Course description

A bottom-up parser creates the parse tree for a given input string starting from leaves towards the root. A bottom-up parser tries to find the right-most derivation of the given input string in the reverse order. Bottom-up parsing is also known as shift-reduce parsing. Bottom-up parsing is the process of "reducing" a string ‘w’ to the start symbol of the grammar. At each reduction step, a particular substring matching the right-side of a production is replaced by the symbol on the left-side of the production. If the substring is chosen correctly, a right most derivation is traced out in reverse. A general style of bottom-up syntax analysis, known as shift-reduce parsing. Two types of bottom-up parsing: Operator-Precedence parsing - an easy to implement form of shift reduce parsing. LR parsing - a much more general form of Shift Reduce Parsing. LR parsing is used in a number of automatic parser generators. Informally a Handle of a string ‘w’ is a substring that matches the RHS of some production and whose reduction to the non-terminal on the LHS of the production represents one step along the reverse of a rightmost derivation. But not every substring that matches the right side of a production rule is handle. A rightmost derivation in reverse can be obtained by “handle-pruning.”

What will i learn?

  • Understanding Priority selection of operators by operator precedence parsing
  • Parsing the input string by Simple LR parser
  • Identification of most powerful parsing technique
  • Parsing the input string by Lookahead LR parser
  • Parsing the input string by Canonical LR parser

Requirements

  • Basics of Syntax analysis and Parsing
  • Prerequisites for Understanding Bottom-Up Parsing: Basic Knowledge of Programming: Familiarity with at least one programming language (e.g., C, Java, or Python) to understand the concepts related to syntax and language structure. Understanding of Formal Languages: Basic knowledge of formal languages, such as grammars, syntax, and productions. Understanding how language syntax is described using BNF (Backus-Naur Form) or EBNF (Extended BNF) will help in understanding parsing techniques. Mathematical Foundations: Some background in mathematics, particularly in set theory and logic, is useful since parsing involves manipulation of symbols and rules. Data Structures: A solid understanding of data structures, especially stacks, trees, and graphs, as these are commonly used in parsing algorithms. Algorithms: Basic knowledge of algorithms and computational theory, such as finite automata, context-free grammars, and parse trees, is helpful for understanding the underlying principles of parsing.
  • Course Materials and Tools: Computer and Internet Access: A computer with an internet connection is essential for accessing course content, watching videos, and participating in coding assignments. Compiler Design Tools: Familiarity with compiler construction tools like Yacc (Yet Another Compiler Compiler) or Bison (a modern version of Yacc) will be useful, though not always mandatory, as they implement bottom-up parsing techniques like LR parsing. Text Editor/IDE: An IDE (e.g., Visual Studio Code, Eclipse) or text editor for writing code and implementing parsing algorithms. Version Control System: Understanding how to use Git for source code management and collaboration can be helpful, especially for group projects or assignments.
  • Software Requirements: Yacc or Bison: For implementing bottom-up parsers using LR or LALR techniques. Most courses will guide you through setting up these tools. GCC Compiler: For compiling C programs that utilize Yacc/Bison. It’s commonly used alongside Yacc/Bison in C-based compiler design. Parser Generator Tools (optional): Tools such as ANTLR (ANother Tool for Language Recognition) or Flex may also be introduced for more advanced parser generation.

Frequently asked question

Bottom-Up Parsing is a type of parsing technique in compiler design where the parse tree is built starting from the leaf nodes (i.e., the terminals) and works its way upwards towards the root of the tree (the start symbol). The goal is to reduce the input string to the start symbol by applying production rules in reverse.

Top-Down Parsing starts from the start symbol and tries to derive the input string by applying production rules (e.g., recursive descent parsing). Bottom-Up Parsing, on the other hand, starts with the input string and attempts to reduce it to the start symbol by working from the leaves up to the root (e.g., Shift-Reduce Parsing).

Efficiency: Bottom-up parsers, particularly LR parsers (a type of bottom-up parser), can parse a broader class of grammars (LR(k) grammars) efficiently. These grammars include many practical programming languages. Error Detection: Bottom-up parsing is better at detecting errors in the input earlier than top-down parsers, which can be important for compiler robustness. Determinism: Bottom-up parsing can be more deterministic and does not require backtracking, making it more efficient for larger and more complex grammars. Handling Ambiguity: It is effective in parsing unambiguous and deterministic languages, like most programming languages, by ensuring a single path to reduce the input.

Shift-Reduce Parser: A simple form of bottom-up parsing where the input is shifted and reduced using the grammar’s production rules until the entire input is reduced to the start symbol. LR Parser: A more sophisticated form of bottom-up parsing that is capable of parsing a larger class of grammars, specifically LR(k) grammars, which include most programming language constructs. SLR(1): Simple LR with 1 token of lookahead. LALR(1): Look-Ahead LR with 1 token of lookahead, often used in practice due to its efficiency. Canonical LR(1): The most powerful form of LR parsing, capable of handling the largest class of grammars.

₹399

₹799

Lectures

8

Skill level

Beginner

Expiry period

Lifetime

Certificate

Yes

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