
- Automata Theory - Applications
- Automata Terminology
- Basics of String in Automata
- Set Theory for Automata
- Finite Sets and Infinite Sets
- Algebraic Operations on Sets
- Relations Sets in Automata Theory
- Graph and Tree in Automata Theory
- Transition Table in Automata
- What is Queue Automata?
- Compound Finite Automata
- Complementation Process in DFA
- Closure Properties in Automata
- Concatenation Process in DFA
- Language and Grammars
- Language and Grammar
- Grammars in Theory of Computation
- Language Generated by a Grammar
- Chomsky Classification of Grammars
- Context-Sensitive Languages
- Finite Automata
- What is Finite Automata?
- Finite Automata Types
- Applications of Finite Automata
- Limitations of Finite Automata
- Two-way Deterministic Finite Automata
- Deterministic Finite Automaton (DFA)
- Non-deterministic Finite Automaton (NFA)
- NDFA to DFA Conversion
- Equivalence of NFA and DFA
- Dead State in Finite Automata
- Minimization of DFA
- Automata Moore Machine
- Automata Mealy Machine
- Moore vs Mealy Machines
- Moore to Mealy Machine
- Mealy to Moore Machine
- Myhill–Nerode Theorem
- Mealy Machine for 1’s Complement
- Finite Automata Exercises
- Complement of DFA
- Regular Expressions
- Regular Expression in Automata
- Regular Expression Identities
- Applications of Regular Expression
- Regular Expressions vs Regular Grammar
- Kleene Closure in Automata
- Arden’s Theorem in Automata
- Convert Regular Expression to Finite Automata
- Conversion of Regular Expression to DFA
- Equivalence of Two Finite Automata
- Equivalence of Two Regular Expressions
- Convert Regular Expression to Regular Grammar
- Convert Regular Grammar to Finite Automata
- Pumping Lemma in Theory of Computation
- Pumping Lemma for Regular Grammar
- Pumping Lemma for Regular Expression
- Pumping Lemma for Regular Languages
- Applications of Pumping Lemma
- Closure Properties of Regular Set
- Closure Properties of Regular Language
- Decision Problems for Regular Languages
- Decision Problems for Automata and Grammars
- Conversion of Epsilon-NFA to DFA
- Regular Sets in Theory of Computation
- Context-Free Grammars
- Context-Free Grammars (CFG)
- Derivation Tree
- Parse Tree
- Ambiguity in Context-Free Grammar
- CFG vs Regular Grammar
- Applications of Context-Free Grammar
- Left Recursion and Left Factoring
- Closure Properties of Context Free Languages
- Simplifying Context Free Grammars
- Removal of Useless Symbols in CFG
- Removal Unit Production in CFG
- Removal of Null Productions in CFG
- Linear Grammar
- Chomsky Normal Form (CNF)
- Greibach Normal Form (GNF)
- Pumping Lemma for Context-Free Grammars
- Decision Problems of CFG
- Pushdown Automata
- Pushdown Automata (PDA)
- Pushdown Automata Acceptance
- Deterministic Pushdown Automata
- Non-deterministic Pushdown Automata
- Construction of PDA from CFG
- CFG Equivalent to PDA Conversion
- Pushdown Automata Graphical Notation
- Pushdown Automata and Parsing
- Two-stack Pushdown Automata
- Turing Machines
- Basics of Turing Machine (TM)
- Representation of Turing Machine
- Examples of Turing Machine
- Turing Machine Accepted Languages
- Variations of Turing Machine
- Multi-tape Turing Machine
- Multi-head Turing Machine
- Multitrack Turing Machine
- Non-Deterministic Turing Machine
- Semi-Infinite Tape Turing Machine
- K-dimensional Turing Machine
- Enumerator Turing Machine
- Universal Turing Machine
- Restricted Turing Machine
- Convert Regular Expression to Turing Machine
- Two-stack PDA and Turing Machine
- Turing Machine as Integer Function
- Post–Turing Machine
- Turing Machine for Addition
- Turing Machine for Copying Data
- Turing Machine as Comparator
- Turing Machine for Multiplication
- Turing Machine for Subtraction
- Modifications to Standard Turing Machine
- Linear-Bounded Automata (LBA)
- Church's Thesis for Turing Machine
- Recursively Enumerable Language
- Computability & Undecidability
- Turing Language Decidability
- Undecidable Languages
- Turing Machine and Grammar
- Kuroda Normal Form
- Converting Grammar to Kuroda Normal Form
- Decidability
- Undecidability
- Reducibility
- Halting Problem
- Turing Machine Halting Problem
- Rice's Theorem in Theory of Computation
- Post’s Correspondence Problem (PCP)
- Types of Functions
- Recursive Functions
- Injective Functions
- Surjective Function
- Bijective Function
- Partial Recursive Function
- Total Recursive Function
- Primitive Recursive Function
- μ Recursive Function
- Ackermann’s Function
- Russell’s Paradox
- Gödel Numbering
- Recursive Enumerations
- Kleene's Theorem
- Kleene's Recursion Theorem
- Advanced Concepts
- Matrix Grammars
- Probabilistic Finite Automata
- Cellular Automata
- Reduction of CFG
- Reduction Theorem
- Regular expression to ∈-NFA
- Quotient Operation
- Parikh’s Theorem
- Ladner’s Theorem
Applications of Context-Free Grammar
For a little recap, let us see the definitions of context-free grammar. Just like other grammars, we can define a context-free grammar using a four-tuple structure. These four components are −
- V − This represents the set of variables which are also known as non-terminals. Think of them as placeholders that can be replaced by other symbols.
- T − This is the set of symbols used in the grammar. We often call these terminals because they represent the final, indivisible elements of our language.
- P − This set of the production rules. These rules define how we can replace variables with other variables and terminals.
- S − Lastly, we have the start symbol. This specific non-terminal acts as the initial point from which we begin building strings in our language.
Importance of Production Rules
The defining characteristic of a CFG lies within its production rules. These rules are like to the following structure −
- LHS − Left-hand side, consisting of a single variable.
-
RHS − Right-hand side, potentially consisting of:
- Epsilon (ε), representing an empty string
- A single terminal symbol
- A string of terminals and/or variables
There is the flexibility of RHS. This distinguishes CFGs from regular grammars, which impose restrictions on the RHS, limiting it to a single terminal followed by a variable, a single variable followed by a terminal, or just a single terminal.
Let us take an example for a clear understanding. Consider a CFG designed to generate strings with at least two 'a's over the alphabet {a, b} −
V = {S, T} T = {a, b} P = { S -> TaTaT T -> aT | bT | } Start Symbol = S
In this example, 'S' and 'T' are variables, 'a' and 'b' are terminals, and the production rules define how variables can be replaced. For instance, the rule 'S → TaTaT'.
Applications of Context-Free Grammar
Let us see the applications of context-free grammars.
Programming Language Design and Implementation
CFGs are fundamental to defining the syntax of programming languages. The Backus-Naur Form (BNF) and Extended Backus-Naur Form (EBNF) notations, widely used for specifying programming language grammars. These are essentially context-free grammars. These grammars states the structure of programs, keeping the language's rules.
Compiler Construction: Parsing and Syntax Analysis
Compilers translate high-level code into machine-executable instructions. Compilers heavily rely on CFGs during the parsing phase. Parsing involves analyzing the syntactic structure of the input code based on the language's grammar.
CFGs are used for the construction of parsers, which are algorithms responsible for −
- Lexical Analysis − Grouping characters into meaningful units or tokens.
- Syntax Analysis − Verifying if the sequence of tokens conforms to the grammar rules.
- Building Parse Trees − Creating tree-like representations of the code's grammatical structure.
Markup Languages and Data Representation − Markup languages like HTML and XML, used for web development and data representation, they rely on CFG-based principles to define their structure. These languages use tags to define elements and attributes, and their hierarchical organization can be represented and validated using CFGs.
Natural Language Processing (NLP) − Natural language is inherently ambiguous and more complex than formal languages we learn in automata theory. The context-free grammars still play a significant role in NLP as well.
- Grammar Formalisms − CFGs are used in computational linguistics to model the grammatical structure of natural language, even if they can't capture all nuances.
- Parsing Natural Language − While challenging, parsing natural language with CFGs helps with tasks like identifying parts of speech and understanding sentence structure, these are crucial for applications like machine translation and sentiment analysis.
Conclusion
In this chapter, we explored the core idea of context-free grammars, starting from its definition and a simple example. Then, we highlighted a class of different application areas where contextfree grammars can be used. In the subsequent chapters of this tutorial, we will see context free grammars in further detail.