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/*
 * 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.runtime.atn;

import java.util.ArrayList;
import java.util.List;

/**
 * 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 */ public class DecisionInfo { /** * The decision number, which is an index into {@link ATN#decisionToState}. */ public final int decision; /** * The total number of times {@link ParserATNSimulator#adaptivePredict} was * invoked for this decision. */ public long invocations; /** * The total time spent in {@link ParserATNSimulator#adaptivePredict} for * this decision, in nanoseconds. * *

* The value of this field contains the sum of differential results obtained * by {@link 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 * {@link System#nanoTime()}, and perform profiling in a separate process * which is warmed up by parsing the input prior to profiling. If desired, * call {@link ATNSimulator#clearDFA} to reset the DFA cache to its initial * state before starting the profiling measurement pass.

*/ public long timeInPrediction; /** * 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 {@link PredictionMode#LL} or * {@link PredictionMode#LL_EXACT_AMBIG_DETECTION} is used. */ public long SLL_TotalLook; /** * 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 long SLL_MinLook; /** * 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 long SLL_MaxLook; /** * Gets the {@link LookaheadEventInfo} associated with the event where the * {@link #SLL_MaxLook} value was set. */ public LookaheadEventInfo SLL_MaxLookEvent; /** * 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 long LL_TotalLook; /** * 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 * {@link PredictionMode#LL}, an ambiguity state (for * {@link PredictionMode#LL_EXACT_AMBIG_DETECTION}, or a syntax error. */ public long LL_MinLook; /** * 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 * {@link PredictionMode#LL}, an ambiguity state (for * {@link PredictionMode#LL_EXACT_AMBIG_DETECTION}, or a syntax error. */ public long LL_MaxLook; /** * Gets the {@link LookaheadEventInfo} associated with the event where the * {@link #LL_MaxLook} value was set. */ public LookaheadEventInfo LL_MaxLookEvent; /** * A collection of {@link ContextSensitivityInfo} instances describing the * context sensitivities encountered during LL prediction for this decision. * * @see ContextSensitivityInfo */ public final List contextSensitivities = new ArrayList(); /** * A collection of {@link ErrorInfo} instances describing the parse errors * identified during calls to {@link ParserATNSimulator#adaptivePredict} for * this decision. * * @see ErrorInfo */ public final List errors = new ArrayList(); /** * A collection of {@link AmbiguityInfo} instances describing the * ambiguities encountered during LL prediction for this decision. * * @see AmbiguityInfo */ public final List ambiguities = new ArrayList(); /** * A collection of {@link PredicateEvalInfo} instances describing the * results of evaluating individual predicates during prediction for this * decision. * * @see PredicateEvalInfo */ public final List predicateEvals = new 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 long SLL_ATNTransitions; /** * 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 long SLL_DFATransitions; /** * 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 * {@link 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, {@link PredictionMode#SLL} would produce the same overall * parsing result as {@link PredictionMode#LL}.

*/ public long LL_Fallback; /** * 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 long LL_ATNTransitions; /** * 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 long LL_DFATransitions; /** * Constructs a new instance of the {@link DecisionInfo} class to contain * statistics for a particular decision. * * @param decision The decision number */ public DecisionInfo(int decision) { this.decision = decision; } @Override public String toString() { 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 + '}'; } }




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