public void test_convert() throws Exception {
        /*
         * TODO ReadingConverterChain chain = new ReadingConverterChain(); chain.addConverter(new KatakanaConverter());
         * chain.addConverter(new KatakanaToAlphabetConverter()); chain.init();
         *
         * List<String> list = chain.convert("検索"); assertTrue(list.contains("ケンサク"));
         * assertTrue(list.contains("kennsaku"));
         */
    }

            normalizer = new LangAnalyzerNormalizer(null);
        } else {
            final NormalizerChain chain = new NormalizerChain();
            for (final String lang : langs) {
                chain.add(new LangAnalyzerNormalizer(lang));
            }
            normalizer = chain;
        }
        return normalizer.normalize(text, field);
    }

    /**
     * Language-specific analyzer normalizer.

 * It applies each normalizer in the order they were added to the chain.
 *
 * <p>Usage example:</p>
 * <pre>
 * NormalizerChain chain = new NormalizerChain();
 * chain.add(new SomeNormalizer());
 * chain.add(new AnotherNormalizer());
 * String normalizedText = chain.normalize("input text", "field", "en");
 * </pre>
 *
 * <p>Methods:</p>
 * <ul>

        final ReadingConverterChain chain = new ReadingConverterChain();
        chain.addConverter(new AnalyzerConverter(client, settings));
        chain.addConverter(new KatakanaToAlphabetConverter());
        return chain;
    }

    /**
     * Creates a default ReadingConverterChain with a KatakanaToAlphabetConverter.
     *

    }

    protected ReadingConverter createDefaultReadingConverter() throws IOException {
        ReadingConverterChain chain = new ReadingConverterChain();
        // chain.addConverter(new KatakanaConverter());
        chain.addConverter(new KatakanaToAlphabetConverter());
        chain.init();
        return chain;
    }

    protected Normalizer createDefaultNormalizer() {
        // TODO
        return new NormalizerChain();

import java.util.List;
import java.util.Queue;

/**
 * A chain of {@link ReadingConverter} implementations that applies each converter in sequence to generate possible reading variations of a given text.
 * It maintains a list of ReadingConverter instances and iterates through them, applying each converter to the input text and accumulating the results.
 * The chain stops processing when the maximum number of readings is reached.
 */

            converter = new LangAnalyzerConverter(null);
        } else {
            final ReadingConverterChain chain = new ReadingConverterChain();
            for (final String lang : langs) {
                chain.addConverter(new LangAnalyzerConverter(lang));
            }
            converter = chain;
        }
        return converter.convert(text, field);
    }

    /**

        // Test that all methods return the builder instance for chaining
        String id = "chain-test";
        SuggestSettings settings = builder.setSettingsIndexName("CHAINED_INDEX")
                .addInitialSettings("chain.key1", "chainValue1")
                .addInitialSettings("chain.key2", "chainValue2")
                .scrollTimeout("11s")
                .searchTimeout("12s")

        assertEquals("concurrentRule", testRule.getRuleId());
        assertSame(processor, testRule.getResponseProcessor());
    }

    /**
     * Test rule chain with AbstractRule
     */
    public void test_ruleChain() {
        // Create chain of rules
        TestAbstractRule rule1 = new TestAbstractRule();
        rule1.crawlerContainer = container;
        rule1.setRuleId("rule1");

        assertEquals(threadCount * operationsPerThread, transformer.getGetDataCallCount());
    }

    /**
     * Test transformer chain
     */
    public void test_transformerChain() {
        // Create chain of transformers
        List<Transformer> transformerChain = new ArrayList<>();
        transformerChain.add(new TestTransformer("first"));