final FessAdminAction action = createAction();
        System.setProperty("fess.var.path", varDir.toString());
        assertThrows(IllegalArgumentException.class, () -> action.validateFilePath(varDir.toString() + "/subdir/../../.."));
    }

    // ===================================================================================
    //                                                              fess.var.path Tests

name: Submit Dependency Graph
on:
  workflow_dispatch:
  push:
    branches:
      - master

permissions: {}

jobs:
  generate-and-submit:
    permissions:
      contents: write
    runs-on: ubuntu-latest
    steps:
    - uses: actions/checkout@v6
    - uses: actions/setup-java@v5
      with:
        distribution: temurin
        java-version: 17
    - name: Setup Gradle

labels.key_match_title_details=Coincidencia de clave
labels.design_configuration=Diseño de página
labels.design_title_file_upload=Archivo a subir
labels.design_title_file=Administrador de archivos
labels.design_file=Subir archivo
labels.design_file_name=Nombre de archivo (opcional)
labels.design_button_upload=Subir
labels.design_file_title_edit=Ver archivo de página
labels.design_edit_button=Editar
labels.design_download_button=Descargar

## Why this policy exists

There is a fundamental **asymmetry** between submitting a contribution and reviewing one: AI tools make it easy to generate and submit large amounts of code, but they do not make it equally faster for us to review it. 
This policy protects our limited review budget, allowing us to invest our attention wisely.

        AtomicInteger totalDrained = new AtomicInteger(0);

        for (int t = 0; t < numThreads; t++) {
            final int threadId = t;
            executor.submit(() -> {
                try {
                    startLatch.await();
                    for (int i = 0; i < eventsPerThread; i++) {

If the **human effort** put in a PR, e.g. writing LLM prompts, is **less** than the **effort we would need to put** to **review it**, please **don't** submit the PR.

Think of it this way: we can already write LLM prompts or run automated tools ourselves, and that would be faster than reviewing external PRs.

### Closing Automated and AI PRs

                                        <la:message key="labels.crud_button_back"/>
                                    </la:link>
                                    <button type="submit" class="btn btn-success" name="create"
                                            value="<la:message key="labels.crud_button_create" />">
                                        <i class="fa fa-plus" aria-hidden="true"></i>

errors.app.db.already.updated = Mogło zostać już zaktualizowane przez inny proces. Spróbuj ponownie.
errors.app.db.already.exists = Dane już istnieją. Spróbuj ponownie.
errors.app.double.submit.request = To żądanie mogło zostać już przetworzone. Spróbuj ponownie.
# _/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/
# you can define your messages here:
# e.g.
# errors.xxx = ...

            .filter(s -> !s.isEmpty())
            .collect(Collectors.toList());
    }

    private static Future<String> readStreamAsync(InputStream inputStream) {
        return THREAD_POOL.submit((Callable<String>) () -> readFully(inputStream));
    }

    private static String readFully(InputStream inputStream) throws IOException {

 *       captured by any of the steps in the pipeline are closed.
 * </ol>
 *
 * <h3>Starting a pipeline</h3>
 *
 * Start a {@code ClosingFuture} pipeline {@linkplain #submit(ClosingCallable, Executor) from a
 * callable block} that may capture objects for later closing. To start a pipeline from a {@link
 * ListenableFuture} that doesn't create resources that should be closed later, you can use {@link