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Understanding Lexical Analyzer

Authored by RAMESH CSE

Computers

University

Used 1+ times

Understanding Lexical Analyzer
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15 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the primary purpose of a lexical analyzer?

To manage memory allocation during runtime.

To compile the source code into machine language.

To optimize the execution speed of the program.

To convert source code into tokens for further processing.

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Define tokenization in the context of compilers.

Tokenization is the process of converting a sequence of characters in source code into a sequence of tokens.

Tokenization is the method of debugging source code during compilation.

Tokenization is the process of compiling source code into machine code.

Tokenization refers to the optimization of code execution in compilers.

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a lexeme? Give an example.

The word 'run' is a lexeme, encompassing its various forms like 'runs', 'running', and 'ran'.

The word 'happy' is a lexeme, but it has no variations.

The word 'jump' is a lexeme, only referring to its base form.

A lexeme is a type of punctuation mark, like a comma.

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How do tokens differ from lexemes?

Tokens are categories of meaning; lexemes are the actual character sequences.

Tokens represent specific instances; lexemes are general concepts.

Tokens are used in programming; lexemes are used in natural language.

Tokens are the actual character sequences; lexemes are categories of meaning.

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Explain the role of regular expressions in lexical analysis.

Regular expressions help define patterns for recognizing tokens in lexical analysis.

Regular expressions are primarily for data storage and retrieval.

Regular expressions are only applicable in web development.

Regular expressions are used to compile source code directly.

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the significance of a finite automaton in tokenization?

Finite automata enable efficient pattern recognition for tokenization.

Finite automata are used for data storage in databases.

Finite automata are only applicable in natural language processing.

Finite automata are primarily for graphical user interface design.

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Describe the process of identifying tokens from a source code.

Formatting the code for better readability

The process of identifying tokens from source code involves reading the code, removing comments, defining token patterns, scanning the code, and extracting tokens.

Running the code to check for errors

Compiling the code into machine language

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