"-s", "testuser2 private share;/testuser2;no;no;no;testuser2", //
                        "-s", "empty;/empty;no;no;no;testuser", //
                        "-s", "deep;/deep;no;no;no;testuser", //
                        "-s", "special;/special;no;no;no;testuser", //
                        "-g", "server min protocol = NT1", //
                        "-g", "log level = 3");

    <default>
      <key>package</key>
      <value>org.apache.maven.artifact.repository.metadata</value>
    </default>
  </defaults>
  <classes>
    <class rootElement="true" xml.tagName="metadata" java.clone="deep">
      <name>Metadata</name>
      <version>1.0.0+</version>
      <fields>
        <field xml.attribute="true" xml.tagName="modelVersion">
          <name>modelVersion</name>
          <version>1.1.0+</version>

    ]]>
  </description>
  <defaults>
    <default>
      <key>package</key>
      <value>org.apache.maven.settings</value>
    </default>
  </defaults>
  <classes>
    <class java.clone="deep">
      <name>TrackableBase</name>
      <version>1.0.0+</version>
      <description>
        Common base class that contains code to track the source for this instance.
      </description>
      <codeSegments>

{* ../../docs_src/path_params/tutorial005_py39.py hl[1,6:9] *}


/// tip | Tipp

Falls Sie sich fragen, was „AlexNet“, „ResNet“ und „LeNet“ ist, das sind Namen von <abbr title="Genau genommen, Deep-Learning-Modellarchitekturen">Modellen</abbr> für maschinelles Lernen.

///

### Einen *Pfad-Parameter* deklarieren { #declare-a-path-parameter }

    assertThat(reader.readLine()).isEqualTo("hello world")
    val request = server.takeRequest()
    assertThat(request.requestLine).isEqualTo(
      "GET /a/deep/path?key=foo%20bar HTTP/1.1",
    )
    assertThat(request.path).isEqualTo("/a/deep/path?key=foo%20bar")
    val requestUrl = request.requestUrl
    assertThat(requestUrl!!.scheme).isEqualTo("http")
    assertThat(requestUrl.host).isEqualTo(server.hostName)

        Path deepDir = publicDir.resolve("deep");
        Files.createDirectory(deepDir);
        Path currentDir = deepDir;
        for (int i = 1; i <= 5; i++) {
            currentDir = currentDir.resolve("level" + i);
            Files.createDirectory(currentDir);
        }
        Files.writeString(currentDir.resolve("deepfile.txt"), "deep content");

        // Zero byte file for test_zeroByteFile

	induce_bitrot "2" "/data"$((DATA_DRIVE + 1)) $FILE
	WANT='{ "before": { "color": "green", "missing": 0, "corrupted": 1 }, "after": { "color": "green", "missing": 0, "corrupted": 0 }, "args": {"file": "'${FILE}'", "dir": "'${DIR}'", "deep": true} }'
	verify_resiliency_healing "${FUNCNAME[0]}" "${WANT}"

	# Induce bitrot in two parts -- status becomes yellow (2 corrupted)
	induce_bitrot "2" "/data"$((DATA_DRIVE)) $FILE

* <abbr title="Eine Methode des Machine Learning, die künstliche neuronale Netze mit zahlreichen versteckten Schichten zwischen Eingabe- und Ausgabeschicht verwendet und so eine umfassende interne Struktur entwickelt">Deep Learning</abbr>

### Das abbr gibt eine vollständige Phrase und eine Erklärung { #the-abbr-gives-a-full-phrase-and-an-explanation }

{* ../../docs_src/path_params/tutorial005_py39.py hl[1,6:9] *}

/// tip | Consejo

Si te estás preguntando, "AlexNet", "ResNet" y "LeNet" son solo nombres de <abbr title="Técnicamente, arquitecturas de modelos de Deep Learning">modelos</abbr> de Machine Learning.

///

### Declarar un *path parameter* { #declare-a-path-parameter }

{* ../../docs_src/path_params/tutorial005_py39.py hl[1,6:9] *}

/// tip | Dica
Se você está se perguntando, "AlexNet", "ResNet" e "LeNet" são apenas nomes de <abbr title="Tecnicamente, arquiteturas de modelos de Deep Learning">modelos</abbr> de Aprendizado de Máquina.
///

### Declare um parâmetro de path { #declare-a-path-parameter }