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