- What is an LR(1) parser?
- Why did you make this?
- How can I use the CLI in the picture?
- Can I use it as a standalone library?
- How it works?
- Can I have an LALR(1) parser instead of an LR(1) parser?
- Any benchmarks?
- Can I modify it?
- Which resources did you use when creating this?
- How is it licensed?
LR(1) parser is a type of bottom-up parser for parsing a subset of context free languages.
1 indicates that the parser will use a single lookahead token when making parsing decisions.
LR(1) parsers are powerful because they can parse a wide range of context free languages, including most programming languages!
To learn and to help others learn! This project allows you to visualize LR(1) parsers, from construction to parsing, which makes it easier to understand how they work.
If you want to play around with dotlr to visualize parser construction and step-by-step parsing of
different grammars, you can use the main executable of the crate.
You can install the dotlr cli from crates.io.
cargo install dotlrPaste the following into a file called grammar.lr:
P -> E
E -> E '+' T
E -> T
T -> %id '(' E ')'
T -> %id
%id -> /[A-Za-z][A-Za-z0-9]+/
Run dotlr cli with the grammar file and an input:
dotlr grammar.lr "foo(bar + baz)"It'll print:
+--------------------------------+
| Grammar |
+--------------------------------+
| P -> E |
| E -> E '+' T |
| E -> T |
| T -> %id '(' E ')' |
| T -> %id |
| |
| %id -> /^[A-Za-z][A-Za-z0-9]+/ |
+--------------------------------+
+--------+-----------+-----------------+
| Symbol | First Set | Follow Set |
+--------+-----------+-----------------+
| T | { %id } | { $, '+', ')' } |
+--------+-----------+-----------------+
| E | { %id } | { $, '+', ')' } |
+--------+-----------+-----------------+
| P | { %id } | { $ } |
+--------+-----------+-----------------+
+-------+------------------------+--------------+---------------+
| State | Items | Lookaheads | Transitions |
+-------+------------------------+--------------+---------------+
| 0 | P -> . E | { $ } | E -> 1 |
| | E -> . E '+' T | { $, '+' } | T -> 2 |
| | E -> . T | { $, '+' } | %id -> 3 |
| | T -> . %id '(' E ')' | { $, '+' } | |
| | T -> . %id | { $, '+' } | |
+-------+------------------------+--------------+---------------+
| 1 | P -> E . | { $ } | '+' -> 14 |
| | E -> E . '+' T | { $, '+' } | |
+-------+------------------------+--------------+---------------+
| 2 | E -> T . | { $, '+' } | |
+-------+------------------------+--------------+---------------+
| 3 | T -> %id . '(' E ')' | { $, '+' } | '(' -> 4 |
| | T -> %id . | { $, '+' } | |
+-------+------------------------+--------------+---------------+
| 4 | T -> %id '(' . E ')' | { $, '+' } | E -> 5 |
| | E -> . E '+' T | { ')', '+' } | %id -> 6 |
| | E -> . T | { ')', '+' } | T -> 9 |
| | T -> . %id '(' E ')' | { ')', '+' } | |
| | T -> . %id | { ')', '+' } | |
+-------+------------------------+--------------+---------------+
| 5 | T -> %id '(' E . ')' | { $, '+' } | '+' -> 11 |
| | E -> E . '+' T | { ')', '+' } | ')' -> 13 |
+-------+------------------------+--------------+---------------+
| 6 | T -> %id . '(' E ')' | { ')', '+' } | '(' -> 7 |
| | T -> %id . | { ')', '+' } | |
+-------+------------------------+--------------+---------------+
| 7 | T -> %id '(' . E ')' | { ')', '+' } | %id -> 6 |
| | E -> . E '+' T | { ')', '+' } | E -> 8 |
| | E -> . T | { ')', '+' } | T -> 9 |
| | T -> . %id '(' E ')' | { ')', '+' } | |
| | T -> . %id | { ')', '+' } | |
+-------+------------------------+--------------+---------------+
| 8 | T -> %id '(' E . ')' | { ')', '+' } | ')' -> 10 |
| | E -> E . '+' T | { ')', '+' } | '+' -> 11 |
+-------+------------------------+--------------+---------------+
| 9 | E -> T . | { ')', '+' } | |
+-------+------------------------+--------------+---------------+
| 10 | T -> %id '(' E ')' . | { ')', '+' } | |
+-------+------------------------+--------------+---------------+
| 11 | E -> E '+' . T | { ')', '+' } | %id -> 6 |
| | T -> . %id '(' E ')' | { ')', '+' } | T -> 12 |
| | T -> . %id | { ')', '+' } | |
+-------+------------------------+--------------+---------------+
| 12 | E -> E '+' T . | { ')', '+' } | |
+-------+------------------------+--------------+---------------+
| 13 | T -> %id '(' E ')' . | { $, '+' } | |
+-------+------------------------+--------------+---------------+
| 14 | E -> E '+' . T | { $, '+' } | %id -> 3 |
| | T -> . %id '(' E ')' | { $, '+' } | T -> 15 |
| | T -> . %id | { $, '+' } | |
+-------+------------------------+--------------+---------------+
| 15 | E -> E '+' T . | { $, '+' } | |
+-------+------------------------+--------------+---------------+
+-------+---------------------------------------+----------------------+
| | Action | Goto |
| State | ------------------------------------- | -------------------- |
| | '+' '(' ')' %id $ | P E T |
+-------+---------------------------------------+----------------------+
| 0 | - - - s3 - | - 1 2 |
+-------+---------------------------------------+----------------------+
| 1 | s14 - - - a1 | - - - |
+-------+---------------------------------------+----------------------+
| 2 | r3 - - - r3 | - - - |
+-------+---------------------------------------+----------------------+
| 3 | r5 s4 - - r5 | - - - |
+-------+---------------------------------------+----------------------+
| 4 | - - - s6 - | - 5 9 |
+-------+---------------------------------------+----------------------+
| 5 | s11 - s13 - - | - - - |
+-------+---------------------------------------+----------------------+
| 6 | r5 s7 r5 - - | - - - |
+-------+---------------------------------------+----------------------+
| 7 | - - - s6 - | - 8 9 |
+-------+---------------------------------------+----------------------+
| 8 | s11 - s10 - - | - - - |
+-------+---------------------------------------+----------------------+
| 9 | r3 - r3 - - | - - - |
+-------+---------------------------------------+----------------------+
| 10 | r4 - r4 - - | - - - |
+-------+---------------------------------------+----------------------+
| 11 | - - - s6 - | - - 12 |
+-------+---------------------------------------+----------------------+
| 12 | r2 - r2 - - | - - - |
+-------+---------------------------------------+----------------------+
| 13 | r4 - - - r4 | - - - |
+-------+---------------------------------------+----------------------+
| 14 | - - - s3 - | - - 15 |
+-------+---------------------------------------+----------------------+
| 15 | r2 - - - r2 | - - - |
+-------+---------------------------------------+----------------------+
> foo(bar + baz)
P
└─ E
└─ T
├─ foo
├─ (
├─ E
│ ├─ E
│ │ └─ T
│ │ └─ bar
│ ├─ +
│ └─ T
│ └─ baz
└─ )
+------+---------------+-------------------+---------------------------+-------------------------------+
| Step | State Stack | Symbol Stack | Remaining Input | Action Taken |
+------+---------------+-------------------+---------------------------+-------------------------------+
| 0 | 0 | | %id '(' %id '+' %id ')' $ | Shift 3 |
+------+---------------+-------------------+---------------------------+-------------------------------+
| 1 | 0 3 | %id | '(' %id '+' %id ')' $ | Shift 4 |
+------+---------------+-------------------+---------------------------+-------------------------------+
| 2 | 0 3 4 | %id '(' | %id '+' %id ')' $ | Shift 6 |
+------+---------------+-------------------+---------------------------+-------------------------------+
| 3 | 0 3 4 6 | %id '(' %id | '+' %id ')' $ | Reduce 4 (T -> %id) |
+------+---------------+-------------------+---------------------------+-------------------------------+
| 4 | 0 3 4 9 | %id '(' T | '+' %id ')' $ | Reduce 2 (E -> T) |
+------+---------------+-------------------+---------------------------+-------------------------------+
| 5 | 0 3 4 5 | %id '(' E | '+' %id ')' $ | Shift 11 |
+------+---------------+-------------------+---------------------------+-------------------------------+
| 6 | 0 3 4 5 11 | %id '(' E '+' | %id ')' $ | Shift 6 |
+------+---------------+-------------------+---------------------------+-------------------------------+
| 7 | 0 3 4 5 11 6 | %id '(' E '+' %id | ')' $ | Reduce 4 (T -> %id) |
+------+---------------+-------------------+---------------------------+-------------------------------+
| 8 | 0 3 4 5 11 12 | %id '(' E '+' T | ')' $ | Reduce 1 (E -> E '+' T) |
+------+---------------+-------------------+---------------------------+-------------------------------+
| 9 | 0 3 4 5 | %id '(' E | ')' $ | Shift 13 |
+------+---------------+-------------------+---------------------------+-------------------------------+
| 10 | 0 3 4 5 13 | %id '(' E ')' | $ | Reduce 3 (T -> %id '(' E ')') |
+------+---------------+-------------------+---------------------------+-------------------------------+
| 11 | 0 2 | T | $ | Reduce 2 (E -> T) |
+------+---------------+-------------------+---------------------------+-------------------------------+
| 12 | 0 1 | E | $ | Accept 0 (P -> E) |
+------+---------------+-------------------+---------------------------+-------------------------------+
You can also enter REPL mode if you omit the input:
dotlr grammar.lrYes, you can depend on the dotlr crate from crates.io.
Paste the following to your dependencies section of your Cargo.toml:
dotlr = { version = "0.1", default-features = false }Here is a basic example that shows the primary operations of the dotlr crate:
use dotlr::{
Grammar,
Parser,
ParserError,
};
const GRAMMAR: &str = r#"
P -> E
E -> E '+' T
E -> T
T -> %id '(' E ')'
T -> %id
%id -> /[A-Za-z][A-Za-z0-9]+/
"#;
const INPUT: &str = r#"
foo(bar + baz)
"#;
fn main() {
let grammar = match Grammar::parse(GRAMMAR.trim()) {
Ok(grammar) => grammar,
Err(error) => {
eprintln!("grammar error: {}", error);
return;
}
};
let parser = match Parser::lr(grammar) {
Ok(parser) => parser,
Err(error) => {
eprintln!("parser error: {}", error);
if let ParserError::Conflict { parser, .. } = error {
parser.dump();
}
return;
}
};
let tokens = match parser.tokenize(INPUT.trim()) {
Ok(tokens) => tokens,
Err(error) => {
eprintln!("tokenization error: {}", error);
return;
}
};
let (parse_trace, parse_tree) = match parser.trace(tokens) {
Ok(result) => result,
Err(error) => {
eprintln!("tokenization error: {}", error);
return;
}
};
parser.dump();
println!();
parse_tree.dump();
println!();
parse_trace.dump(parser.grammar());
}Let's go over a step-by-step construction of the parser for the following grammar:
E -> E '+' F
E -> F
F -> F '*' T
F -> T
T -> %b
%b -> /[0-1]/
And then do a step-by-step explanation of the parsing steps for the following input:
1 + 0 * 1
Few notes before starting:
$represents the end of input token- symbols that can expand to empty string are not supported in
dotlr, which simplifies the explanations below (i.e., no rules likeS ->)
First, we need to parse the grammar string to a grammar object that we can work with.
The grammar object will consist of:
-
symbols (HashSet):
- The set of symbols in the grammar
(e.g.,{ E, F, T })
- The set of symbols in the grammar
-
start_symbol (Symbol):
- The symbol to parse
(e.g.,E)
- The symbol to parse
-
constant_tokens (HashSet):
- The set of constant tokens in the grammar
(e.g.,{ '+', '*' })
- The set of constant tokens in the grammar
-
regular_expressions (HashMap<RegexToken, Regex>):
- The map of regular expression tokens to their corresponding compiled regular expressions
(e.g.,{ b -> /[0-1]/ })
- The map of regular expression tokens to their corresponding compiled regular expressions
-
rules (Vec):
- The list of rules in the grammar
(e.g.,[ E -> E '+' F, E -> F, ... ])
- The list of rules in the grammar
This is done in src/grammar.rs with a simple handwritten parser.
Now, we need to compute a set of tokens for each symbol in the grammar according to the following constraints:
- For each
token ∈ FIRST(Symbol), at least one of the following conditions must hold:Symbol -> token ... ∈ grammar.rulesSymbol -> AnotherSymbol ... ∈ grammar.rulesand
token ∈ FIRST(AnotherSymbol)
As for the implementation, here is a python-like pseudocode of the algorithm to compute FIRST sets:
# Start with FIRST(all_symbols) = {}
first_sets = {}
# Iterate until no more changes
while first_sets.has_changed():
# Iterate over the rules of the grammar
for rule in grammar:
# If pattern of the rule starts with a token
if rule.pattern[0].is_token:
# S -> '+' ... <==> S can start with '+'
# --------------------------------------
# Add the matching token to the FIRST set of the symbol of the rule
first_sets[rule.symbol].add(rule.pattern[0])
# If pattern of the rule starts with a symbol
elif rule.pattern[0].is_symbol:
# S -> E ... <==> S can start with anything E can start with
# ----------------------------------------------------------
# Add every token in the FIRST set of the matching symbol
# to the FIRST set of the symbol of the rule
first_sets[rule.symbol].extend(first_sets[rule.pattern[0]])This is done in src/tables.rs.
FIRST sets of the example grammar:
+--------+-----------+
| Symbol | First Set |
+--------+-----------+
| T | { %b } |
+--------+-----------+
| F | { %b } |
+--------+-----------+
| E | { %b } |
+--------+-----------+
Next, we need to compute another set of tokens for each symbol in the grammar according the following constraints:
- For each
token ∈ FOLLOW(Symbol), at least one of the following conditions must hold:-
Symbol == grammar.start_symboland
token == $ -
Anything -> ... Symbol token ... ∈ grammar.rules -
Anything -> ... Symbol AnotherSymbol ... ∈ grammar.rulesand
token ∈ FIRST(AnotherSymbol) -
Symbol -> ... AnotherSymbol ∈ grammar.rulesand
token ∈ FOLLOW(AnotherSymbol)
-
As for the implementation, here is a python-like pseudocode of the algorithm to compute FOLLOW sets:
# Start with just FOLLOW(grammar.start_symbol) = { $ }
follow_sets = { grammar.start_symbol: { $ } }
# Iterate until no more changes
while follow_sets.has_changed():
# Iterate over the rules of the grammar
for rule in grammar:
# Iterate over the 2-windows of the pattern of the rule
for i in range(len(rule.pattern) - 1):
# If the first atomic pattern is a symbol
if rule.pattern[i].is_symbol:
# And if the second atomic pattern is a token
if rule.pattern[i + 1].is_token:
# S -> ... E '+' ... <==> E can follow '+'
# ----------------------------------------
# Add the matching token to the FOLLOW set of the matching symbol
follow_sets[rule.pattern[i]].add(rule.pattern[i + 1])
# Or if the second atomic pattern is a symbol
elif rule.pattern[i + 1].is_symbol:
# S -> ... E F ... <==> E can follow anything F can start with
# ------------------------------------------------------------
# Add every token in the FIRST set of the second symbol
# to the FOLLOW set of the first symbol
follow_sets[rule.pattern[i]].extend(first_sets[rule.pattern[i + 1]])
# If pattern of ends with a symbol
if rule.pattern[-1].is_symbol:
# S -> ... E <==> S can follow anything E can follow
# --------------------------------------------------
# Add every token in the FOLLOW set of the matching symbol
# to the FOLLOW set of the symbol of the rule
follow_sets[rule.symbol].extend(follow_sets[rule.patten[-1]])This is done in src/tables.rs.
FOLLOW sets of the example grammar:
+--------+-----------------+
| Symbol | Follow Set |
+--------+-----------------+
| T | { $, '+', '*' } |
+--------+-----------------+
| F | { $, '+', '*' } |
+--------+-----------------+
| E | { $, '+' } |
+--------+-----------------+
It's time to construct the LR(1) automaton for the grammar.
Here is the drawing of the LR(1) automaton of a different grammar to get an intuition of what an LR(1) automaton is:
An automaton object is just of a list of states.
Each state has:
-
id (usize):
- The identifier of the state
(e.g.,0,1)
- The identifier of the state
-
items (Vec):
- The list of LR(1) items of the state
(e.g.,E -> E . '+' F | { $, '+' })
- The list of LR(1) items of the state
-
transitions (HashMap<AtomicPattern, usize>):
- The map of atomic patterns that would make transition to a new state
(e.g.,{ '+' -> 7 },{ %b -> 4, T -> 6 })
- The map of atomic patterns that would make transition to a new state
Each item has:
-
rule (Rule):
- Underlying rule of the item
(e.g.,E -> E '+' FinE -> E . '+' F | { $, '+' })
- Underlying rule of the item
-
dot (usize):
- Position of the dot in the rule
(e.g.,1inE -> E . '+' F | { $, '+' })
- Position of the dot in the rule
-
lookahead (HashSet):
- The set of tokens that could follow after the rule is applied.
Keep in mind that, one of the lookahead tokens MUST follow for the rule to be applied.
(e.g.,{ $, '+' }inE -> E . '+' F | { $, '+' })
- The set of tokens that could follow after the rule is applied.
Keep in mind that, one of the lookahead tokens MUST follow for the rule to be applied.
As for the implementation, here is a python-like pseudocode of the algorithm to construct the LR(1) automaton:
# Setup the kernel of the first state
first_state = next_empty_state()
for rule in grammar.rules:
if rule.symbol == grammar.start_symbol:
first_state.add_item(Item(rule, dot=0, lookahead={$}))
# Initialize construction state
states_to_process = [first_state]
processed_states = []
# Iterate until there aren't any more states to process.
while len(states_to_process) > 0:
# Get the state to process
state_to_process = states_to_process.pop()
# Computing closure of the state to process
# Loop until no more items are added
while True:
new_items = []
# Iterate current items to obtain new items
for item in state_to_process.items:
# If dot is not at the end of the pattern
if item.dot != len(item.rule.pattern):
# And if there is a symbol after dot
if item.rule.pattern[item.dot].is_symbol:
# Compute the lookahead for the new item
if item.dot == len(item.rule.pattern) - 1:
# S -> ... . E <==> Tokens in the current lookahead can follow E
# --------------------------------------------------------------
lookahead = item.lookahead
elif item.rule.pattern[item.dot + 1].is_token:
# S -> ... . E '+' <==> '+' can follow E
# --------------------------------------
lookahead = {item.rule.pattern[item.dot + 1]}
elif item.rule.pattern[item.dot + 1].is_symbol:
# S -> ... . E F <==> Tokens in FIRST(F) can follow E
# ---------------------------------------------------
lookahead = first_sets[item.rule.pattern[item.dot + 1]]
# Iterate over the rules of the grammar
for rule in grammar.rules:
# If the rule is for the symbol after dot
if rule.symbol == item.rule.pattern[item.dot]:
# Create a new item from the rule, with dot at the beginning
new_item = Item(rule, dot=0, lookahead=lookahead)
# If the item is not already in items of the state
if new_item not in state_to_process.items:
# Add it the set of new items
new_items.push(new_item)
# Process new items
for new_item in new_items:
# If a similar item with the same rule and the same dot but a different lookahead exists
if state_to_process.has_same_base_item(new_item):
# Merge lookaheads
state_to_process.merge_base_items(new_item)
# Otherwise
else:
# Add the new item directly
state_to_process.items.add(new_item)
# If state hasn't changed, break the loop
if not state_to_process.items.has_changed():
break
# Merge the states to process with an already existing state with the same closure.
replaced = False
for existing_state_with_same_items in processed_states:
if existing_state_with_same_items.items == state_to_process.items:
replaced = True
for state in processed_states:
# Replace transitions from existing states to point to the correct state.
state.transitions.replace_value(state_to_process, existing_state_with_same_items)
break
if replaced:
# If it's merged with an existing state, there is nothing else to do
continue
# Compute transitions of from the state to process.
for item in state_to_process.items:
# If dot is not at the end
if item.dot != len(item.rule.pattern):
# S -> ... . E ... <==> Seeing E would cause a transition to another state
# S -> ... . '+' ... <==> Seeing '+' would cause a transition to another state
# ----------------------------------------------------------------------------
atomic_pattern_after_dot = item.rule.pattern[item.dot]
# If state to transition is not created yet, create an empty state for it.
if atomic_pattern_after_dot is not in transitions:
# Create an empty state to transition to
state_to_process.transitions[atomic_pattern_after_dot] = next_empty_state()
# Setup the kernel of the state to transition
state_to_transition = state_to_process.transitions[atomic_pattern_after_dot]
state_to_transition.items.push(item.shift_dot_to_right())
# Add state to process to processed states, as we're done with it
processed_states.push(state_to_process)This is done in src/automaton.rs.
The LR(1) automaton of the example grammar:
+-------+------------------+-----------------+--------------+
| State | Items | Lookaheads | Transitions |
+-------+------------------+-----------------+--------------+
| 0 | E -> . E '+' F | { $, '+' } | E -> 1 |
| | E -> . F | { $, '+' } | F -> 2 |
| | F -> . F '*' T | { $, '+', '*' } | T -> 3 |
| | F -> . T | { $, '+', '*' } | %b -> 4 |
| | T -> . %b | { $, '+', '*' } | |
+-------+------------------+-----------------+--------------+
| 1 | E -> E . '+' F | { $, '+' } | '+' -> 7 |
+-------+------------------+-----------------+--------------+
| 2 | E -> F . | { $, '+' } | '*' -> 5 |
| | F -> F . '*' T | { $, '+', '*' } | |
+-------+------------------+-----------------+--------------+
| 3 | F -> T . | { $, '+', '*' } | |
+-------+------------------+-----------------+--------------+
| 4 | T -> %b . | { $, '+', '*' } | |
+-------+------------------+-----------------+--------------+
| 5 | F -> F '*' . T | { $, '+', '*' } | %b -> 4 |
| | T -> . %b | { $, '+', '*' } | T -> 6 |
+-------+------------------+-----------------+--------------+
| 6 | F -> F '*' T . | { $, '+', '*' } | |
+-------+------------------+-----------------+--------------+
| 7 | E -> E '+' . F | { $, '+' } | T -> 3 |
| | F -> . F '*' T | { $, '+', '*' } | %b -> 4 |
| | F -> . T | { $, '+', '*' } | F -> 8 |
| | T -> . %b | { $, '+', '*' } | |
+-------+------------------+-----------------+--------------+
| 8 | E -> E '+' F . | { $, '+' } | '*' -> 5 |
| | F -> F . '*' T | { $, '+', '*' } | |
+-------+------------------+-----------------+--------------+
Finally, we can compute ACTION and GOTO tables of the parser according the following constraints:
-
For each
action ∈ ACTION(state, token), at least one of the following conditions must hold:-
Anything -> ... . token ... | lookahead ∈ state.itemsand
action == Shift(state.transitions[token]) -
Anything -> ... . | lookahead ∈ state.itemsand
token ∈ lookaheadand
token == $and
item.rule.symbol == grammar.start_symboland
action == Accept(item.rule) -
Anything -> ... . | lookahead ∈ state.itemsand
token ∈ lookaheadand
(token != $oritem.rule.symbol != grammar.start_symbol) and
action == Reduce(item.rule)
-
-
For each
goto ∈ GOTO(state, Symbol), at least one of the following conditions must hold:Anything -> ... . Symbol ... | lookahead ∈ state.itemsand
goto == state.transitions[Symbol]
As for the implementation, here is a python-like pseudocode of the algorithm to construct ACTION and GOTO tables:
# Initialize empty action tables
action_table = {}
goto_table = {}
# For each state in the automaton
for state in automaton.states:
# Iterate over the items of the state
for item in state.items:
# If dot is at the end of the item
if item.dot == len(item.rule.pattern):
# S -> ... . <==> We can either reduce the rule or accept if S is a start symbol
# ------------------------------------------------------------------------------
# We can only perform actions for the tokens in the follow set of the symbol of the rule
for following_token in follow_sets[item.rule.symbol]:
# And only if the token is also in the lookahead of the item
if following_token in item.lookahead:
# Finally, if the token is $ and matching rule is a start symbol
if following_token == $ and item.rule.symbol == grammar.start_symbol:
# We should accept
action_table[state, following_token].push(Accept(item.rule))
# Otherwise
else:
# We should reduce the matching rule
action_table[state, following_token].push(Reduce(item.rule))
else:
# We get the last atomic pattern
atomic_pattern_after_dot = item.rule.pattern[item.dot]
# And the transition on the atomic pattern from the automaton
transition = state.transitions[atomic_pattern_after_dot]
if atomic_pattern_after_dot.is_token:
# S -> ... . '+' ... <==> We should shift and transition to another state
# if the dot precedes a token
# -------------------------------------------------------------------
action_table[state, atomic_pattern_after_dot].push(Shift(transition))
elif atomic_pattern_after_dot.is_symbol:
# S -> ... . E ... <==> We should update GOTO table if the dot precedes a symbol
# This can only happen after a reduction, and the parser
# would look to GOTO table to determine the next state
# --------------------------------------------------------------------------------
goto_table[state, atomic_pattern_after_dot] = transitionThis is done in src/tables.rs.
ACTION and GOTO tables of the example grammar:
+-------+-------------------------------+-------------------+
| | Action | Goto |
| State | ----------------------------- | ----------------- |
| | '+' '*' %b $ | E F T |
+-------+-------------------------------+-------------------+
| 0 | - - s4 - | 1 2 3 |
+-------+-------------------------------+-------------------+
| 1 | s7 - - - | - - - |
+-------+-------------------------------+-------------------+
| 2 | r2 s5 - a2 | - - - |
+-------+-------------------------------+-------------------+
| 3 | r4 r4 - r4 | - - - |
+-------+-------------------------------+-------------------+
| 4 | r5 r5 - r5 | - - - |
+-------+-------------------------------+-------------------+
| 5 | - - s4 - | - - 6 |
+-------+-------------------------------+-------------------+
| 6 | r3 r3 - r3 | - - - |
+-------+-------------------------------+-------------------+
| 7 | - - s4 - | - 8 3 |
+-------+-------------------------------+-------------------+
| 8 | r1 s5 - a1 | - - - |
+-------+-------------------------------+-------------------+
Tokenization algorithm in dotlr is the simplest tokenization algorithm thinkable.
Here is the idea in a python-like pseudocode:
# Initialize the result
tokens = []
# Loop until all of the input is consumed
remaining_input = input.trim();
while len(remaining_input) > 0:
# Try to match regular expression tokens
for (regex_token, regex) in grammar.regular_expressions:
if match := regex.start_matches(remaining_input):
# We have a match so add it to result
tokens.push(regex_token)
# And shrink remaining input
remaining_input = remaining_input[match.end:].trim()
break
# No regular expression tokens matched
else:
# So try to match constant tokens
for constant_token in grammar.constant_tokens:
if remaining_input.startswith(constant_token):
# We have a match so add it to result
tokens.push(constant_token)
# And shrink remaining input
remaining_input = remaining_input[len(constant_token):]
break
# No tokens matched
else:
raise TokenizationError
# Lastly, add the end of input token so the parser eventually accepts.
tokens.push($)Tokenized example input:
%b '+' %b '*' %b $
Finally, here is the parsing algorithm in a python-like pseudocode:
# Initialize the parsing state
state_stack = [ 0 ]
tree_stack = []
remaining_tokens.reverse()
# Get the first token
current_token = remaining_tokens.pop()
# Loop until algorithm either accepts or rejects
while True:
# Get the current state
current_state = state_stack[-1]
# Get the action to take from ACTION table
action_to_take = action_table[current_state, current_token]
# If the action is to shift
if action_to_take == Shift(next_state):
# Create a terminal tree for the current token and push it to the tree stack
tree_stack.push(TerminalNode(current_token));
# Pop the next token
current_token = remaining_tokens.pop()
# Transition to the next state according to ACTION table
state_stack.push(next_state);
# If the action is to reduce
elif action_to_take == Reduce(rule_index):
# Get the length of the pattern of the rule, say N
rule = grammar.rules[rule_index]
pattern_length = len(rule.pattern)
# Create a non-terminal tree with last N items in the tree stack
tree = NonTerminalNode(rule.symbol, tree_stack[-pattern_length:])
# Shrink state and tree stacks
tree_stack = tree_stack[:-pattern_length]
state_stack = state_stack[:-pattern_length]
# Push the new tree to the tree stack
tree_stack.push(tree)
# Transition to the next state according to GOTO table
state_stack.push(goto_table[state_stack[-1], rule.symbol])
# If the action is to accept
elif action_to_take == Accept(rule_index):
# Create a final non-terminal tree with everything in the tree stack and return it
return NonTerminalNode(grammar.start_symbol, tree_stack)
# No action can be taken, so input is not well-formed
else:
# So raise an error
raise ParsingErrorThe parsing steps for the example input:
+------+-------------+----------------+--------------------+-------------------------+
| Step | State Stack | Symbol Stack | Remaining Input | Action Taken |
+------+-------------+----------------+--------------------+-------------------------+
| 0 | 0 | | %b '+' %b '*' %b $ | Shift 4 |
+------+-------------+----------------+--------------------+-------------------------+
| 1 | 0 4 | %b | '+' %b '*' %b $ | Reduce 4 (T -> %b) |
+------+-------------+----------------+--------------------+-------------------------+
| 2 | 0 3 | T | '+' %b '*' %b $ | Reduce 3 (F -> T) |
+------+-------------+----------------+--------------------+-------------------------+
| 3 | 0 2 | F | '+' %b '*' %b $ | Reduce 1 (E -> F) |
+------+-------------+----------------+--------------------+-------------------------+
| 4 | 0 1 | E | '+' %b '*' %b $ | Shift 7 |
+------+-------------+----------------+--------------------+-------------------------+
| 5 | 0 1 7 | E '+' | %b '*' %b $ | Shift 4 |
+------+-------------+----------------+--------------------+-------------------------+
| 6 | 0 1 7 4 | E '+' %b | '*' %b $ | Reduce 4 (T -> %b) |
+------+-------------+----------------+--------------------+-------------------------+
| 7 | 0 1 7 3 | E '+' T | '*' %b $ | Reduce 3 (F -> T) |
+------+-------------+----------------+--------------------+-------------------------+
| 8 | 0 1 7 8 | E '+' F | '*' %b $ | Shift 5 |
+------+-------------+----------------+--------------------+-------------------------+
| 9 | 0 1 7 8 5 | E '+' F '*' | %b $ | Shift 4 |
+------+-------------+----------------+--------------------+-------------------------+
| 10 | 0 1 7 8 5 4 | E '+' F '*' %b | $ | Reduce 4 (T -> %b) |
+------+-------------+----------------+--------------------+-------------------------+
| 11 | 0 1 7 8 5 6 | E '+' F '*' T | $ | Reduce 2 (F -> F '*' T) |
+------+-------------+----------------+--------------------+-------------------------+
| 12 | 0 1 7 8 | E '+' F | $ | Accept 0 (E -> E '+' F) |
+------+-------------+----------------+--------------------+-------------------------+
And lastly, the parse tree of the example input:
E
├─ E
│ └─ F
│ └─ T
│ └─ 1
├─ +
└─ F
├─ F
│ └─ T
│ └─ 0
├─ *
└─ T
└─ 1
Yes, dotlr supports both LR(1) and LALR(1) parsers!
In the CLI, you can simply use the --lalr option:
dotlr --lalr grammar.lr "1 + 2 * 3"And in the API, you can use Parser::lalr instead of Parser::lr:
Parser::lalr(grammar)LALR(1) parser is construction is very similar to LR(1) parser construction. The only difference is that after 4) Constructing the LR(1) automaton, there is another step to reduce the LR(1) automaton to an LALR(1) automaton, using the following algorithm:
# Iterate over the state pairs of the automaton.
for state1 in automaton.states:
for state2 in automaton.states:
# Check if the states share the same core.
# Which means their items are the same ignoring the lookaheads.
# Here is an example:
# ...
# +-------+------------------------+--------------+---------------+
# | 3 | T -> %id . '(' E ')' | { $, '+' } | '(' -> 4 |
# | | T -> %id . | { $, '+' } | |
# +-------+------------------------+--------------+---------------+
# ...
# +-------+------------------------+--------------+---------------+
# | 6 | T -> %id . '(' E ')' | { ')', '+' } | '(' -> 7 |
# | | T -> %id . | { ')', '+' } | |
# +-------+------------------------+--------------+---------------+
# ...
if state1.core == state2.core:
# Merge the states.
# Which is combining lookaheads of the same items.
# Transitions should be mapped to the new states as well.
# Here is the merge of the two states in the example above:
# ...
# +-------+------------------------+-----------------+--------------+
# | 3 | T -> %id . '(' E ')' | { $, '+', ')' } | '(' -> 4 |
# | | T -> %id . | { $, '+', ')' } | |
# +-------+------------------------+-----------------+--------------+
# ...
automaton.merge_states(state1, state2)the actual implementation is a bit more involved, but the idea is exactly this.
Luckily, it's documented extensively at
automaton.rs
(search for to_lalr). I highly recommend reading the comments in the
source to understand the nuances of the implementation.
Yes, even though dotlr isn't a performance focused project, I thought it'd be interesting to have
a benchmark suite to see how changes affect its performance, so I've created a couple of JSON
grammars and benchmarked parsing them.
You can run the benchmarks with this command in the project directory:
cargo benchThis command prints the following in my own computer with an Intel i7-12700K CPU:
...
Parsing JSON/Simple LR(1)
time: [260.33 ms 265.74 ms 269.29 ms]
thrpt: [92.578 MiB/s 93.815 MiB/s 95.765 MiB/s]
...
Parsing JSON/Simple LALR(1)
time: [287.93 ms 288.71 ms 289.49 ms]
thrpt: [86.119 MiB/s 86.350 MiB/s 86.583 MiB/s]
...
Parsing JSON/Optimized LR(1)
time: [211.55 ms 211.71 ms 211.90 ms]
thrpt: [117.65 MiB/s 117.76 MiB/s 117.85 MiB/s]
...
Parsing JSON/Optimized LALR(1)
time: [192.66 ms 193.53 ms 194.39 ms]
thrpt: [128.25 MiB/s 128.82 MiB/s 129.40 MiB/s]
...
Furthermore, it generates an HTML report with detailed plots. You can find this
report at target/criterion/report/index.html, after running the command.
Performance isn't good for a JSON parser, but that's to be expected as it's not the primary objective. Feel free to create pull requests to improve parsing performance, hopefully without changing the understandability of the library.
Also keep in mind that these benchmarks are only for the parsing step. Tokenization is not the focus of this library, and frankly, its implementation is not the best.
Of course, feel free to fork dotlr from GitHub, clone the
fork to your machine, fire up your favourite IDE, and make any modification you want.
Don't forget to open up a pull request if you have useful changes that can be beneficial to everyone
using dotlr!
- https://www3.nd.edu/~dthain/compilerbook/chapter4.pdf
- https://soroushj.github.io/lr1-parser-vis/
- https://jsmachines.sourceforge.net/machines/lr1.html
dotlr is free, open source and permissively licensed!
All code in this repository is dual-licensed under either:
- MIT License (LICENSE-MIT or https://opensource.org/licenses/MIT)
- Apache License, Version 2.0 (LICENSE-APACHE or https://www.apache.org/licenses/LICENSE-2.0)
This means you can select the license you prefer!