
- 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
Reduction of Context-Free Grammars (CFG)
In this chapter, we will explain how to make the context free grammars simpler. As we know, not all CFGs are created equal. Some may contain unnecessary or redundant parts that make them harder to work with. In this article, we will see how to simplify CFGs by removing these unnecessary elements. This process is called reduction or simplification of context-free grammars. Here, we will go through some examples for a better understanding.
Why Do We Need to Simplify of Context-Free Grammars?
We must understand why we need simplification of contextfree grammars. Simplifying CFGs is important for several reasons −
- It makes the grammar easier to understand and work with.
- It prepares the grammar for conversion into special forms, like Chomsky Normal Form.
- It can make parsing and other algorithms more efficient.
Types of Redundant Productions
There are three main types of productions (rules) in CFGs that we often want to remove:
- Useless productions
- ε (epsilon) productions
- Unit productions
Let us look at each of these in detail.
Removing Useless Productions
Useless Productions are rules in the grammar that can never be used to generate a string in the language. They come in two characteristics −
- Productions that can never be reached from the start symbol
- Productions that can never lead to a string of terminals
Example of Useless Productions
Let us look at an example grammar −
$$\mathrm{S\: \rightarrow\: abS\: | \: abA \: | \: abB}$$
$$\mathrm{A\: \rightarrow\: cd}$$
$$\mathrm{B\: \rightarrow\: aB}$$
$$\mathrm{C\: \rightarrow\: dc}$$
In this grammar, the production C → dc is useless because C can never be reached from the start symbol S.
The production B → aB is useless because it can never terminate (lead to a string of only terminals).
How to Remove Useless Productions?
To remove useless productions, we follow these steps −
- Find all variables that can derive terminal strings.
- Remove productions with variables that can't derive terminal strings.
- Find all variables reachable from the start symbol.
- Remove productions with variables not reachable from the start symbol.
After applying these steps, our grammar becomes −
$$\mathrm{S\: \rightarrow\: abS \: | \: abA}$$
$$\mathrm{A\: \rightarrow\: cd}$$
Removing ε Productions
The ε productions (also called lambda or null productions) are rules that allow a variable to be replaced by nothing. They look like A → ε.
Example of ε Productions
Consider this grammar −
$$\mathrm{S \: \rightarrow\: ABCd}$$
$$\mathrm{A \: \rightarrow\: BC}$$
$$\mathrm{B \: \rightarrow\: bB \: | \: \epsilon}$$
$$\mathrm{C \: \rightarrow\: cC \: | \: \epsilon}$$
Here, both B and C have ε productions.
How to Remove ε Productions?
To remove ε productions:
- Find all "nullable" variables (variables that can derive ε).
- For each production, create new productions by optionally removing nullable variables.
- Remove the original ε productions.
After applying these steps, our grammar becomes −
$$\mathrm{S \: \rightarrow\: ABCd \: | \: ABd \: | \: ACd \: | \: BCd \: | \: Ad \: | \: Bd \: | \: Cd \: | \: d}$$
$$\mathrm{A \: \rightarrow\: BC \: | \: B \: | \: C}$$
$$\mathrm{B \: \rightarrow\: bB \: | \: b}$$
$$\mathrm{C \: \rightarrow\: cC \: | \: c}$$
Removing Unit Productions
Finally we have the question, what are Unit Productions? The unit productions are rules where a variable derives just another single variable, like A -> B.
Example of Unit Productions
Consider this grammar −
$$\mathrm{S \: \rightarrow\: Aa \: | \: B}$$
$$\mathrm{A \: \rightarrow\: b \: | \: B}$$
$$\mathrm{B \: \rightarrow\: A \: | \: a}$$
Here, S → B, A → B, and B → A are unit productions.
How to Remove Unit Productions
To remove the unit productions we need to follow the steps.
- Add all non-unit productions to the new grammar.
- For each variable A, find all variables B such that A* ⇒ B (A derives B in zero or more steps).
- For each such pair (A, B), add A → x for each non-unit production B → x in the original grammar.
After applying these steps, our grammar becomes −
$$\mathrm{S \: \rightarrow\: Aa \: | \: b \: | \: a}$$
$$\mathrm{A \: \rightarrow\: b \: | \: a}$$
From the overall process, when simplifying a CFG, it's important to follow these steps in order −
- Remove ε productions
- Remove unit productions
- Remove useless productions
Following this order ensures that we get the correct result.
Conclusion
In this chapter, we explained the process of simplifying context-free grammars. We covered the three types of redundant productions: useless productions, ε productions, and unit productions.
Simplifying CFGs is an important step in working with formal languages. It makes our grammars cleaner, more efficient, and ready for further transformations.