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RIPAL: Responsive and Intuitive Parsing for the Analysis of Language

Licensing

RIPAL: Responsive and Intuitive Parsing for the Analysis of Language is licensed under LGPL v. 2.1.

For more information, see LICENSE.md.

Version History

6.0.0

  1. Updating RIPAL to run on Java 22
  2. Upgrading to latest JUnit standalone executor for compatibility with JUnit 5
  3. Updating unit tests to use JUnit 5 syntax

5.0.0

  1. LR1 parsing

4.0.0

  1. SLR1 parsing

3.0.0

  1. Improving methodology of unit test assertions
  2. Improving terminology of grammar-related variables in unit testing
  3. Improving terminology used to refer to context-free grammars in main code
  4. Factoring LR0 parse stack object out of LR0 parser
  5. Adding checking for context-free grammar equality when comparing LR0 production set DFAs
  6. Restructuring the handling of augmented context-free grammar when generating an LR0 parser
  7. Documenting project LGPL licensing
  8. Improving conflict tracking in LR0 parser contruction
  9. Improving unit test coverage of error cases in LR0 parsing
  10. Cleaning up and adding missing equality unit tests
  11. Restructuring code namespaces and class names to be more generic and consistent
  12. Moving unit tests into a namespace structure that mirrors the main code
  13. Improving Makefile to not require manual encoding of unit test class names
  14. Reducing the usage of the instanceof operator within the context of handling LR0 parse actions
  15. Improving the prioritizing and testing of regular expression and context-free grammar tokenization error handling
  16. Improving error handling in first set calculator
  17. Improving error handling in LR0 production set DFA compiler
  18. Improving unit test coverage related to Epsilon NFA to NFA conversion and NFA to DFA conversion
  19. Improving unit test coverage of regular and context-free parser factory handling of empty grammars
  20. Improving unit test coverage related to error handling in production node dot repository
  21. Improving terminology related to context-free grammars in unit test names
  22. Improving terminology related to regular expressions in unit test names

2.0.0

  1. LR0 parsing

1.0.0

  1. Initial Beta release with support for regular language parsing and LL1 parsing

Regular Languages

Step 1: Tokenize Regular Expression

  • Initialize an empty list of tokens found
  • Initialize parenthesis depth as 0
  • Initialize an escape status flag to not escaping
  • For each character in the regular expression
    • If escaping, add the current character as a character token to the result, set escape status to not escaping and move on to the next character
    • If the character is an open parenthesis, increment parenthesis depth
    • If the character is a close parenthesis, decrement parenthesis depth
    • If the current character is the escape symbol, set the escape status flag to escaping and move on the to the next character
    • If parenthesis depth is negative, fail
    • If the current character is a kleene closure or an or symbol and the token list is empty, append epsilon to the token list
    • If the current character is a close parenthesis, kleene closure or and or symbol and the last token was an open parenthesis or an or token, append epsilon to the token list
    • If the character is a an open parenthesis, close parenthesis, kleene closure, or symbol or character, add it to the list
  • If parenthesis depth is not zero, fail
  • If escaping, fail
  • If the token list contains no tokens or the last token was an or symbol, append epsilon to the token list
  • Return the token list

Step 2: Convert Token List to Parse Tree

  • If there is at least one or token at the top level (not within parentheses)
    • Create a concatenation node
    • For each segment of the token list separated by top-level or tokens (excluding the or token), perform the conversion recursively, appending the result as a child of the concatenation node
    • Return the concatenation node
  • Otherwise, create a concatenation node
  • Initialize parenthesis depth as 0
  • For each token in the list
    • If the token is an open parenthesis, increment parenthesis depth
    • If the token is a close parenthesis, decrement parenthesis depth
    • If the token is a character and parenthesis depth is 0, append a character node as a child of the concatenation node
    • If the token is a kleene closure symbol and parenthesis depth is 0, re-parent the previous child as a child of a new kleene closure node
    • If the token is a close parenthesis token which brings parenthesis depth back to 0, perform the conversion recursively on the contents of the parentheses, appending the result as the child of a concatenation node
  • Return the concatenation node

Step 3: Convert Parse Tree to Epsilon-NFA

  • Build the state group (Epsilon-NFA with tracked first and last states) from the root node of the parse tree as follows
    • If the parse tree node is a concatenation node, build state groups for all child nodes, then insert epsilon transitions between the end state of each and the start state of the next
    • If the parse tree node is a character node, the state group has two-node Epsilon-NFA with a transition between the states matching the character from the node
    • If the parse tree node is a kleene closure node, build the child node state group, then add epsilon transitions in both directions between the resulting start and end states
    • If the parse tree node is a concatenation node, build state groups for all child nodes, then insert epsilon transitions from a new state state to each group's start state and from each group's end state to a new end state
  • Return an Epsilon-NFA with a start state matching that of the top-level state group, setting the corresponding end state to accepting

Step 4: Convert Epsilon-NFA to NFA

Run the following algorithm for the start state of the Epsilon-NFA:

  • If the provided Epsilon-NFA state has already been covered, return the corresponding mapped NFA state
  • Create a new start state
  • Map the provided Epsilon-NFA state to this new start state, flagging the Epsilon-NFA state as having been covered
  • If the provided Epsilon-NFA state is accepting or an accepting Epsilon-NFA state is reachable from that state via a sequence of epsilon transitions, flag the new start state as accepting
  • For each non-epsilon transition from the provided Epsilon-NFA state
    • Apply this conversion recursively on the Epsilon-NFA state following the transition, then add a transition from the new start state to the resulting NFA
  • For each epsilon transition from the provided Epsilon-NFA state
    • Obtain all tangible Epsilon-NFA state transitions reachable from the provided Epsilon-NFA state via a sequence of epsilon transitions
    • For each such transition, apply this conversion recursively on the Epsilon-NFA state following the transition, then add a transition from the new start state to the resulting NFA, using that transition's input character as the transition input
  • Return the new start state

Step 5: Convert NFA to DFA

Run the following algorithm for the set containing a single element - the start state of the NFA:

  • If the provided set of NFA states has alraedy been covered, return the corresponding mapped DFA state
  • Create a new start state
  • Map the provided set of NFA states to this new start state, flagging the NFA state as having been covered
  • Create an empty mapping of input characters to sets of NFA states
  • For each NFA state in the provided set of NFA states
    • Add the mapping entry of input character to subsequent NFA state to the mapping, appending to the set corresponding to that input character if one or more elements already exist for that character
    • If the NFA state is accepting, flag the new start state as accepting
  • For each entry in the mapping of input characters to NFA states
    • Apply this conversion recursively on the set of NFA states corresponding to that input character
    • Add a transition from the new start state to the resulting DFA, using that input character as the transition input
  • Return the new start state

Step 6: Feed String to DFA

  • Initialize the current state to the DFA's start state
  • Initialize the current character position to 0
  • While the current state exists and the character position is less than the size of the input string
    • Calculate the current input character as input string character at the current character position
    • Update the current state to the state following from the current state's transition with the current input character
    • Increment the current character position
  • If the current state exists and is accepting, accept, otherwise reject

Context-Free Languages

Step 1: Tokenize Context-Free Grammar

  • Initialize an empty list of tokens found
  • Initialize a buffer of pending characters to the empty string
  • Initialze a flag tracking whether tokenization is currently within a terminal string to not being within a terminal string
  • Initialize an escape status flag to not escaping
  • For each character in the context-free grammar production
    • If escaping, appending it to the buffer and set escape status to not escaping
    • If the character is the escape character and tokenization is not currently within a terminal string, fail
    • If the character is the escape character and tokenization is currently within a terminal string, set escape status to escaping
    • If the character is a colon and tokenization is not currently within a terminal string, flush the buffer, then add a separator token to the token list
    • If the character is a double quote and tokenization is not currently within a terminal string, flush the buffer, then flag that tokenization is within a terminal string
    • If the character is a double quote and tokenization is currently within a terminal string, flush the buffer, then flag that tokenization is not within a terminal string
    • If the character is a space and tokenization is not currently within a terminal string, flush the buffer
    • If the character is none of the above, append it to the buffer
  • If tokenization is currently within a terminal string, fail
  • If the token list has fewer than three tokens, or doesn't start with a non-terminal token followed by a separator token, fail
  • If the number of separator tokens is not one, fail
  • Remove all epsilon tokens from the result unless the right-hand side of the production is equivalent to a single epsilon, in which case reduce the right-hand side to a single epsilon
  • Return the token list

The process of flushing the buffer can be defined as:

  • If the triggering character is a colon, an opening double-quote or a space, add a non-terminal with name equal to the buffer contents to the token list (if not empty), then empty the buffer
  • If the triggering character is a closing double-quote, add a terminal with value equal to the buffer contents to the token list (or an epsilon token if the buffer is empty), then empty the buffer

Step 2: Convert Token List to Parse Tree

  • Initialize a production node
  • Initialize a non-terminal node with value equal to the value of the first (non-terminal) token from the provided token list, appending it as the first child of the production node
  • Initialize a concatenation node, appending it as the second child of the production node
  • For each token in the provided token list, create a corresponding node, appending it as a child of the concatenation node
  • Return the production node

Step 3: Convert Parse Tree into Parse Table (LL1)

  • Initialize a parse table
  • For each production in the provided context-free grammar
    • Calculate the first set for the production rule
    • For each non-epsilon terminal in that first set, map the combination of that rule's left-hand non-terminal node and that terminal from the first set to the production rule index
    • If epsilon is part of the first set, for each terminal in the follow set of that rule's left-hand non-terminal node, map the combination of that rule's left-hand non-terminal and the follow set terminal to the production rule index
  • Return the parse table

To calculate the first set for a production node, initialize an empty set of nodes processed, then call the following with that set:

  • Initialize an empty set of nodes
  • Add the provided production node to the set of nodes processed
  • If the first token on the right-hand side of the production rule is a terminal node, append that node to the set of nodes
  • If the first token on the right-hand side of the production rule is an epsilon node, append that node to the set of nodes
  • If the first token on the right-hand size of the production rule is a non-terminal node
    • For each production node (rule) in the grammar with that non-terminal on the left-hand size, recursively add the first set from that production to the set of nodes, with the exception of epsilon nodes
    • If the right-hand side is in the form of a sequence of non-terminal nodes that go to epsilon followed by a terminal node, add that terminal node to the set of nodes
    • If the right-hand side is in the form of a sequence of non-terminal nodes that go to epsilon, add epsilon to the set of nodes
    • If the right-hand side is in the form of a sequence of non-terminal nodes that go to epsilon followed by a non-terminal node that goes to something other than epsilon, add the first set from that non-terminal node to the set of nodes by performing this calculation recursively for each production node with that non-terminal on the left-hand side (if the production node does not belong to the set of nodes already processed)
  • Return the set of nodes

To calculate the follow set for a non-terminal node:

  • Create a mapping of non-terminal nodes to sets of follow nodes
  • Add an end-of-string node to the set for the grammar's start symbol
  • Calculate which non-terminals go to epsilon by looking for production rules where the right-hand-side is simply an epsilon node
  • For each production in the context-free grammar
    • For any non-terminal node directly followed by a terminal node, store the first character of the terminal node in the mapping as belonging to the follow of the non-terminal node
    • For any non-terminal node followed by a series of non-terminals that go to epsilon, then a terminal node, store the first character of the terminal node in the mapping as belonging to the follow of the non-terminal node
    • For any non-terminal node directly followed by a non-terminal node, store the first set of the second non-terminal node (excluding epsilon) in the mapping as belonging to the follow of the first non-terminal node
    • For any non-terminal node directly followed by aseries of non-terminals that go to epsilon, then a non-terminal node, store the first set of the second non-terminal node (excluding epsilon) in the mapping as belonging to the follow of the first non-terminal node
  • While there still exists some follow in the subsequent form to propagate
    • For each production ending in a non-terminal, store the follow set of the left-hand non-terminal node in the mapping as belonging to the final right-hand non-terminal
    • For each production ending in a sequence of non-terminals that go to epsilon proceeded by another non-terminal, store the follow set of the left-hand non-terminal node in the mapping as belonging to that non-terminal
  • Return the mapping

Step 3: Convert Parse Tree into Parse Table (LR0)

  • Initialize a DFA with the potential to store sets of context-free grammar productions in its states
  • Create an augmented version of the provided context-free grammar
  • Create a new DFA start state containing the starting production of the augmented grammar with a dot symbol added to the right-hand side
    • N -> .S
  • Expand the DFA's start state using the algorithm stated below, adding it to the DFA
  • Construct the parse table using the algorithm stated below
  • Return the parse table

To create the augmented context-free grammar:

  • Create a new start non-terminal as follows:
    • Scan through the context-free grammar and collect the set of names used within non-terminal nodes
    • Initialize the new start symbol name to the same name as the current start symbol, S
    • While the new start symbol name is within the collected set, append a ' to the end of the name
  • Create a new start symbol, N, with the above name, and add a new initial production in the form N -> S
  • For each multi-character terminal node in the new grammar, replace it with the corresponding set of terminal nodes with one character each
  • Return the augmented context-free grammar

To expand the start state of the DFA containing the context-free grammar production sets:

  • Obtain the set of context-free-grammar productions stored in the state
  • Calculate the closure of the production set as follows:
    • For each production in the set in the form A -> prefix .B, where A and B are non-terminals and prefix is any empty or non-empty set of symbols, add all productions from the context-free grammar in the form B -> symbols to the set, prefixing the right-hand side with a dot
    • Repeat the above process until no productions are added
    • For each production in the set in the form A -> .epsilon, add A -> epsilon. to the set
  • If a DFA state already exists with this production set, return that state
  • Construct the current state with this set of productions
  • For each symbol appearing directly after the dot on the right-hand side of one of the productions
    • Collect the set context-free grammar productions where a dot appears directly before that symbol
    • For each such production, shift the dot to the right of that symbol
    • Apply this expanding algorithm to a subsequent state starting with this set of productions with the dot shifted
    • Create a transition from the current state to the subsequent state with transition symbol equal to this symbol
  • Return the current state

To construct the parse table:

  • Initialize a parse table, setting the start state as the production set DFA's start state
  • Initialize the current state to the production set DFA's start state
  • For each production in the current state's set in the form A -> prefix.
    • Map the combination of each terminal node in the context-free grammar plus the end of string node and the current state to a reduce action corresponding to the production index
  • For each transition from the current state with a non-terminal transition symbol
    • Map the combination of the transition symbol and the current state to a shift action corresponding to the next state in the transition
  • For each transition from the current state with a terminal transition symbol
    • Map the combination of the transition symbol and the current state to a goto action corresponding to the next state in the transition
  • Return the parse table

Step 3: Convert Parse Tree into Parse Table (SLR1)

Follow the same steps as is done for LR0, with the change noted below.

When construcing the parse table:

  • For each production in the current state's set in the form A -> prefix.
    • Map the combination of each terminal node in the context-free grammar plus the end of string node that fall within the follow set of A and the current state to a reduce action corresponding to the production index

Step 3: Convert Parse Tree into Parse Table (LR1)

Follow the same steps as is done for LR0, with the changes noted below.

When calculating DFA closures:

  • Store an additional set of lookaheads in each closure item
  • For the initial closure item of S' -> .S $
    • Initialize the lookahead set to {$}
  • When calculating further lookaheads within a set of closure items spawning from A -> .B C {L}
    • For each production in the form B -> .D in the grammar and each token T in the first set of C L, add B -> .D {T} to the closure set
  • When creating a closure item for a new closure set spawning from an item A -> .B C {L}, the new closure item will be in the form A -> B .C {L}

When construction the parse table:

  • For each production in the current state's set in the form A -> prefix. {L}
    • Map the combination of {L} and the current state to a reduce action corresponding to the production index

Step 4: Attempt to Match String using Parse Table (LL1)

  • If the provided context-free-grammar has no rules, reject
  • Initialize a stack of syntax nodes to contain the start symbol
  • Initialize the remaining input to contain the input string
  • While the stack still contains a symbol and the remaining input is not empty
    • If the top symbol of the stack is a non-terminal node, remove the top symbol, then add the right-hand side of the context-free-grammar rule corresponding to the parse table entry for that non-terminal node combined the first character of the remaining input (reject if one doesn't exist)
    • If the top symbol of the stack is a terminal node, remove the first character of that terminal node and remaining input if they match (rejecting otherwise), adding back the remaining content of the terminal node to the stack if the remaining content is not empty
  • While the remaining input is empty and the top symbol of the stack is a non-terminal node corresponding to a parse table entry mapping to the end-of-string node, remove the top symbol, then add the right-hand side of the context-free-grammar rule corresponding to that context-free-grammar rule
  • If the stack and remaining input string are empty, accept, otherwise reject

Step 4: Attempt to Match String using Parse Table (LR0 / SLR1 / LR1)

  • Initialize the parse stack with the parse table's start state
  • Initialize the current state to the parse table's start state
  • Initialize the input queue with the set of input characters as terminal nodes, plus an end of string node
  • While not done
    • Set the character node to the first terminal in the input queue
    • If the top of the parse stack is a context-free grammar node, set the character node to that grammar node
    • Look up the parse table entry corresponding the the current state combined with the character node
    • If the entry is not found, reject
    • If the entry is the accept action, accept
    • If the entry is a shift action, shift the first character from the input queue onto the top of the parse stack, then append the shift action's state to the top of the parse stack
    • If the entry is a reduce action, remove two entries from the top of the parse stack for each syntax node in the right-hand side of the reduce action's corresponding production, then add the left-hand size node from that production to the top of the parse stack
    • If the entry is a goto action, add the goto action's state to the top of the parse stack
    • Set the current state to the top state from the parse stack

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Responsive and Intuitive Parsing for the Analysis of Language - Regular Expression, LL1, LR0, SLR1 and LR1 parsing

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