Many resources are needed to download a project. Please understand that we have to compensate our server costs. Thank you in advance. Project price only 1 $
You can buy this project and download/modify it how often you want.
// Copyright 2017-present Strumenta and contributors, licensed under Apache 2.0.
// Copyright 2024-present Strumenta and contributors, licensed under BSD 3-Clause.
package org.antlr.v4.kotlinruntime.atn
import kotlin.time.measureTimedValue
/**
* This class contains profiling gathered for a particular decision.
*
* Parsing performance in ANTLR 4 is heavily influenced by both static factors
* (e.g. the form of the rules in the grammar) and dynamic factors (e.g., the
* choice of input and the state of the DFA cache at the time profiling
* operations are started). For best results, gather and use aggregate
* statistics from a large sample of inputs representing the inputs expected in
* production before using the results to make changes in the grammar.
*
* @param decision The decision number, which is an index into [ATN.decisionToState]
*
* @since 4.3
*/
@Suppress("PropertyName", "MemberVisibilityCanBePrivate")
public class DecisionInfo(public val decision: Int) {
/**
* The total number of times [ParserATNSimulator.adaptivePredict] was
* invoked for this decision.
*/
public var invocations: Long = 0
/**
* The total time spent in [ParserATNSimulator.adaptivePredict] for
* this decision, in nanoseconds.
*
* The value of this field contains the sum of results obtained
* by [measureTimedValue], and is not adjusted to compensate for JIT
* and/or garbage collection overhead.
*
* For best accuracy, perform profiling in a separate process
* which is warmed up by parsing the input prior to profiling.
* If desired, call [ATNSimulator.clearDFA] to reset the DFA cache
* to its initial state before starting the profiling measurement pass.
*/
public var timeInPrediction: Long = 0
/**
* The sum of the lookahead required for SLL prediction for this decision.
*
* Note that SLL prediction is used before LL prediction for performance
* reasons even when [PredictionMode.LL] or [PredictionMode.LL_EXACT_AMBIG_DETECTION] is used.
*/
public var SLL_TotalLook: Long = 0
/**
* Gets the minimum lookahead required for any single SLL prediction to
* complete for this decision, by reaching a unique prediction, reaching an
* SLL conflict state, or encountering a syntax error.
*/
public var SLL_MinLook: Long = 0
/**
* Gets the maximum lookahead required for any single SLL prediction to
* complete for this decision, by reaching a unique prediction, reaching an
* SLL conflict state, or encountering a syntax error.
*/
public var SLL_MaxLook: Long = 0
/**
* Gets the [LookaheadEventInfo] associated with the event where
* the [SLL_MaxLook] value was set.
*/
public var SLL_MaxLookEvent: LookaheadEventInfo? = null
/**
* The sum of the lookahead required for LL prediction for this decision.
*
* Note that LL prediction is only used when SLL prediction reaches a
* conflict state.
*/
public var LL_TotalLook: Long = 0
/**
* Gets the minimum lookahead required for any single LL prediction to
* complete for this decision.
*
* An LL prediction completes when the algorithm reaches a unique prediction,
* a conflict state (for [PredictionMode.LL], an ambiguity state, for
* [PredictionMode.LL_EXACT_AMBIG_DETECTION], or a syntax error).
*/
public var LL_MinLook: Long = 0
/**
* Gets the maximum lookahead required for any single LL prediction to
* complete for this decision.
*
* An LL prediction completes when the algorithm reaches a unique prediction,
* a conflict state (for [PredictionMode.LL], an ambiguity state, for
* [PredictionMode.LL_EXACT_AMBIG_DETECTION], or a syntax error).
*/
public var LL_MaxLook: Long = 0
/**
* Gets the [LookaheadEventInfo] associated with the event where
* the [LL_MaxLook] value was set.
*/
public var LL_MaxLookEvent: LookaheadEventInfo? = null
/**
* A collection of [ContextSensitivityInfo] instances describing the
* context sensitivities encountered during LL prediction for this decision.
*
* @see ContextSensitivityInfo
*/
public val contextSensitivities: MutableList = ArrayList()
/**
* A collection of [ErrorInfo] instances describing the parse errors
* identified during calls to [ParserATNSimulator.adaptivePredict] for
* this decision.
*
* @see ErrorInfo
*/
public val errors: MutableList = ArrayList()
/**
* A collection of [AmbiguityInfo] instances describing the
* ambiguities encountered during LL prediction for this decision.
*
* @see AmbiguityInfo
*/
public val ambiguities: MutableList = ArrayList()
/**
* A collection of [PredicateEvalInfo] instances describing the
* results of evaluating individual predicates during prediction for this
* decision.
*
* @see PredicateEvalInfo
*/
public val predicateEvals: MutableList = ArrayList()
/**
* The total number of ATN transitions required during SLL prediction for
* this decision.
*
* An ATN transition is determined by the number of times the
* DFA does not contain an edge that is required for prediction, resulting
* in on-the-fly computation of that edge.
*
* If DFA caching of SLL transitions is employed by the implementation, ATN
* computation may cache the computed edge for efficient lookup during
* future parsing of this decision. Otherwise, the SLL parsing algorithm
* will use ATN transitions exclusively.
*
* @see SLL_ATNTransitions
* @see ParserATNSimulator.computeTargetState
* @see LexerATNSimulator.computeTargetState
*/
public var SLL_ATNTransitions: Long = 0
/**
* The total number of DFA transitions required during SLL prediction for
* this decision.
*
* If the ATN simulator implementation does not use DFA caching for SLL
* transitions, this value will be 0.
*
* @see ParserATNSimulator.getExistingTargetState
* @see LexerATNSimulator.getExistingTargetState
*/
public var SLL_DFATransitions: Long = 0
/**
* Gets the total number of times SLL prediction completed in a conflict
* state, resulting in fallback to LL prediction.
*
* Note that this value is not related to whether or not
* [PredictionMode.SLL] may be used successfully with a particular
* grammar. If the ambiguity resolution algorithm applied to the SLL
* conflicts for this decision produce the same result as LL prediction for
* this decision, [PredictionMode.SLL] would produce the same overall
* parsing result as [PredictionMode.LL].
*/
public var LL_Fallback: Long = 0
/**
* The total number of ATN transitions required during LL prediction for
* this decision.
*
* An ATN transition is determined by the number of times the
* DFA does not contain an edge that is required for prediction,
* resulting in on-the-fly computation of that edge.
*
* If DFA caching of LL transitions is employed by the implementation, ATN
* computation may cache the computed edge for efficient lookup during
* future parsing of this decision. Otherwise, the LL parsing algorithm will
* use ATN transitions exclusively.
*
* @see LL_DFATransitions
* @see ParserATNSimulator.computeTargetState
* @see LexerATNSimulator.computeTargetState
*/
public var LL_ATNTransitions: Long = 0
/**
* The total number of DFA transitions required during LL prediction for
* this decision.
*
* If the ATN simulator implementation does not use DFA caching for LL
* transitions, this value will be `0`.
*
* @see ParserATNSimulator.getExistingTargetState
* @see LexerATNSimulator.getExistingTargetState
*/
public var LL_DFATransitions: Long = 0
override fun toString(): String =
buildString {
append("{")
append("decision=")
append(decision)
append(", contextSensitivities=")
append(contextSensitivities.size)
append(", errors=")
append(errors.size)
append(", ambiguities=")
append(ambiguities.size)
append(", SLL_lookahead=")
append(SLL_TotalLook)
append(", SLL_ATNTransitions=")
append(SLL_ATNTransitions)
append(", SLL_DFATransitions=")
append(SLL_DFATransitions)
append(", LL_Fallback=")
append(LL_Fallback)
append(", LL_lookahead=")
append(LL_TotalLook)
append(", LL_ATNTransitions=")
append(LL_ATNTransitions)
append("}")
}
}
