name: docs

on:
  push:
    branches:
      - master
  pull_request:
    types: [opened, labeled, unlabeled, synchronize]

permissions:
  contents: read

env:
  GRADLE_OPTS: "-Dorg.gradle.jvmargs=-Xmx4g -Dorg.gradle.daemon=false -Dkotlin.incremental=false"

jobs:
  test_docs:
    permissions:
      checks: write # for actions/upload-artifact
    runs-on: ubuntu-latest

* `initialize` (not `initialise`)
* `behavior` (not `behaviour`)
* `analyze` (not `analyse`)
* `organization` (not `organisation`)
* `center` (not `centre`)
* `canceled` (not `cancelled`)
* `labeled` (not `labelled`)

### Rationale for American English

American English was chosen for the following reasons:

* **Current predominance**: The majority of existing Gradle code and documentation already uses American English

name: build

on:
  push:
    branches:
      - master
  pull_request:
    types: [opened, labeled, unlabeled, synchronize]

permissions:
  contents: read

env:
  GRADLE_OPTS: "-Xmx4g -Dorg.gradle.daemon=false -Dkotlin.incremental=false"

concurrency:
  group: ${{ github.workflow }}-${{ github.ref }}
  cancel-in-progress: true

jobs:
  publish:
    runs-on: ubuntu-latest

labels.facet_contentLength_1m=content_length:[1000000 TO *]\n\
labels.facet_filetype_title:\
labels.facet_filetype_html=filetype:html\t\
labels.facet_filetype_word=filetype:word\t\
labels.facet_filetype_excel=filetype:excel\t\
labels.facet_filetype_powerpoint=filetype:powerpoint\t\
labels.facet_filetype_odt=filetype:odt\t\
labels.facet_filetype_ods=filetype:ods\t\
labels.facet_filetype_odp=filetype:odp\t\

</p>

<pre class="ebnf">
EmptyStmt = .
</pre>


<h3 id="Labeled_statements">Labeled statements</h3>

<p>
A labeled statement may be the target of a <code>goto</code>,
<code>break</code> or <code>continue</code> statement.
</p>

<pre class="ebnf">
LabeledStmt = Label ":" Statement .
Label       = identifier .
</pre>

<pre>
Error: log.Panic("error encountered")
</pre>

        // Verify labels are merged
        String[] labels = (String[]) dataMap.get("label");
        assertEquals(3, labels.length);
        Set<String> labelSet = new HashSet<>();
        for (String label : labels) {
            labelSet.add(label);
        }
        assertTrue(labelSet.contains("existing"));
        assertTrue(labelSet.contains("label1"));
        assertTrue(labelSet.contains("label2"));

        to a labeled dataset, in one function call. Note that it doesn't perform
        image data augmentation (which is meant to be done using preprocessing
        layers).
    *   **[`text_dataset_from_directory`](https://www.tensorflow.org/api_docs/python/tf/keras/preprocessing/text_dataset_from_directory)**
        takes you from a structured directory of text files to a labeled
        dataset, in one function call.

     * labels.facet_filetype_title:labels.facet_filetype_html=filetype:html	labels.facet_filetype_word=filetype:word	labels.facet_filetype_excel=filetype:excel	labels.facet_filetype_powerpoint=filetype:powerpoint	labels.facet_filetype_odt=filetype:odt	labels.facet_filetype_ods=filetype:ods	labels.facet_filet...

                    labels.add("label1");
                    labels.add("label2");
                }
                return labels;
            }
        };
        ComponentUtil.register(mockLabelTypeHelper, "labelTypeHelper");

        // Mock LanguageHelper
        LanguageHelper mockLanguageHelper = new LanguageHelper() {
            @Override
            public Script createScript(Map<String, Object> doc, String scriptString) {

  private int compareLabel(String label, int offset) {
    int labelLen = label.length();
    int nodeLabelLen = stringPool.charAt(offset);
    int minLen = Math.min(nodeLabelLen, labelLen);
    for (int i = 0; i < minLen; i++) {
      char c1 = label.charAt(i);
      char c2 = stringPool.charAt(offset + 1 + i);
      if (c1 != c2) {
        return c1 - c2;
      }
    }
    return labelLen - nodeLabelLen;
  }

  /**