*   <li>Dynamic replanning when necessary (e.g., for forked executions)</li>
 *   <li>Project setup, execution, and teardown phases management</li>
 * </ol>
 *
 * <h2>Thread Management:</h2>
 * <p>The number of threads used is determined by:</p>
 * <pre>
 * min(degreeOfConcurrency, numberOfProjects)
 * </pre>
 * where degreeOfConcurrency is set via the -T command-line option.
 *

                }
              });
      thread.start();
      // we want to wait until each thread is WAITING - one thread waiting inside CacheLoader.load
      // (in startSignal.await()), and the others waiting for that thread's result.
      while (thread.isAlive() && thread.getState() != Thread.State.WAITING) {
        Thread.yield();
      }
    }
    gettersStartedSignal.countDown();

crawler.system.monitor.interval=60
# Whether to ignore idle threads in hot thread monitoring.
crawler.hotthread.ignore_idle_threads=true
# Interval for hot thread monitoring (e.g., 500ms).
crawler.hotthread.interval=500ms
# Number of snapshots for hot thread monitoring.
crawler.hotthread.snapshots=10
# Number of threads for hot thread monitoring.
crawler.hotthread.threads=3
# Timeout for hot thread monitoring (e.g., 30s).
crawler.hotthread.timeout=30s

                    throw new IllegalArgumentException("Invalid threads core multiplier value: '" + threadConfiguration
                            + "'. Value must be positive.");
                }

                int procs = Runtime.getRuntime().availableProcessors();
                int threads = (int) (coreMultiplier * procs);
                return threads == 0 ? 1 : threads;
            } else {

   * accommodate as many threads as will ever concurrently modify the table. Using a significantly
   * higher value than you need can waste space and time, and a significantly lower value can lead
   * to thread contention. But overestimates and underestimates within an order of magnitude do not
   * usually have much noticeable impact. A value of one permits only one thread to modify the cache

                if (attempt < 10) {
                    Thread.sleep(500); // First 10 attempts: 0.5 second intervals
                } else if (attempt < 30) {
                    Thread.sleep(1000); // Next 20 attempts: 1 second intervals
                } else {
                    Thread.sleep(2000); // Remaining attempts: 2 second intervals
                }
            }
        }

   * accommodate as many threads as will ever concurrently modify the table. Using a significantly
   * higher value than you need can waste space and time, and a significantly lower value can lead
   * to thread contention. But overestimates and underestimates within an order of magnitude do not
   * usually have much noticeable impact. A value of one permits only one thread to modify the cache

 *
 * OkHttp performs best when you create a single `OkHttpClient` instance and reuse it for all of
 * your HTTP calls. This is because each client holds its own connection pool and thread pools.
 * Reusing connections and threads reduces latency and saves memory. Conversely, creating a client
 * for each request wastes resources on idle pools.
 *
 * Use `new OkHttpClient()` to create a shared instance with the default settings:
 *

labels.includedDocPaths=Chemins inclus pour la recherche
labels.includedDocUrls=URL incluses pour la recherche
labels.maxAccessCount=Nombre d'accès maximum
labels.name=Nom
labels.numOfThread=Nombre de threads
labels.duplicateHostName=Nom d'hôte en double
labels.pageNumber=Numéro de page
labels.password=Mot de passe
labels.paths=Chemins
labels.port=Port
labels.regex=Expression régulière
labels.regularName=Nom régulier

    hand it off to another thread to write to it after `writeTo` returns.

    The `EventListener` may now see requests and responses interleaved in ways not previously
    permitted. For example, a listener may receive `responseHeadersStart()` followed by
    `requestBodyEnd()`, both on the same call. Such events may be triggered by different threads
    even for a single call.