The document provides an overview of SLR parsing, a bottom-up parsing technique used in compiler construction, highlighting its simplicity and efficiency compared to Canonical LR parsing, which handles more complex grammars. It discusses the roles of context-free grammars, finite automata, and parsing tables in the construction of parsers, as well as the advantages and limitations of SLR parsing. Additionally, it touches upon practical applications in compiler design and formal verification.

1. NADAR SARASWATHI COLLEGE
OF ARTS AND SCIENCE
By
P.JEYA SHRI NITHI
I M.Sc(CS)

2. Introduction to
SLR Parsing
SLR parsing is a bottom-up parsing
technique used in compiler construction
to analyze the syntax of a programming
language. It is a popular choice due to
its simplicity and efficiency.
JP

3. Context-Free Grafifiars
Context-free grammars (CFGs) are used to define the syntax of a
programming language. They specify the rules for constructing valid
sentences in the language. A CFG consists of a set of non-terminal
symbols, terminal symbols, a start symbol, and a set of production rules.
1 Non-terfiinal
Syfibols
Represent grammatical
categories or phrases,
such as "expression" or
"statement."
2 Terfiinal Syfibols
Represent the actual symbols
that appear in the input
string, such as keywords,
identifiers, and operators.
3 Production Rules
Describe how to derive a
string of terminal
symbols from the start
symbol.
fi Start Syfibol
Represents the root of the
parse tree and the starting
point for deriving
sentences.

4. Finite Autofiata and Parsing
Finite automata are mathematical models that describe a sequence of states and transitions. They play a crucial role in parsing
by recognizing valid sequences of input symbols.
1
Input String
The string of input tokens is processed one symbol at a
time.
2
State Transitions
The automaton transitions between states based on
the current input symbol.
3
Acceptance
If the automaton reaches a final state after processing
the entire input string, the input is recognized as valid.

5. Constructing SLR Parsing Tables
SLR parsing tables are constructed using the information obtained from the CFG and the corresponding finite automaton. The
table guides the parser through the process of recognizing and constructing a parse tree for the input string.
State Input Symbol Action
0 id Shift 1
1 + Reduce by A -> id
2 $ Accept

6. Canonical LR(1) Parsing
Canonical LR(1) parsing is a more powerful and general parsing technique compared to SLR. It uses a larger set of states and
transitions in the finite automaton, leading to more accurate and robust parsing.
SLR Parsing
Uses a single state for each non-terminal
symbol.
Simpler to implement but less
powerful.
Canonical LR(1) Parsing
Uses multiple states for each non-terminal
symbol.
More powerful but complex to
implement.

7. Differences between
SLR and Canonical LR
SLR and Canonical LR parsing differ in the way they handle conflicts during
parsing. SLR uses a simpler approach, which can lead to conflicts that
need to be resolved manually. Canonical LR, on the other hand, resolves
these conflicts automatically by utilizing a more comprehensive set of
states.
SLR
Simpler to
implement.
Canonical LR
Handles more complex
grammars.
SLR
Can lead to parsing
conflicts.
Canonical LR
More complex to
implement.

8. Advantages and
Lifiitations of SLR
Parsing
SLR parsing offers advantages in terms of simplicity and efficiency, making it
suitable for parsing grammars with relatively simple structures. However, it
has limitations when handling complex grammars with ambiguities or
conflicts.
1
Advantages
Easy to implement.
2
Lifiitations
Not suitable for all
grammars.
3
Applications
Used in various compilers and
interpreters.

9. Practical Considerations
and Applications
SLR parsing finds applications in various compiler construction scenarios. It
is particularly well-suited for parsing languages with simpler syntax and
fewer ambiguities. The choice between SLR and Canonical LR depends on
the specific requirements of the compiler.
Cofipiler Design
SLR parsing is used to analyze
and translate source code into
machine code.
Language
Processing
It is utilized in tools for
natural language
processing, such as parsers
and grammars.
Forfial Verification
SLR parsing is used to check the correctness and consistency of formal
specifications.

10. Introduction to
Canonical LR
Parsing
Canonical LR parsing is a powerful bottom-up parsing technique widely used
in compiler design. It's known for its efficiency and ability to handle a wide
range of programming language constructs. This presentation aims to
explore the fundamentals of canonical LR parsing, delving into its principles,
construction, and implementation.
JP

11. LR Parsing Automata
LR parsing automata are finite-state machines that efficiently recognize valid input strings based on the grammar
rules. They operate on a stack, reading the input one symbol at a time and maintaining a state to track the parsing
progress.
1
State
Represents the parsing context and the current position in the
grammar.
2 Stack
Stores the symbols that
have been successfully
parsed, providing the
current parsing context.
3
Input Buffer
Contains the remaining input symbols to be parsed.
4 Action Table
Specifies the parsing action
(shift, reduce, or accept) for
each state and input symbol.
5
Goto Table
Indicates the next state to transition to based on the current
state and the input symbol.

12. Constructing the LR(0) Automaton
The LR(0) automaton is the foundation for canonical LR parsing. It's constructed through a
systematic process of exploring all possible parsing states and their transitions based on the
grammar.
Start Symbol
The initial state is
determined by the
start symbol of the
grammar.
Closure Operation
Expands the states by
including all possible
production rule right-
hand sides (RHS) that
can be derived from
the left-hand side
(LHS) of the current
state.
Goto Function
Computes transitions
between states based
on the input symbol.

13. Canonical LR(1) Parsing
Tables
The LR(1) parsing tables are constructed from the LR(0) automaton by
incorporating lookahead symbols. The tables specify the parsing action (shift,
reduce, or accept) and the next state for each state and input symbol.
State Input Symbol Action
0 a shift, 1
1 b shift, 2
2 $ reduce, 1

14. Handling Shift-Reduce and
Reduce-Reduce Conflicts
Conflicts arise when multiple parsing actions are possible for a given state and input
symbol. Shift-reduce conflicts occur when both a shift and a reduce action are valid, while
reduce-reduce conflicts arise when multiple reduce actions are possible.
Shift-Reduce Conflicts
Occur when the parser can either shift the current input symbol or reduce the top
of the stack.
Reduce-Reduce Conflicts
Occur when the parser can reduce the top of the stack using multiple production
rules.
Conflict Resolution
The choice between conflicting actions can be resolved by using various
techniques, such as precedence rules, associativity rules, or operator-
precedence grammars.

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