Fact-checked by Grok 2 weeks ago

LL parser

An LL parser is a type of top-down parser in used for syntactic analysis of context-free grammars, which scans the input from left to right while constructing a leftmost and employs a fixed number k of lookahead to deterministically predict production expansions without . The notation LL(k) derives from the parser's left-to-right scan of the input, production of a leftmost , and use of k lookahead symbols, making it suitable for generating s or directly driving syntax-directed in compilers. This approach contrasts with bottom-up parsers like LR parsers, as it builds the parse tree from the start symbol downward, predicting nonterminal expansions based on current stack state and lookahead. The concept of (k) parsing was formally introduced in 1968 by Philip M. Lewis II and Richard E. Stearns in their seminal work on syntax-directed transduction, where they defined (k) grammars as those amenable to such predictive and explored their equivalence to certain classes of deterministic context-free languages. Building on early formal language theory from the and , including Backus-Naur Form notations, parsers became a cornerstone of by enabling efficient, automated syntax recognition for programming languages. Subsequent developments, such as grammar transformations to eliminate and factor left-common prefixes, made parsing practical for implementation via recursive descent or table-driven methods. The most commonly implemented variant is the LL(1) parser, which uses a single token of lookahead and relies on a predictive parsing table constructed from FIRST and FOLLOW sets to resolve nonterminal expansions unambiguously. For a grammar to be LL(1), the FIRST sets of alternative right-hand sides for each production must be disjoint, ensuring no parsing conflicts; if conflicts arise during table construction, the grammar requires rewriting. LL(1) parsers operate in linear time relative to input size, with low constant factors, and support straightforward integration of semantic actions for attribute evaluation during parsing. LL parsers excel in simplicity and speed for hand-coded recursive descent implementations, making them ideal for languages with well-structured, non-ambiguous grammars like Pascal or subsets of C, and they facilitate good error recovery through localized diagnostics. However, not all context-free grammars are LL(k) for any finite k, particularly those with inherent ambiguities, left recursion, or nondeterminism requiring more lookahead; in such cases, more powerful LR parsers are preferred. Despite these limitations, LL parsing remains influential in tools like ANTLR for generating efficient parsers and in educational contexts for illustrating top-down analysis principles.

Fundamentals

Definition and Characteristics

An LL parser is a type of top-down parser designed for context-free grammars, performing a left-to-right scan of the input string while constructing a leftmost in a predictive manner using a bounded number of lookahead to select the appropriate production rule. This approach ensures that parsing decisions are made deterministically without for grammars that meet the LL(k) criteria, where the parser expands non-terminals starting from the grammar's start symbol and proceeds downward through the . The formal notation LL(k) denotes the parser's behavior: the first "L" signifies the left-to-right direction of input scanning, the second "L" indicates the production of a leftmost derivation, and "k" represents the fixed number of lookahead tokens used to predict the next expansion, with LL(1) being the common case where k=1. Key characteristics of LL parsers include their top-down strategy, which builds the parse tree incrementally by predicting and applying productions based on the current non-terminal and lookahead; their determinism for LL(k)-compatible grammars, enabling unambiguous parsing paths; and their implementation flexibility, often via recursive descent procedures that correspond directly to grammar rules or via a parsing table indexed by non-terminals and lookahead symbols to guide expansions. The predictive mechanism avoids the need for trial-and-error in decision-making, making LL parsers particularly suitable for unambiguous context-free grammars without left recursion. LL parsers offer distinct advantages in simplicity and efficiency, as their recursive descent implementations naturally align with the hierarchical structure of the , facilitating straightforward and integration of semantic actions during . For input strings of length n, they achieve linear O(n), providing a balance of predictability and performance for languages where grammar ambiguities are resolved through lookahead.

Historical Development

The development of LL parsers emerged from early advancements in top-down syntax analysis during the , as designers sought efficient methods for processing context-free grammars. A foundational contribution was Edgar T. Irons's 1961 syntax-directed for , which employed predictive top-down techniques resembling recursive descent parsing to generate code directly from grammar rules. This approach, scanning input left-to-right while predicting derivations, influenced subsequent formalizations by emphasizing lookahead to resolve parsing choices without . The formal introduction of LL(k) parsers occurred in 1968, when Philip M. Lewis II and Richard E. Stearns defined LL(k) grammars as those parsable deterministically via top-down methods using k tokens of lookahead, in their paper "Syntax-Directed Transduction." This work built upon prior predictive parsing ideas, including those explored in implementations, and established the theoretical basis for LL parsers within formal language theory. Donald E. Knuth extended these concepts in his 1971 paper "Top-down syntax analysis," providing a detailed framework for predictive , including algorithms for lookahead sets and error handling. In the 1970s, LL parsing saw practical adoption in compiler construction, particularly through Niklaus Wirth's Pascal compiler (released around 1970), which utilized recursive descent parsing for its single-pass efficiency and ease of implementation on limited hardware. Bernard Lang contributed to the field's evolution in 1974 with his paper "Deterministic techniques for efficient non-deterministic parsers," which analyzed optimizations for parallel non-deterministic top-down parsers, paving the way for generalized LL variants capable of handling broader classes. During this decade, formalization advanced alongside integration into early parser tools, drawing inspiration from 1960s designs while addressing limitations in lookahead for deterministic . Milestones in LL parser adoption include its widespread use in Pascal compilers, where the method's simplicity supported educational and production systems. Modern applications trace to tools like , initiated by Terence Parr in as a predicated-LL(k) generator, which automated table construction and extended LL parsing for ambiguous grammars in diverse languages. ANTLR's development marked a shift from manual recursive procedures to generator-based workflows, influencing subsequent tools. The evolution of LL parsers transitioned from hand-crafted recursive descent in the to automated generators by the , reducing manual table construction and enabling scalability. Extensions to object-oriented paradigms emerged in this period, with ANTLR's Java-based implementations (from in 1997) supporting modular, reusable parser components in .

Prerequisite Concepts

Context-Free Grammars

A (CFG) is a for defining the syntax of a through a set of rules that generate strings from a start symbol. Formally, a CFG is a quadruple G = (V, \Sigma, P, S), where V is a of nonterminal symbols (variables), \Sigma is a of terminal symbols (the alphabet of the ), P is a of rules, and S \in V is the start symbol. This structure allows the grammar to specify hierarchical relationships in strings without dependencies on surrounding context, making CFGs foundational for syntax analysis in programming s and . The production rules in P take the form A \to \alpha, where A \in V is a nonterminal and \alpha \in (V \cup \Sigma)^* is a string of zero or more terminals and nonterminals (including the empty string ). These rules enable the replacement of nonterminals to build strings step by step. A in a CFG is a sequence of such replacements starting from the start symbol S, denoted by \Rightarrow, where \alpha \Rightarrow \beta means \beta can be obtained from \alpha by applying one production rule. The leftmost derivation specifically replaces the leftmost nonterminal at each step, which is central to approaches like LL parsers. The language generated by G, denoted L(G), is the set of all terminal strings derivable from S. In the of formal grammars, CFGs occupy Type-2, generating context-free languages that are recognized by nondeterministic pushdown automata. These languages capture recursive structures efficiently but may be ambiguous, meaning some strings admit multiple distinct leftmost , which complicates deterministic . A CFG is suitable for LL parsing if it is an LL(k)-grammar for some fixed k \geq 1, where the parser can uniquely predict the next production by examining at most k lookahead tokens from the input, ensuring a deterministic left-to-right scan that constructs the leftmost . The LL(k) notation emphasizes scanning the input left to right while producing the leftmost in top-down fashion.

FIRST and FOLLOW Sets

In the context of context-free grammars used for LL parsing, the FIRST set of a grammar symbol X (which may be a terminal, nonterminal, or string) is defined as the set of terminals that can appear as the first symbol in some string derived from X, formally \text{FIRST}(X) = \{ a \in \Sigma \mid X \Rightarrow^* a \beta \}, where \Sigma is the set of terminals, \Rightarrow^* denotes zero or more applications of productions, and \beta is any string; if X can derive the empty string \epsilon, then \epsilon is also included in \text{FIRST}(X). This set captures the possible starting terminals for expansions, essential for predicting which production to apply in top-down parsing. To handle empty derivations, nullability must first be determined for nonterminals. A nonterminal N is nullable if there exists a N \to \epsilon or if all symbols in the right-hand side of some for N are themselves nullable; this is computed iteratively by initializing nullable sets as empty, marking direct \epsilon-productions, and propagating through productions where all components are nullable until no changes occur. Nullability is crucial because it allows \epsilon to propagate in FIRST computations for strings that may derive the . The FIRST set is computed iteratively for all symbols in the . Begin by setting \text{FIRST}(t) = \{t\} for each t, and \text{FIRST}(N) = \{\epsilon\} if N is nullable. For each N \to Y_1 Y_2 \dots Y_k, where each Y_i is a symbol, add to \text{FIRST}(N) all non-\epsilon s from \text{FIRST}(Y_1); if \epsilon \in \text{FIRST}(Y_1), then include non-\epsilon s from \text{FIRST}(Y_2), and continue similarly for subsequent Y_i, skipping those with \epsilon in their FIRST; finally, if \epsilon is in \text{FIRST}(Y_i) for all i, add \epsilon to \text{FIRST}(N). Repeat this process over all productions until the sets stabilize, accounting for left-recursive chains by processing in dependency order or multiple passes. For a \alpha = X_1 X_2 \dots X_n, \text{FIRST}(\alpha) is computed similarly: include non-\epsilon from \text{FIRST}(X_1), then from \text{FIRST}(X_2) if \epsilon \in \text{FIRST}(X_1), and so on, adding \epsilon only if all X_i contribute \epsilon. The FOLLOW set for a nonterminal A consists of the terminals that can immediately follow A in any sentential form derived from the start symbol S, formally \text{FOLLOW}(A) = \{ b \in \Sigma \mid S \Rightarrow^* \alpha A b \beta \} for some strings \alpha, \beta; additionally, the end-of-input marker $ is included in \text{FOLLOW}(S). Unlike FIRST, FOLLOW sets do not include \epsilon and focus on what follows complete derivations of nonterminals. FOLLOW sets are also computed iteratively, starting with the for all nonterminals except adding $ to \text{FOLLOW}(S). For each production A \to \alpha B \beta, where B is a nonterminal and \beta is the remaining , add all non- terminals from \text{FIRST}(\beta) to \text{FOLLOW}(B); if \beta is empty or nullable (i.e., \beta \Rightarrow^* [\epsilon](/page/Epsilon)), then add all of \text{FOLLOW}(A) to \text{FOLLOW}(B). Process all productions in this manner, propagating updates until no further changes occur, ensuring that follow information flows from left to right in derivations. These sets are used briefly in constructing LL(1) tables to resolve production choices based on lookahead terminals.

Core Mechanics

LL(1) Parsing Algorithm

The LL(1) parsing algorithm is a table-driven, deterministic technique for context-free grammars that predicts productions using exactly one lookahead symbol from the input stream. It processes the input string from left to right, constructing a leftmost while maintaining a to represent the current parse . The algorithm assumes the grammar is LL(1), meaning the parsing has no conflicts, and it relies on a precomputed LL(1) parsing derived from the grammar's FIRST and FOLLOW sets. The input to the algorithm consists of a string w \in \Sigma^*, where \Sigma is the terminal alphabet, augmented with a special end-of-input marker (often denoted \ or EOF).[15] The parsing stack is initialized by pushing the end marker at the bottom, followed by the grammar's start symbol (possibly augmented with a new start symbol for convenience).[16] The output is either successful acceptance, confirming that w $ is a valid sentence in the grammar's language (potentially building a parse tree as a byproduct), or rejection due to a parsing error. The core procedure operates in a loop that continues until the stack is empty or the input is exhausted. At each step, the top of the stack is examined against the current lookahead symbol a from the input: if the top is a terminal, it must match a, in which case the terminal is popped from the stack and the input advances; if mismatched, parsing fails. If the top is a nonterminal A, the parsing table entry M[A, a] is consulted; if it specifies a production A \to \alpha, where \alpha is a string of grammar symbols, then A is popped, and the symbols of \alpha are pushed onto the stack in reverse order (rightmost symbol first) to ensure the leftmost symbol of \alpha becomes the new top. This right-to-left pushing simulates the left-to-right expansion needed for top-down parsing, with terminals matched immediately and nonterminals expanded predictively. The loop terminates with acceptance if both the stack and input reach their end markers simultaneously; otherwise, it rejects the input. Stack operations are central to the efficiency and determinism of the algorithm: pops occur on successful terminal matches, while expansions replace a single nonterminal with multiple symbols, growing the stack temporarily to reflect the derivation depth. The stack never holds more than O(n) symbols for an input of length n, as expansions correspond directly to the parse tree height. Error handling is straightforward and local: parsing rejects immediately if a terminal mismatch occurs or if the table entry M[A, a] is empty (indicating no predictable production), reporting the error at the current input position without backtracking. This design ensures linear-time parsing for valid inputs but provides only basic diagnostics, often requiring additional mechanisms in practical implementations for better recovery. The following pseudocode outlines the algorithm, using a stack \Gamma, input position i for string w with w_{n+1} = \ , and table M $:
create stack Γ and push $ onto Γ
push S' (augmented start symbol) onto Γ
i ← 1  // position in input w
while true do
    let A be the top symbol of Γ
    let a = w_i  // current lookahead
    if A = $ and a = $ then
        accept
        break
    if A is a terminal then
        if A = a then
            pop Γ
            i ← i + 1
        else
            error("mismatch at position i")
            break
    else  // A is nonterminal
        if M[A, a] is empty then
            error("no production for A with lookahead a at position i")
            break
        else
            let M[A, a] = A → X_1 X_2 … X_k
            pop Γ
            for j = k downto 1 do
                push X_j onto Γ
This implementation runs in O(n) time for inputs of length n, as each symbol is pushed and popped at most once.

Constructing LL(1) Parsing Tables

The LL(1) parsing table is a two-dimensional used to guide the selection of productions during , with rows indexed by non-terminals and columns by terminals including the end-of-input marker $. Each entry M[A, a] specifies a production A → α or indicates an if no production applies. To populate the table, consider each production A → α in the . For every a in the FIRST set of α, place the production A → α in M[A, a]. If α can derive the ε (i.e., ε ∈ FIRST(α)), then additionally place A → α in M[A, b] for every b in the FOLLOW set of A, including the end marker $ if it is in FOLLOW(A). The construction algorithm proceeds as follows: first compute the FIRST and FOLLOW sets for all non-terminals and right-hand sides using standard methods; then iterate over all productions and apply the entry rules above to fill the table without introducing multiple entries in any cell. If a cell receives more than one production, the grammar is not LL(1), as this indicates a parsing conflict. A is LL(1) if, for every non-terminal A with productions A → α_i and A → α_j (i ≠ j), the FIRST sets are disjoint: FIRST(α_i) ∩ FIRST(α_j) = ∅. Additionally, if any α_i derives ε, then FIRST(α_i) must be disjoint from FOLLOW(A), and more precisely, FIRST(α_j) ∩ FOLLOW(A) = ∅ for all j where α_j does not derive ε. These conditions ensure the table has at most one entry per cell, enabling unambiguous prediction with one lookahead symbol. For illustration, consider the for simple expressions:
  • → T E'
  • E' → + T E' | ε
  • T → ( ) |
Assuming FIRST(') = {+, ε} and FOLLOW(') = {$, )}, the relevant table entries for E' are M[E', +] = E' → + T E' and M[E', $] = E' → ε, along with M[E', )] = E' → ε. A partial table might appear as:
id(+)$
→ T ' → T '
E'E' → + T E'E' → εE' → ε
TT → T → ( )
This filling confirms the grammar is LL(1) with no conflicts.

Practical Examples

Setup of a Sample Grammar

To illustrate the concepts of LL parsing, a simple for arithmetic expressions is commonly employed, featuring and with operator precedence. This , originally presented in foundational compiler design literature, is defined by the following productions:
E → T | E + T
T → F | T * F
F → id | ( E )
Here, E represents an expression, T a term, and F a factor, capturing the hierarchy where multiplication binds tighter than addition. The non-terminals in this grammar are E, T, and F, while the terminals consist of the operators + and *, the identifier id, the parentheses *( * and * ) *, and the end-of-input marker $. No non-terminal is nullable, as the productions contain no ε-rules, ensuring every derivation yields a non-empty string. An initial examination reveals immediate left recursion in the productions for E and T, which must be eliminated for LL(1) applicability. Nonetheless, potential predictive conflicts due to overlapping FIRST sets of alternatives may arise after transformation, necessitating computation of FIRST and FOLLOW sets for resolution. For parsing demonstration, the input string id + id * id serves as a representative example, tokenized into the sequence id + id * id $ to simulate a complete expression.

Step-by-Step Parsing Procedure

To demonstrate the LL(1) parsing procedure, consider the sample arithmetic expression grammar from the previous section, which has been transformed to be LL(1)-compatible by eliminating . For simplicity in this example, we omit parentheses and treat all factors as identifiers (id), focusing on operator precedence; subtraction and division are also excluded. The grammar productions are numbered as follows:
  1. E → T E'
  2. E' → + T E'
  3. E' → ε
  4. T → F T'
  5. T' → * F T'
  6. T' → ε
  7. F → id
Here, id represents identifiers (or numbers) as terminals for simplicity (analogous to factors in more general cases). The endmarker is '' (equivalent to 'eof'). The relevant portions of the FIRST and FOLLOW sets used to construct the parsing table are: FIRST(E) = FIRST(T) = FIRST(F) = {id}; FIRST(E') = {+, ε}; FIRST(T') = {*, ε}; FOLLOW(E) = FOLLOW(E') = {}; FOLLOW(T) = FOLLOW(T') = {+, }; FOLLOW(F) = {*, +, }. The LL(1) parsing table M is constructed by placing production number p in M[A, a] if a ∈ FIRST+(A → α), where FIRST+ includes FOLLOW(A) for ε-productions. The table entries for the key terminals (+, *, id, $ ) are:
Nonterminal+*id$
E1
E'23
T4
T'656
F7
(Blank cells indicate no production, avoiding conflicts.) The parsing process uses a stack initialized with the endmarker at the bottom and the start symbol E on top, and an input buffer with the string "id + id * id". The algorithm repeatedly examines the top stack symbol A and the lookahead terminal a: if A is a terminal, match and pop it while advancing input if it equals a; if A is a nonterminal, select the unique production from M[A, a], pop A, and push the production's right-hand side symbols in reverse order (rightmost first); if ε-production, simply pop A. Parsing succeeds if the stack and input empty simultaneously at $. Step-by-step trace for input "id + id * id $":
  1. Stack: [$ E], Input: id + id * id $, Lookahead: id
    M[E, id] = 1 (E → T E'), pop E, push E' T → Stack: [$ E' T]
  2. Stack: [$ E' T], Input: id + id * id $, Lookahead: id
    M[T, id] = 4 (T → F T'), pop T, push T' F → Stack: [$ E' T' F]
  3. Stack: [$ E' T' F], Input: id + id * id $, Lookahead: id
    M[F, id] = 7 (F → id), pop F, push id → Stack: [$ E' T' id]
  4. Stack: [$ E' T' id], Input: id + id * id , Lookahead: id Match id, pop id, advance input → Stack: [$ E' T'], Input: + id * id
  5. Stack: [$ E' T'], Input: + id * id $, Lookahead: +
    M[T', +] = 6 (ε), pop T' → Stack: [$ E']
  6. Stack: [$ E'], Input: + id * id $, Lookahead: +
    M[E', +] = 2 (E' → + T E'), pop E', push E' T + → Stack: [$ E' T +]
  7. Stack: [$ E' T +], Input: + id * id , Lookahead: + Match +, pop +, advance input → Stack: [$ E' T], Input: id * id
  8. Stack: [$ E' T], Input: id * id $, Lookahead: id
    M[T, id] = 4 (T → F T'), pop T, push T' F → Stack: [$ E' T' F]
  9. Stack: [$ E' T' F], Input: id * id $, Lookahead: id
    M[F, id] = 7 (F → id), pop F, push id → Stack: [$ E' T' id]
  10. Stack: [$ E' T' id], Input: id * id , Lookahead: id Match id, pop id, advance input → Stack: [$ E' T'], Input: * id
  11. Stack: [$ E' T'], Input: * id $, Lookahead: *
    M[T', *] = 5 (T' → * F T'), pop T', push T' F * → Stack: [$ E' T' F *]
  12. Stack: [$ E' T' F *], Input: * id , Lookahead: * Match *, pop *, advance input → Stack: [$ E' T' F], Input: id
  13. Stack: [$ E' T' F], Input: id $, Lookahead: id
    M[F, id] = 7 (F → id), pop F, push id → Stack: [$ E' T' id]
  14. Stack: [$ E' T' id], Input: id , Lookahead: id Match id, pop id, advance input → Stack: [$ E' T'], Input:
  15. Stack: [$ E' T'], Input: , Lookahead:
    M[T', ] = 6 (ε), pop T' → Stack: [ E']
  16. Stack: [$ E'], Input: , Lookahead:
    M[E', ] = 3 (ε), pop E' → Stack: []
  17. Stack: [$], Input: , Lookahead:
    Match , pop → Stack: [], Input: empty. Accept.
Key decisions in the rely on the lookahead to select productions unambiguously. For instance, after the first 'id' as F → id and reducing to E via T and ε-productions, the lookahead '+' selects E' → + T E' from M[E', +], expanding to incorporate the ; similarly, after the second 'id', the lookahead '*' selects T' → * F T' from M[T', *], enforcing precedence without . The procedure produces the following leftmost derivation, reflecting the parse tree structure where E is the root, with left-associative additions and right-recursive multiplications ensuring operator precedence (* over +): E ⇒ T E'
⇒ F T' E'
⇒ id T' E'
⇒ id ε E'
⇒ id E'
⇒ id + T E'
⇒ id + F T' E'
⇒ id + id T' E'
⇒ id + id * F T' E'
⇒ id + id * id T' E'
⇒ id + id * id ε E'
⇒ id + id * id E'
⇒ id + id * id ε
This derivation corresponds to the :
       E
      / \
     T  E'
    /|   \
   F T'  + T E'
    |    /|   \
   id  ε F T' ε
        |  /| 
        id * F T'
           |  / \
           id ε  ε
The tree groups "id * id" under T before adding to the initial "id", capturing the expression (id + (id * id)).

Implementation in Pseudocode

An parser relies on key components including a table represented as a two-dimensional array M, where rows correspond to non-terminals and columns to lookahead terminals (including the end-of-input marker \ ), with entries specifying production rules or [ \epsilon $](/page/Epsilon) for nullable cases; a implemented as a list to manage the process; and an input buffer maintaining the token stream with a current position pointer. These elements enable predictive without for LL(1) grammars. The following pseudocode outlines the non-recursive LL(1) parsing procedure, assuming a grammar G with start symbol S, input string tokenized as w = a_1 a_2 \dots a_n \ , and precomputed parsing table M $. The algorithm simulates leftmost derivations by expanding non-terminals based on table lookups and matching terminals against the input. Error handling is triggered on mismatches or undefined table entries.
procedure parse(w, M, G):
    // Initialize stack: bottom marker $, then start symbol
    stack = [$]  // $ is end-of-input marker
    push(stack, S)  // S is the start non-terminal
    
    // Initialize input position
    i = 1  // Points to first token in w
    
    while stack is not empty and i <= length(w):
        X = top(stack)
        a = w[i]  // Current lookahead token
        
        if X is a terminal:
            if X == a:
                pop(stack)
                i = i + 1
            else:
                error("Terminal mismatch: expected " + X + ", found " + a)
        else:  // X is a non-terminal
            if M[X, a] is defined as production X → Y₁ Y₂ … Yₖ (k ≥ 0):
                pop(stack)
                // Handle ε-production (k=0): no push needed
                if k > 0:
                    // Push in reverse order for left-to-right expansion
                    for j = k downto 1:
                        push(stack, Yⱼ)
            elif M[X, a] = ε:  // Nullable case
                pop(stack)
            else:
                error("No production for " + X + " with lookahead " + a)
    
    // Successful parse if stack empty and input consumed
    if stack is empty and i > length(w):
        return success
    else:
        error("Parse failed: incomplete input or leftover stack")
Table integration occurs via the lookup M[\text{top}(stack), \text{lookahead}], which selects the unique production to avoid conflicts in LL(1) grammars; an undefined entry signals a parsing error. To build an (AST), the parser attaches nodes during non-terminal expansions: upon selecting a production X \to Y_1 \dots Y_k, create an AST node for X and designate the subtrees rooted at Y_1, \dots, Y_k as its children, with terminals contributing nodes during matches. This semantic action can be embedded in the pseudocode's expansion step, often using a secondary semantic to construct and link nodes post-pop.

Advanced Variants

LL(k) Parsers for k > 1

LL(k) parsers extend the LL(1) approach by incorporating k tokens of lookahead to predict the correct production for a nonterminal, where k is a fixed positive greater than 1. Formally introduced by Philip M. Lewis II and Richard E. Stearns in 1968, an LL(k) parser processes the input from left to right, constructs a leftmost , and uses the current nonterminal along with the subsequent k input symbols (the lookahead ) to deterministically select the next production. A is LL(k) if, for every nonterminal, the right-hand sides of its productions can be uniquely distinguished by their FIRST_k sets, ensuring no conflicts in the parsing table entries indexed by k-tuples from the input alphabet. Such parsers are necessary for grammars that exhibit predictability only with more than one of lookahead, particularly when multiple productions for a nonterminal share a common initial sequence of terminals or nonterminals that require additional context to disambiguate. For instance, consider a with productions S → A a | B b, A → a, B → a; this generates the language consisting of the strings "aa" and "ab". The FIRST sets for the productions of S both contain {a}, leading to a conflict in an LL(1) parser since the choice cannot be made with a single lookahead . However, with k=2, the lookahead tuples "aa" and "ab" are disjoint, allowing unique selection of the appropriate production and confirming the is LL(2). Constructing LL(k) parsers faces significant challenges due to the exponential growth in the size of the parsing table, which has rows for nonterminals and columns corresponding to all possible k-tuples over the terminal Σ, resulting in up to |nonterminals| × |Σ|^k entries. This complexity makes implementation impractical for large k or alphabets, as the table construction time and space requirements grow exponentially. In practice, LL(k) parsers with k > 2 are rarely used, as most programming language grammars can be transformed to LL(1) or handled with k=2, and higher k leads to inefficient parsers without substantial benefits.

Generalized Table Construction

The construction of parsing tables for LL(k) parsers, where k > 1, generalizes the approach used for LL(1) by incorporating lookahead strings of length k rather than single symbols. In this framework, the table M is indexed by nonterminals A on the rows and possible k-tuples of terminal symbols w on the columns. For each A → α in the , an entry M[A, w] = A → α is added for every w belonging to FIRST_k(α), the set of all terminal strings of length exactly k that can be derived as the first k symbols from α. If α can derive a string of fewer than k symbols (including the ), then the relevant prefixes are extended by unioning with elements from FOLLOW_k(A), the set of k-length terminal strings that can follow A in any . This ensures that the parser can unambiguously select the correct based on the next k input symbols. The algorithm for populating the table proceeds systematically across all productions. For a given nonterminal A with alternatives A → α_1 | ... | A → α_m, compute FIRST_k(α_i) for each i, and if any α_i is nullable (derives ε), include FOLLOW_k(A) in the lookahead set for that production. Entries are placed without overlap to avoid shift-reduce or reduce-reduce conflicts; if overlaps occur, the grammar is not LL(k). This process builds a deterministic table that guides the top-down parser in expanding nonterminals based on the lookahead tuple. The resulting table enables the parser to perform leftmost derivations while scanning the input left-to-right. Computing FIRST_k and FOLLOW_k sets extends the standard FIRST and FOLLOW computations to handle k-tuples through iterative traversal of the grammar's productions. Start by initializing FIRST_k(X) as empty for nonterminals X and containing all k-tuples of terminals for terminals themselves. Then, repeatedly apply rules: for a X → Y_1 ... Y_n, add to FIRST_k(X) all k-prefixes derivable from the initial segments of Y_1 ... Y_n, propagating through nullable symbols until fixed points are reached. Similarly, FOLLOW_k(A) is computed by examining contexts where A appears on the right-hand side, appending k-lookahead from subsequent symbols or the end-of-input marker. This iteration, akin to dynamic programming over trees, converges for context-free grammars but has complexity exponential in k due to the size of the tuple sets. A grammar satisfies the LL(k) condition if, for every nonterminal A, the lookahead sets FIRST_k(α_i) ∪ (FOLLOW_k(A) if α_i nullable) are pairwise disjoint across all alternatives α_i of A. This disjointness guarantees a unique table entry for each possible k-tuple, ensuring deterministic without . Violations indicate nondeterminism, requiring grammar transformations or increased k. Seminal theoretical work establishes that every LL(k) grammar admits such a table, with the construction yielding a parser that recognizes the in linear time relative to input length. In practice, manual construction of LL(k) tables is feasible only for small k (typically k ≤ 2) and simple grammars, as the exponential growth in lookahead set sizes quickly becomes unwieldy. Automated tools, such as parser generators implementing algorithms based on the foundational work, handle the computation for moderately complex grammars by representing k-tuples efficiently via tries or hashing, enabling LL(k) parsing in production compilers where k is bounded. These tools often incorporate optimizations to prune unreachable tuples during iteration, making the process viable for real-world use.

Grammar Transformations

Resolving Left Recursion

Left recursion in a occurs when a nonterminal can derive a sentential form beginning with itself, preventing top-down parsers like parsers from terminating due to infinite recursive calls during leftmost derivations. There are two main types: immediate left recursion, where a directly starts with the nonterminal (e.g., A → A α), and indirect left recursion, where the nonterminal leads to another that eventually cycles back (e.g., via a chain A → B γ and B → A δ). Resolving is essential for parsers, as it transforms the grammar into an equivalent right-recursive form that supports finite leftmost derivations without loops. For immediate left recursion, the standard algorithm eliminates it by introducing a new nonterminal A'. Given productions of the form A → A α_1 | ⋯ | A α_m | β_1 | ⋯ | β_n (where none of the β_i begin with A), replace them with A → β_1 A' | ⋯ | β_n A' and A' → α_1 A' | ⋯ | α_m A' | ε. This substitution shifts the recursion to the right, ensuring progress in by consuming input before recursing. A classic example is the arithmetic expression grammar with immediate left recursion: E → E + T | T. Applying the algorithm yields E → T E' and E' → + T E' | ε, where E' handles the additive tail recursively from the right. This transformed generates the same language of expressions but allows an LL parser to process terms first and then additives without infinite descent. Indirect left recursion requires a more general procedure to first convert it to immediate form before applying the above. Order the nonterminals as A_1, ..., A_n such that substitutions propagate forward. For each A_i, replace any production A_i → A_j γ (with j < i) by substituting the current productions of A_j into it, yielding A_i → δ_1 γ | ⋯ | δ_k γ (where A_j → δ_1 | ⋯ | δ_k). Then, eliminate any resulting immediate on A_i using the direct method. This iterative substitution breaks cycles by expanding earlier nonterminals, assuming no ε-productions or cycles among nonterminals. The transformation preserves the language generated by the original grammar, as every leftmost derivation in the recursive form corresponds to a unique right-recursive derivation in the transformed grammar, and vice versa, maintaining equivalence without altering the parse trees' yields. It enables leftmost derivations to proceed by always expanding non-left-recursive alternatives first, ensuring termination in top-down parsing. However, resolving left recursion increases the grammar's size by adding new nonterminals and productions, potentially exponentially in the case of complex indirect recursion depending on nonterminal ordering. Moreover, while the language remains the same, the transformed grammar does not always retain LL(k) status for the same k, as substitutions may introduce new lookahead dependencies or nondeterminism requiring higher k or further adjustments. By eliminating left recursion, LL parsers avoid non-termination conflicts that mimic shift-reduce issues in top-down table construction.

Applying Left Factoring

Left factoring is a grammar transformation technique applied to context-free grammars to eliminate common prefixes in the right-hand sides of productions for a non-terminal, thereby resolving nondeterminism in top-down parsers such as LL(1). This issue arises when multiple productions for a non-terminal A share an initial sequence α, as in Aα β | α γ, causing the FIRST sets of the alternatives to overlap and preventing unique prediction of the production based on a single lookahead token. The algorithm for left factoring proceeds as follows: for a non-terminal A with productions sharing a common prefix α, introduce a new non-terminal A' and rewrite the productions as Aα A', with A'β | γ (and additional alternatives if present). If the remaining suffixes β and γ themselves share a common prefix, the process is applied recursively to A'. This transformation is typically performed after eliminating left recursion to ensure the grammar is suitable for LL(1) parsing table construction. Consider a grammar fragment for statements with conditional constructs:
S → if stmt | if expr then stmt
Here, both productions share the prefix "if", leading to overlapping FIRST sets. Applying left factoring yields:
S → if A
A → stmt | expr then stmt
This separates the common prefix, allowing the parser to match "if" unambiguously before deciding on the suffix via A. For cases with longer common prefixes across multiple levels, the algorithm extends naturally by factoring the longest shared sequence first and recursing on the new non-terminal if needed; for instance, productions sharing "if expr then" would factor that entire prefix before handling remaining alternatives. The resulting grammar generates the same language as the original, preserving semantic equivalence while enabling deterministic prediction in without increasing lookahead requirements. This technique is integral to verifying LL(1) compatibility during grammar analysis.

Substitution Techniques

Substitution techniques in the context of LL parsing refer to the process of inlining simple non-terminals, particularly through the elimination of unit productions of the form A \to B, where both A and B are non-terminals, to reduce the hierarchical layers of the grammar and facilitate unambiguous top-down parsing. The standard algorithm for this elimination involves an iterative substitution: for each unit production A \to B, replace it by adding all non-unit productions of B (i.e., B \to \alpha where \alpha is not a single non-terminal) directly to A, and remove the original unit production; this process repeats until no unit productions remain, with ε-productions addressed beforehand to prevent the introduction of unintended nullable derivations that could complicate FIRST set computations. For instance, given productions A \to B and B \to c \mid d (where c and d are terminals), substitution replaces A \to B by adding A \to c \mid A \to d, then removes the unit production A \to B, yielding A \to c \mid d. By flattening the grammar structure, this technique simplifies the derivation tree, potentially exposing factorable prefixes in productions or uncovering hidden forms of recursion that might otherwise lead to parsing conflicts in LL(1) table construction. Despite these advantages, substitution can significantly bloat the grammar by duplicating productions across multiple levels, especially in cases of long unit chains, and it alone may not suffice to eliminate all ambiguities without supplementary methods.

Conflicts and Limitations

Types of Parsing Conflicts

In LL(1) parsing, conflicts arise when the parsing table contains multiple production rules for a given nonterminal A and lookahead terminal a, denoted as multiple entries in M[A, a], leading to choice ambiguity where the parser cannot uniquely determine the correct production to apply. These conflicts indicate that the grammar is not LL(1), as the single lookahead token fails to disambiguate alternatives. The primary types of LL(1) conflicts are FIRST/FIRST and FIRST/FOLLOW conflicts, both stemming from overlaps in the FIRST and FOLLOW sets computed for the grammar. A FIRST/FIRST conflict occurs when two or more alternative productions for a nonterminal A have overlapping FIRST sets, meaning there exists a terminal a in both \mathrm{FIRST}(\alpha) and \mathrm{FIRST}(\beta) for productions A \to \alpha and A \to \beta, causing multiple rules to be eligible for the same lookahead a. For example, in a grammar with E \to E + E \mid \mathrm{ID}, the FIRST sets overlap on \mathrm{ID}, resulting in ambiguity for input starting with an identifier. A FIRST/FOLLOW conflict arises in the presence of epsilon-productions (\epsilon-productions), where a nonterminal A is nullable (i.e., A \Rightarrow^* \epsilon) and the FOLLOW set of A overlaps with the FIRST set of another alternative production for A. Specifically, if a \in \mathrm{FOLLOW}(A) and a \in \mathrm{FIRST}(\alpha) for A \to \alpha (with A \to \epsilon as an alternative), the parser cannot decide whether to apply the epsilon-production or expand \alpha upon seeing a. An illustrative case is a grammar like E \to F * E \mid F where F is nullable, leading to overlap between \mathrm{FIRST}(F * E) and \mathrm{FOLLOW}(E). Detection of these conflicts occurs during the construction of the LL(1) parsing table, after computing the FIRST and FOLLOW sets via fixed-point iteration on the grammar productions. For each production A \to X_1 \dots X_n, entries are added to M[A, t] for t \in \mathrm{FIRST}(X_1 \dots X_n); if the right-hand side is nullable, additional entries are placed for t \in \mathrm{FOLLOW}(A). Any table cell M[A, a] with more than one production flags a conflict, confirming the grammar's non-LL(1) status. For broader LL(k) parsers with k > 1, conflicts generalize to overlaps in k-s within the PREDICT sets, where the lookahead consists of sequences of k tokens rather than single terminals. These tuple overlaps in generalized parsing tables occur when the FIRST_k sets of alternative productions are not disjoint, such as when multiple productions share common k-token prefixes, preventing unique prediction based on the k-lookahead. Detection involves checking for intersecting k-tuples during table construction, often using FIRST_k trees or set comparisons to identify ambiguities that require greater lookahead or adjustments.

Strategies Beyond Basic Transformations

When basic transformations such as elimination and left factoring fail to resolve conflicts in an , augmenting the grammar with error productions offers a for improving error recovery during . Error productions are additional rules that explicitly generate common erroneous constructs, allowing the parser to detect and handle syntax errors more gracefully without halting the entire process. For instance, if a grammar expects an identifier but encounters an unexpected keyword, an error production can synchronize the parser by skipping the invalid and continuing with the next viable input. This approach, originally proposed for syntactic error correction, enables parsers to provide meaningful diagnostics and recover at the phrase level by filling blank entries in the LL parsing table with error-handling routines. Grammar partitioning provides another advanced technique for managing persistent conflicts by decomposing a non-(1) grammar into modular subgrammars, each of which is (1) and handles specific contexts or sublanguages. This modularization allows independent parsing of grammar subsets, reducing conflicts arising from interdependent rules while preserving determinism in . Federal LL(1) parsers constructed from partitioned grammars maintain the full generality of monolithic LL(1) parsers, enabling better handling of complex languages through reusable modules without sacrificing efficiency. In practice, this can result in parsers with fewer states compared to non-partitioned versions, though the primary benefit lies in for large grammars. For grammars that remain ambiguous despite transformations, introducing limited into recursive descent parsers can resolve prediction issues, though this deviates from pure LL determinism. allows the parser to tentatively expand a non-terminal, consume input, and retreat if the path leads to a , effectively handling non-determinism with bounded retries. This , while risking time in worst cases, is suitable for grammars with rare ambiguities and can be optimized through techniques like those in packrat parsing, which ensure linear time by caching subparse results. Packrat parsers convert recursive descent implementations into efficient, functional forms without altering the . Parser generators such as ANTLR employ adaptive lookahead strategies like ALL() to automatically manage conflicts beyond fixed k-lookahead limits, making them practical for real-world grammars. ALL() dynamically analyzes the grammar during prediction to compute necessary lookahead sets, using decision DFAs that adapt to context and resolve ambiguities without manual intervention. This approach combines the simplicity of LL parsing with unbounded lookahead, supporting LL(*) capabilities that handle most programming language grammars efficiently, often outperforming traditional LL(k) in both speed and coverage. By generating optimized code from the grammar, tools like ANTLR minimize the need for extensive transformations. If these strategies still yield unresolved conflicts or unacceptable performance, it may be necessary to abandon strict parsing in favor of rewriting the or adopting a bottom-up LR approach. LR parsers accommodate a broader class of grammars, including those with and certain ambiguities that resist LL transformations, often requiring no grammar modifications. Historical comparisons show that while LL offers easier manual implementation, LR provides superior generality for complex languages like , with parsing tables that resolve more conflicts automatically. Switching to LR, via tools like or , is advisable when LL limitations hinder development, as it ensures deterministic for nearly all practical context-free grammars.

Comparisons with Bottom-Up Parsers

LL parsers and bottom-up parsers, such as LR parsers, differ fundamentally in their approach to syntax analysis. LL parsers employ a top-down strategy, beginning from the start symbol of the and recursively expanding non-terminals to match the input from left to right, producing a leftmost . In contrast, LR parsers use a bottom-up method, starting from the input tokens and building the upward by shifting symbols onto a and reducing them according to production rules, effectively reversing a rightmost . This top-down predictive nature of LL allows for straightforward recursive implementations, while the shift-reduce mechanism in LR parsing enables handling of more intricate syntactic structures. Regarding expressive power, LL parsers are restricted to the LL(k) subclass of context-free grammars, which excludes left-recursive and certain ambiguous productions without transformation, limiting their applicability to simpler, predictable languages. LR parsers, however, can recognize a strictly larger class of deterministic context-free grammars, including those with left recursion and more complex dependencies that LL cannot handle directly, making LR the more powerful option for general-purpose parsing. For instance, LR(k) parsers encompass all LL(k) grammars as a proper subset, allowing them to parse languages like those of programming constructs with embedded actions. In terms of efficiency and implementation, LL parsers offer simplicity and ease of , particularly for human-written recursive descent code, with linear O(n) for suitable grammars and minimal table sizes when using fixed lookahead. LR parsers, while also achieving O(n) time, involve larger parsing tables and more complex shift-reduce decision logic, increasing effort and runtime overhead, though they detect errors earlier in the input. LL's predictive approach avoids in LL(1) cases, facilitating , but LR's generality comes at the cost of automated table generation tools being essential due to manual complexity.
AspectLL ParsersLR Parsers
Implementation SimplicityEasier for hand-coding via recursive descent; intuitive top-down expansion.More complex; relies on automated tools like / for table construction.
Error DetectionErrors detected during prediction; may require more lookahead for resolution.Earlier detection via stack mismatches; handles reductions proactively.
Table SizeSmaller tables for LL(k); scales with grammar simplicity.Larger tables, especially for full LR(k); LALR variants reduce size.
LL parsers are commonly used in scenarios requiring quick prototyping or for domain-specific languages with straightforward syntax, such as expression evaluators or simple scripting tools, where ease of maintenance outweighs full generality. LR parsers dominate in production compilers for complex languages like C or Java, leveraging tools such as Yacc and its open-source counterpart Bison to automate parsing for large grammars. For cases involving ambiguity, hybrid approaches like Generalized LR (GLR) parsers extend LR capabilities to non-deterministic grammars by maintaining multiple parse paths, combining bottom-up efficiency with tolerance for nondeterminism in natural language processing or extensible languages.

References

  1. [1]
    [PDF] Parsing - CS143 Notes - Stanford University
    Apr 19, 2015 · Parsing is the process of converting a flat program text into a tree structure, recovering the program's structure from its textual ...
  2. [2]
    [PDF] Parsers - Elsevier
    LL(1) grammars can be parsed with either a hand-coded recursive-descent parser or a generated LL(1) parser. Many programming languages can be written in an LL(1) ...
  3. [3]
    Top-down syntax analysis
    Mar 29, 1971 · Section 2 introduces an abstract machine which resembles the interpretive routines often used for top-down syntax analysis. Section 3 shows how ...
  4. [4]
    LL(1) grammars are parsed by top-down parsers. They construct the ...
    LL(1) grammars are parsed by top-down parsers. They construct the derivation tree starting with the start nonterminal and working down. One kind of parser for ...
  5. [5]
    A syntax directed compiler for ALGOL 60 - ACM Digital Library
    A syntax directed compiler for ALGOL 60. Special 25th Anniversary Issue · Syntax-Directed Transduction. A transduction is a mapping from one set of sequences to ...
  6. [6]
    Properties of deterministic top-down grammars - ScienceDirect.com
    A procedure is given for eliminating the ε-rules from an LL(k) grammar at the cost of increasing k by 1. There exist cases in which this increase is inevitable.
  7. [7]
    Top-down syntax analysis | Acta Informatica
    Top-down syntax analysis. Published: June 1971. Volume 1, pages 79–110, (1971); Cite this article. Download PDF ... Knuth, D.E. Top-down syntax analysis. Acta ...
  8. [8]
    Deterministic Techniques for Efficient Non-Deterministic Parsers
    Automata, Languages and Programming (ICALP 1974). Deterministic Techniques for Efficient Non-Deterministic Parsers. Download book PDF. Bernard Lang. Part of ...
  9. [9]
    History - antlr
    Release 1.33 is the version corresponding to the initial book release. ANTLR 2.0.0 came out around May 1997 and was partially funded so Terence hired John ...
  10. [10]
    [PDF] Context-Free Grammars and Constituency Parsing
    In this chapter we introduce context-free grammars, give a small sample gram- mar of English, introduce more formal definitions of context-free grammars and.<|control11|><|separator|>
  11. [11]
    [PDF] Lecture Notes on Context-Free Grammars
    Feb 14, 2023 · A grammar is defined by set of productions α → β and a start symbol S, a distinguished non-terminal symbol. In the productions, α and β are ...
  12. [12]
    Three models for the description of language - IEEE Xplore
    Three models for the description of language. Abstract: We investigate several conceptions of linguistic structure to determine whether or not they can provide ...
  13. [13]
    [PDF] FIRST & FOLLOW SETS - UAF CS
    These functions, FIRST and FOLLOW, allow us to fill in the entries of a predictive parsing table for G, whenever possible.
  14. [14]
    [PDF] Parsing and Yaccing - cs.Princeton
    Context-Free Grammars: definition. A CFG consists of. • a finite set N = N1 ... Iteratively visit grammar productions to compute nullable, first, follow.
  15. [15]
    [PDF] Basics of Compiler Design - Otterbein University
    Figure 3.18: Program for table-driven LL(1) parsing with the next input symbol. If the table-entry is empty, we report an error. If not, we pop the ...
  16. [16]
    [PDF] CS 314 Principles of Programming Languages
    Feb 7, 2018 · A terminal symbol has no FOLLOW set. FIRST and FOLLOW sets can be constructed automatically. Page 7. Predictive Parsing. 7. • FIRST (α) ∩ FIRST ...<|control11|><|separator|>
  17. [17]
    [PDF] Compilers: Principles, Techniques, and Tools
    This interior of this book was composed in LATEX. Library of Congress Cataloging-in-Publication Data. Compilers : principles, techniques, and tools / Alfred V.
  18. [18]
    [PDF] LL1.pdf - UT Computer Science
    We can read off the recursive parser from the parsing table. • We can also use an iterative parser that is driven by the parsing table. • Advantage: – ...Missing: pseudocode | Show results with:pseudocode
  19. [19]
    [PDF] a necessary preliminary to constructing the LL(1) parsing table
    Oct 8, 2007 · • FIRST and FOLLOW sets are always sets of terminals (plus, perhaps, ǫ for FIRST sets, and EOF for follow sets). Nonterminals are never in a ...Missing: seminal | Show results with:seminal
  20. [20]
    [PDF] Lecture 9: LL(1) parsing - GitHub Pages
    Sep 28, 2022 · LL(1). LL(1) is a simple table-driven top-down parsing algorithm. Requirements: ▷ Grammar has no left recursion. ▷ For each nonterminal ...Missing: pseudocode | Show results with:pseudocode
  21. [21]
    [PDF] Non-recursive predictive parsing - CS@Purdue
    A ε–free grammar where each alternative expansion for A begins with a distinct terminal is a simple LL(1) grammar. Example. • S → aS | a is not LL(1) because ...
  22. [22]
    [PDF] How do LL(1) Parsers Build Syntax Trees? - cs.wisc.edu
    Building complete (concrete) parse trees automatically is fairly easy. As tokens and non-terminals are matched, they are pushed onto a second stack, the ...
  23. [23]
    On the translation of languages from left to right - ScienceDirect.com
    View PDF; Download full issue. Search ScienceDirect. Elsevier. Information ... On the translation of languages from left to right. Author links open overlay ...
  24. [24]
    [PDF] A Practical approach to LL(k); LLm(n) - Purdue e-Pubs
    Jul 30, 1992 · A parser with k tokens of lookahead can choose between all productions. (which are recognizable at a particular point) that have common prefixes ...Missing: origin | Show results with:origin
  25. [25]
    Extended LL(k) grammars and parsers
    In this paper, a new class of grammars, called. ELL(k) grammars, is defined, which are suitable for practical use because the parsers constructed by this ...
  26. [26]
    On the Translation of Languages from Left to Right - Semantic Scholar
    On the Translation of Languages from Left to Right · D. Knuth · Published in Information and Control 1 December 1965 · Computer Science.
  27. [27]
    Computer Science 160 Translation of Programming Languages
    Eliminating Immediate Left Recursion. To remove left recursion, we can transform the grammar. Consider a grammar fragment of the form. A → A α. | β where α or ...
  28. [28]
    [PDF] Top-down parsing, left-recursion removal
    Eliminating Left Recursion. The transformation eliminates immediate left recursion. What about more general, indirect left recursion ? The general algorithm ...
  29. [29]
    [PDF] Removing Left Recursion from Context-Free Grammars
    In this paper we develop a number of improvements to Panll's algorithm, which help somewhat but do not completely solve the prob- lem. We then go on to develop ...
  30. [30]
    [PDF] Dragon-book.pdf - School of Information Science and Technology
    Here is an outline of the chapters: Chapter 1 contains motivational material and also presents some background issues in computer architecture and programming- ...
  31. [31]
    [PDF] Normal Forms for CFG's - Stanford InfoLab
    Proof: Start with a CFG for L. ◇ Perform the following steps in order: 1. Eliminate ε-productions. 2. Eliminate unit productions.<|control11|><|separator|>
  32. [32]
    [PDF] 1 Eliminating Unit Productions
    Oct 17, 2011 · If G = (V,T,R,S) is a CFG with no null production, then we can design a algo- rithm (see Algorithm 2) to find a CFG G1 = (V,T,R1,S) having no ...
  33. [33]
    [PDF] Lecture Notes on Top-Down Predictive LL Parsing - André Platzer
    In this lecture we discuss a parsing algorithm that traverses the input string from left to right giving a left-most derivation and makes a decision on ...Missing: advantages | Show results with:advantages
  34. [34]
    [PDF] LL parsing Nullable, FIRST, and FOLLOW
    Sep 13, 2021 · LL parsing. Nullable, FIRST, and FOLLOW. Görel Hedin. Revised: 2021-09 ... Conflicts in the table? The grammar is not LL(1). 5. No ...<|control11|><|separator|>
  35. [35]
    [PDF] Advanced LL Parsing Techniques - Faculty of Information Technology
    Advanced LL Parsing Techniques. 3 / 38. Page 4. Example LL(1) Grammar. Example ... Standard LL(1) Parsing – Conflicts. Rules of G2. S → aAaa | bAba, A → b ...
  36. [36]
    On the role of error productions in syntactic error correction
    Error productions are presented as a means of augmenting syntactic error correctors. Such productions are able to simply and efficiently handle a wide variety ...
  37. [37]
    Grammar partitioning and modular deterministic parsing
    We study three conditions for determinism in grammar partitioning: first using homogeneous modules of the LR(1) or LL(1) kind; then using heterogeneous modules ...
  38. [38]
    Packrat parsing:: simple, powerful, lazy, linear time, functional pearl
    Yet despite its power, packrat parsing shares the same simplicity and elegance as recursive descent parsing; in fact converting a backtracking recursive descent ...
  39. [39]
    Adaptive LL(*) parsing: the power of dynamic analysis
    This paper introduces the ALL(*) parsing strategy that combines the simplicity, efficiency, and predictability of conventional top-down LL(k) parsers with the ...<|control11|><|separator|>
  40. [40]
    LL versus LR parsing with illustrations from ALGOL 68
    The fact that LR methods can be applied to a wider class of languages does not seem to give them a significant advantage in practice.Missing: comparison | Show results with:comparison