* @param is the input stream to analyze
     * @param filename the filename to help determine the content type
     * @return the detected content type
     */
    String getContentType(InputStream is, String filename);

    /**
     * Determines the content type of the given input stream using the provided parameters.
     * @param is the input stream to analyze

        assertTrue(analyzerNames.contains(settings.analyzer().getNormalizeAnalyzerName("", "")));

        for (final String lang : settings.analyzer().SUPPORTED_LANGUAGES) {
            assertTrue(analyzerNames.contains(settings.analyzer().getContentsAnalyzerName("", lang)));
            assertTrue(analyzerNames.contains(settings.analyzer().getContentsReadingAnalyzerName("", lang)));

  CodeQL-Build:
    permissions:
      actions: read  # for github/codeql-action/init to get workflow details
      contents: read  # for actions/checkout to fetch code
      security-events: write  # for github/codeql-action/analyze to upload SARIF results
    runs-on: ubuntu-latest

    strategy:
      fail-fast: false
      matrix:
        # Override automatic language detection by changing the below list

fi

# Note: the profile can be viewed by visiting chrome://tracing in a Chrome browser.
# See https://docs.bazel.build/versions/main/skylark/performance.html#performance-profiling

        this.defaultField = defaultField;
    }

    /**
     * Sets the analyzer used to analyze query terms.
     *
     * @param analyzer the analyzer to use
     */
    public void setAnalyzer(final Analyzer analyzer) {
        this.analyzer = analyzer;
    }

    /**
     * Sets whether to allow leading wildcards in query terms.
     *

            throw new ExtractException("Failed to parse CSV content", e);
        }
    }

    /**
     * Detects the delimiter character from a CSV line.
     *
     * @param line the CSV line to analyze
     * @return the detected delimiter character
     */
    protected Character detectDelimiter(final String line) {
        final char[] candidates = { ',', '\t', ';', '|' };
        int maxCount = 0;

    abstract val textReportFile: RegularFileProperty

    @get:Inject
    abstract val workerExecutor: WorkerExecutor

    @get:Inject
    abstract val layout: ProjectLayout

    @TaskAction
    fun analyze() = workerExecutor.processIsolation { classpath.from(additionalClasspath) }.submit(IncubatingApiReportWorkAction::class) {
        repositoryRoot = layout.settingsDirectory
        srcDirs.from(******@****.***s)

    /**
     * Indicates whether the model building should happen in two phases. If enabled, the initial invocation of the model
     * builder will only produce an interim result which may be used to analyze inter-model dependencies before the
     * final invocation of the model builder is performed.
     *
     * @return {@code true} if two-phase building is enabled, {@code false} if the model should be built in a single

        SuggestAnalyzer analyzer = suggester.settings().analyzer().new DefaultContentsAnalyzer();
        String text = "これはテストです。検索エンジン。";

        List<AnalyzeToken> tokens = defaultContentsParser.analyzeTextByReading(analyzer, "content", text, null);

        assertNotNull(tokens);
        // analyzeAndReading may return null for some analyzers
        // Just verify it doesn't throw an exception
    }

### Examples

Use American English spelling, for example:

* `color` (not `colour`)
* `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