π Tokenization is the process of counting the number of tokens in a given code segment.
π’ Tokens can be classified into seven categories: identifiers, operators, constants, keywords, literals, punctuators, and special characters.
βοΈ In the provided source code, the first token encountered is the keyword 'end', followed by the identifier 'main'.
π The video discusses tokenization in lexical analysis, which involves categorizing different elements of a code into tokens.
𧩠Tokens can be categorized into punctuators, keywords, identifiers, and operators.
π’ The example code mentioned in the transcription demonstrates the process of tokenization by incrementing a count for each encountered token.
β‘ The lexical analyzer scans the source code line by line, counting each token it encounters.
π€ Identifiers and fixed values are categorized as tokens and increase the token count.
β Punctuators, like the comma, also increase the token count when encountered.
π There are 27 tokens in the given code.
βοΈ Identifiers, operators, and punctuators are the main token categories.
π’ The count of tokens increases as we encounter identifiers, operators, and punctuators in the code.
π The video explains how to tokenize a program using a lexical analyzer.
βοΈ The process involves identifying different tokens in the program, such as identifiers, literals, and punctuators.
π The token count increases as each token is encountered and categorized.
π‘ The video explains the concept of tokenization in the lexical analysis process.
π Tokens are identified based on different types such as punctuators, keywords, identifiers, and constants.
π’ The example code in the video contains 39 tokens.
β The video introduces the concept of a Lexical Analyzer and its role in counting tokens in a code segment.
β Tokens include punctuators, operators, constants, and string literals, and the Lexical Analyzer counts every occurrence of tokens.
β In the next session, numerical problems related to the Lexical Analyzer will be solved.
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