// Start crawling
        crawlerContext.setStatus(CrawlerStatus.RUNNING);
        crawlerContext.setActiveThreadCount(5);

        // Simulate crawling progress
        for (int i = 0; i < 100; i++) {
            crawlerContext.incrementAndGetAccessCount();
            crawlerContext.getRobotsTxtUrlSet().add("http://site" + i + ".com/robots.txt");
        }

                readings.add(text.toUpperCase());
            } else {
                for (String lang : langs) {
                    if (japaneseMode && "ja".equals(lang)) {
                        // Simulate Japanese conversion
                        if ("東京".equals(text)) {
                            readings.add("トウキョウ");
                        } else {

            return null;
        }
    }

    /**
     * Test state transitions (typical workflow)
     */
    public void test_stateTransitions() {
        // Simulate typical crawler lifecycle
        CrawlerStatus currentStatus = CrawlerStatus.INITIALIZING;
        assertEquals(CrawlerStatus.INITIALIZING, currentStatus);

        // Transition to RUNNING

                if (token instanceof TestAnalyzeToken) {
                    TestAnalyzeToken testToken = (TestAnalyzeToken) token;
                    if (japaneseMode && "ja".equals(lang)) {
                        // Simulate Japanese reading conversion
                        testToken.setReading(convertToJapaneseReading(testToken.getTerm()));
                    } else {
                        // Default: uppercase for reading

        transformer.addTransformationRule("<[^>]+>", ""); // Remove HTML tags
        transformer.addTransformationRule("\\s+", " "); // Normalize whitespace

        // Simulate crawling response
        ResponseData responseData = new ResponseData();
        responseData.setUrl("http://example.com/page.html");
        responseData.setParentUrl("http://example.com/");

*   `tf.lite`:

    *   `tf.quantization.quantize_and_dequantize_v2` has been introduced, which
        updates the gradient definition for quantization which is outside the
        range to be 0. To simulate the V1 the behavior of
        `tf.quantization.quantize_and_dequantize(...)` use
        `tf.grad_pass_through(tf.quantization.quantize_and_dequantize_v2)(...)`.

*   Building TensorFlow: