* It is used to interrupt a running thread when a timeout occurs.
 * The class provides methods to interrupt the thread and stop the timeout target.
 *
 * <p>
 * The class uses a logger to log debug messages.
 * It also uses an AtomicBoolean to track whether the thread is running.
 * </p>
 *
 * <p>
 * The expired method is called when a timeout occurs.
 * It interrupts the running thread up to a maximum number of times.

research](https://scholar.google.com/scholar?q=gpu+side+channel) shows that it
might be possible to use side channel attacks on the GPU to leak data from other
running models or processes in the same system. GPUs can also have
implementation bugs that might allow attackers to leave malicious code running
and leak or tamper with applications from other users. Please report
vulnerabilities to the vendor of the affected hardware accelerator.

 */
public class MockWitnessService implements AutoCloseable {
    private static final Logger log = LoggerFactory.getLogger(MockWitnessService.class);

    private ServerSocket serverSocket;
    private final AtomicBoolean running = new AtomicBoolean(false);
    private final AtomicInteger registrationCounter = new AtomicInteger(0);
    private final ConcurrentHashMap<String, MockRegistration> registrations = new ConcurrentHashMap<>();

        }
        super.tearDown();
    }

    public void test_getStatus_returnsCorrectValue() {
        // Since we cannot easily create a real ClusterHealthResponse without a running cluster,
        // we'll test the class behavior through unit tests that verify the logic
        // The actual integration with ClusterHealthResponse is tested in integration tests

      matrix:
        pyver: ['3.9', '3.10', '3.11', '3.12']
    steps:
      - name: Stop old running containers (if any)
        shell: bash
        run: |
          running_containers=$(docker ps -q) && \
          if [[ $running_containers == "" ]]; then
            echo "No running containers";
          else
            echo "Running container(s) found" && \
            docker stop $running_containers;
          fi

                if (crawler1.crawlerContext.getStatus() == CrawlerStatus.RUNNING) {
                    break;
                }
                Thread.sleep(50);
            }
            assertEquals(CrawlerStatus.RUNNING, crawler1.crawlerContext.getStatus());
            for (int i = 0; i < 100; i++) {
                if (crawler2.crawlerContext.getStatus() == CrawlerStatus.RUNNING) {
                    break;
                }

    }

  /** Ready async calls in the order they'll be run. */
  private val readyAsyncCalls = ArrayDeque<AsyncCall>()

  /** Running asynchronous calls. Includes canceled calls that haven't finished yet. */
  private val runningAsyncCalls = ArrayDeque<AsyncCall>()

  /** Running synchronous calls. Includes canceled calls that haven't finished yet. */
  private val runningSyncCalls = ArrayDeque<RealCall>()

Just keep in mind that when you read "server" in general, it could refer to one of those two things.

When referring to the remote machine, it's common to call it **server**, but also **machine**, **VM** (virtual machine), **node**. Those all refer to some type of remote machine, normally running Linux, where you run programs.

    strategy:
      matrix:
        pyver: ['3.10']
    steps:
      - name: Stop old running containers (if any)
        shell: bash
        run: |
          running_containers=$(docker ps -q) && \
          if [[ $running_containers == "" ]]; then
            echo "No running containers";
          else
            echo "Running container(s) found" && \
            docker stop $running_containers;
          fi

package org.codelibs.fess.crawler;

/**
 * Enum representing the status of a crawler.
 * It can be INITIALIZING, RUNNING, or DONE.
 */
public enum CrawlerStatus {
    /**
     * The crawler is initializing.
     */
    INITIALIZING,

    /**
     * The crawler is currently running.
     */
    RUNNING,

    /**
     * The crawler has completed its task.
     */
    DONE;