import org.codelibs.fess.crawler.exception.ChildUrlsException;
import org.codelibs.fess.crawler.exception.CrawlerSystemException;
import org.codelibs.fess.crawler.processor.ResponseProcessor;
import org.codelibs.fess.crawler.processor.impl.DefaultResponseProcessor;
import org.codelibs.fess.crawler.rule.Rule;
import org.codelibs.fess.crawler.rule.RuleManager;
import org.codelibs.fess.crawler.serializer.DataSerializer;

        assertNull(result);
    }

    // Test convertBooleanQuery with null queryBuilder from processor
    public void test_convertBooleanQuery_withNullQueryBuilder() {
        // Create processor that returns null
        QueryProcessor nullProcessor = new QueryProcessor() {
            @Override

///

---

In this scenario of the parallel burgers, you are a computer / program 🤖 with two processors (you and your crush), both waiting 🕙 and dedicating their attention ⏯ to be "waiting on the counter" 🕙 for a long time.

The fast food store has 8 processors (cashiers/cooks). While the concurrent burgers store might have had only 2 (one cashier and one cook).

                }
            }
        }
        return true;
    }

    /**
     * Processes the response data using the appropriate rule processor.
     * @param urlQueue The URL queue entry.
     * @param responseData The response data to process.
     */
    protected void processResponse(final UrlQueue<?> urlQueue, final ResponseData responseData) {
        // get a rule

        return System.getProperty(TOMCAT_CONFIG_PATH);
    }

    /**
     * Sets up the web application context with Fess-specific configurations.
     * Configures the web resource root and cookie processor for the context.
     */
    @Override
    protected void setupWebappContext() {
        super.setupWebappContext();
        String contextPath = getContextPath();

import java.util.concurrent.CountDownLatch;
import java.util.concurrent.atomic.AtomicInteger;

import org.codelibs.fess.crawler.entity.ResponseData;
import org.codelibs.fess.crawler.processor.ResponseProcessor;
import org.dbflute.utflute.core.PlainTestCase;

/**
 * Test class for RuleManager interface.
 * Tests the contract and behavior of RuleManager implementations.
 */

        for (EventType type : EventType.values()) {
            eventCounters.put(type, new AtomicLong(0));
            eventTimings.put(type, new AtomicLong(0));
        }

        // Start async logging processor
        startAsyncProcessor();

        // Register shutdown hook
        Runtime.getRuntime().addShutdownHook(new Thread(this::shutdown));
    }

    private void startAsyncProcessor() {

        } catch (final Exception e) {
            throw new PluginException("Failed to access " + url, e);
        }
    }

    /**
     * Processes a Maven-style repository to extract artifacts of the specified type.
     *
     * @param artifactType the type of artifacts to process
     * @param url the URL of the repository
     * @return a list of artifacts found in the repository
     */

     *
     * @param params The search request parameters
     * @param cursor Function to process each document in the result set
     * @param userBean Optional user information for permission checking
     * @return Total number of documents processed
     */
    public long scrollSearch(final SearchRequestParams params, final BooleanFunction<Map<String, Object>> cursor,

As noted already, programmers are strongly encouraged to use appropriate synchronization
to avoid data races.
In the absence of data races, Go programs behave as if all the goroutines
were multiplexed onto a single processor.
This property is sometimes referred to as DRF-SC: data-race-free programs
execute in a sequentially consistent manner.
</p>

<p>
While programmers should write Go programs without data races,