}
	if start < len(s) {
		dst.WriteString(s[start:])
	}
}

// htmlSafeSet holds the value true if the ASCII character with the given
// array position can be safely represented inside a JSON string, embedded
// inside of HTML <script> tags, without any additional escaping.
//
// All values are true except for the ASCII control characters (0-31), the
// double quote ("), the backslash character ("\"), HTML opening and closing

    String ROLE = Mojo.class.getName();

    /**
     * Perform whatever build-process behavior this <code>Mojo</code> implements.<br>
     * This is the main trigger for the <code>Mojo</code> inside the <code>Maven</code> system, and allows
     * the <code>Mojo</code> to communicate errors.
     *
     * @throws MojoExecutionException if an unexpected problem occurs.

The contents that you return from your *path operation function* will be put inside of that `Response`.

  parser = argparse.ArgumentParser(
      description='Extracts ResultStore links from a build log.\n'
                  'These can be then printed out, and/or output into a '
                  'JUnit-based XML file inside a specified directory.')

  parser.add_argument('build_log',
                      help='Path to a build log.')
  parser.add_argument('--xml-out-path',
                      required=False,

# for verifying changes to the TFCI scripts system, and most users won't need
# to interact with it at all.
source "${BASH_SOURCE%/*}/utilities/setup.sh"

echo "==TFCI== env outside of tfrun:"
env
echo "==TFCI== env inside of tfrun:"

        if (tagNo == 0x1f)
        {
            int b = s.read();
            if (b < 31)
            {
                if (b < 0)
                {
                    throw new EOFException("EOF found inside tag value.");
                }
                throw new IOException("corrupted stream - high tag number < 31 found");
            }

            tagNo = b & 0x7f;

            // X.690-0207 8.1.2.4.2

Since models are practically programs that TensorFlow executes, using untrusted
models or graphs is equivalent to running untrusted code.

If you need to run untrusted models, execute them inside a
[**sandbox**](https://developers.google.com/code-sandboxing). Memory corruptions
in TensorFlow ops can be recognized as security issues only if they are
reachable and exploitable through production-grade, benign models.

# Docker on Windows has difficulty using volumes other than C:\, when it comes
# to setting up up volume mappings.
# Thus, the drive letter is replaced with C:\, in case it's
# something else (ex. T:), which is frequently the case inside Kokoro jobs.
function replace_drive_letter_with_c () {
  sed -E "s|^[a-zA-Z]:|C:|g" <<< $1

* Eclipse IDE tooling for plugin execution model and metadata model

- we also seem to have information like the plugin lifecycle model that's buried inside the maven execution model
- we also seem to have artifact information tangled inside the plugin model
- we have to deal with scripting implementations (groovy, beanshell, ruby)
- we need to deal with a shared context for plugins, like the guarded mojos

	Read(dst sql.Record) (sql.Record, error)
	Close() error
}

const (
	csvFormat     = "csv"
	jsonFormat    = "json"
	parquetFormat = "parquet"
)

// CompressionType - represents value inside <CompressionType/> in request XML.
type CompressionType string

const (
	noneType  CompressionType = "none"
	gzipType  CompressionType = "GZIP"
	bzip2Type CompressionType = "BZIP2"