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Kotlin multiplatform port of ANTLR
/*
* Copyright (c) 2012-2017 The ANTLR Project. All rights reserved.
* Use of this file is governed by the BSD 3-clause license that
* can be found in the LICENSE.txt file in the project root.
*/
package org.antlr.v4.kotlinruntime.atn
/**
* 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.
*
* @since 4.3
*/
class DecisionInfo
/**
* Constructs a new instance of the [DecisionInfo] class to contain
* statistics for a particular decision.
*
* @param decision The decision number
*/
(
/**
* The decision number, which is an index into [ATN.decisionToState].
*/
val decision: Int) {
/**
* The total number of times [ParserATNSimulator.adaptivePredict] was
* invoked for this decision.
*/
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 differential results obtained
* by [System.nanoTime], and is not adjusted to compensate for JIT
* and/or garbage collection overhead. For best accuracy, use a modern JVM
* implementation that provides precise results from
* [System.nanoTime], and 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.
*/
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.
*/
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.
*/
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.
*/
var SLL_MaxLook: Long = 0
/**
* Gets the [LookaheadEventInfo] associated with the event where the
* [.SLL_MaxLook] value was set.
*/
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.
*/
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.
*/
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.
*/
var LL_MaxLook: Long = 0
/**
* Gets the [LookaheadEventInfo] associated with the event where the
* [.LL_MaxLook] value was set.
*/
var LL_MaxLookEvent: LookaheadEventInfo? = null
/**
* A collection of [ContextSensitivityInfo] instances describing the
* context sensitivities encountered during LL prediction for this decision.
*
* @see ContextSensitivityInfo
*/
val contextSensitivities: List = ArrayList()
/**
* A collection of [ErrorInfo] instances describing the parse errors
* identified during calls to [ParserATNSimulator.adaptivePredict] for
* this decision.
*
* @see ErrorInfo
*/
val errors: List = ArrayList()
/**
* A collection of [AmbiguityInfo] instances describing the
* ambiguities encountered during LL prediction for this decision.
*
* @see AmbiguityInfo
*/
val ambiguities: List = ArrayList()
/**
* A collection of [PredicateEvalInfo] instances describing the
* results of evaluating individual predicates during prediction for this
* decision.
*
* @see PredicateEvalInfo
*/
val predicateEvals: List = 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
*/
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
*/
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].
*/
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
*/
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
*/
var LL_DFATransitions: Long = 0
override fun toString(): String {
return "{" +
"decision=" + decision +
", contextSensitivities=" + contextSensitivities.size +
", errors=" + errors.size +
", ambiguities=" + ambiguities.size +
", SLL_lookahead=" + SLL_TotalLook +
", SLL_ATNTransitions=" + SLL_ATNTransitions +
", SLL_DFATransitions=" + SLL_DFATransitions +
", LL_Fallback=" + LL_Fallback +
", LL_lookahead=" + LL_TotalLook +
", LL_ATNTransitions=" + LL_ATNTransitions +
'}'
}
}