machines, variants of Turing machines, decidability, undecidability, reducibility, and Rice's theorem.

• Chapter 5: Complexity Theory. This chapter introduces complexity theory, time complexity, space complexity, polynomial-time algorithms, NP-completeness, NP-hardness, Cook's theorem, and P versus NP problem.

• Chapter 6: Miscellaneous Topics. This chapter covers some additional topics, such as recursive functions, recursive enumerable languages, linear bounded automata, context-sensitive languages, Post correspondence problem, Chomsky hierarchy, and pumping lemmas.

• Chapter 7: Solved Question Papers. This chapter contains solved question papers from previous GATE exams on theory of computation.

### Option 2: Google Books preview

Another way to download Theory of Computation by Anuradha A. Puntambekar for free is to use the Google Books preview feature. This feature will allow you to preview some pages of the book online before buying it. You can also search for specific keywords or phrases within the book. However, this feature may not show you the entire content of the book or allow you to download it.

## Conclusion

### Summary of the main points

• Theory of computation is a subject that studies the fundamental capabilities and limitations of computers and algorithms.

concepts and topics of theory of computation in a simple and straightforward language.

### Call to action

If you are looking for a good book to learn theory of computation, we recommend you to check out Theory of Computation by Anuradha A. Puntambekar. You can download it for free using any of the options mentioned above. However, if you want to support the author and get the full content of the book, you can also buy it from online or offline stores.

## FAQs

### What is the difference between deterministic and non-deterministic automata?

A deterministic automaton is an automaton that has only one possible transition for each state and input symbol. A non-deterministic automaton is an automaton that can have more than one possible transition for each state and input symbol.

### What is the difference between regular and context-free languages?

A regular language is a language that can be recognized by a finite automaton or generated by a regular expression. A context-free language is a language that can be recognized by a pushdown automaton or generated by a context-free grammar.

### What is the difference between decidability and undecidability?

A problem is decidable if there exists an algorithm that can always give a correct yes or no answer for any instance of the problem. A problem is undecidable if there does not exist such an algorithm.

### What is the difference between NP-completeness and NP-hardness?

A problem is NP-complete if it belongs to the class NP and every other problem in NP can be reduced to it in polynomial time. A problem is NP-hard if every problem in NP can be reduced to it in polynomial time, but it may or may not belong to NP.

### What is the P versus NP problem?

The P versus NP problem is one of the most famous open problems in computer science and mathematics. It asks whether the class P (the set of problems that can be solved in polynomial time) is equal to the class NP (the set of problems that can be verified in polynomial time). 71b2f0854b

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