"axisCenteredZero": false,
            "axisColorMode": "text",
            "axisLabel": "",
            "axisPlacement": "auto",
            "barAlignment": 0,
            "drawStyle": "line",
            "fillOpacity": 10,
            "gradientMode": "none",
            "hideFrom": {
              "legend": false,
              "tooltip": false,
              "viz": false
            },

            final String[] lines = value.split("[\r\n]");
            for (final String line : lines) {
                if (StringUtil.isNotBlank(line)) {
                    final int pos = line.indexOf('=');
                    if (pos == 0) {
                        paramMap.put("unknown." + (unknownKey + 1), line.substring(pos + 1).trim());
                        unknownKey++;
                    } else if (pos > 0) {

            }
        }

        /**
         * Writes a raw line to the temporary file.
         *
         * @param line The line to write.
         * @throws DictionaryException if an I/O error occurs.
         */
        public void write(final String line) {
            try {
                writer.write(line);
                writer.write(Constants.LINE_SEPARATOR);

            }
        }

        /**
         * Writes a line to the new file.
         *
         * @param line The line to write.
         */
        public void write(final String line) {
            try {
                writer.write(line);
                writer.write(Constants.LINE_SEPARATOR);
            } catch (final IOException e) {

 *
 * <p>Subclasses are guaranteed that the life cycle methods ({@link #runOneIteration}, {@link
 * #startUp} and {@link #shutDown}) will never run concurrently. Notably, if any execution of {@link
 * #runOneIteration} takes longer than its schedule defines, then subsequent executions may start
 * late. Also, all life cycle methods are executed with a lock held, so subclasses can safely modify

   * actual {@code y} values of the data and the values predicted by the fit for the {@code x}
   * values (i.e. it is the square root of the mean of the squares of the vertical distances between
   * the data points and the best fit line). For this fit, this error is a fraction {@code sqrt(1 -
   * R*R)} of the population standard deviation of {@code y}, where {@code R} is the Pearson's

                        eventCatapult.fire(ExecutionEvent.Type.ForkedProjectStarted, session, mojoExecution);

                        execute(session, mojoExecutions);

                        eventCatapult.fire(ExecutionEvent.Type.ForkedProjectSucceeded, session, mojoExecution);
                    } catch (LifecycleExecutionException e) {

        initCause(cause);
        this.lineNumber = lineNumber;
        this.columnNumber = columnNumber;
    }

    /**
     * Gets the one-based index of the line containing the error.
     *
     * @return The one-based index of the line containing the error or a non-positive value if unknown.
     */
    public int getLineNumber() {
        return lineNumber;
    }

    /**

    TimeoutFuture<V> result = new TimeoutFuture<>(delegate);
    Fire<V> fire = new Fire<>(result);
    result.timer = scheduledExecutor.schedule(fire, time, unit);
    delegate.addListener(fire, directExecutor());
    return result;
  }

  /*
   * Memory visibility of these fields. There are two cases to consider.
   *
   * 1. visibility of the writes to these fields to Fire.run:
   *

		skip, record bool
	)

	for s.Scan() {
		line := s.Text()
		switch {
		case skip && line != "":
		case skip && line == "":
			skip = false
		case record && line == "":
			stackTrace := bf.String()
			reset()
			record = false
			if searchRE == nil || searchRE.MatchString(stackTrace) {
				ret[t] = append(ret[t], stackTrace)
			}
		case record:
			save(line)
		default: