}

	// NOTE: last option wins, so order in the list is important!

	// Start by getting the defaults.
	retryOpts := DefaultCallRetryOptions()

	// Don't use converge unless we need it. When sending large batches of requests (for example,
	// when we attempt to reach all clusters), converging will result in sending at least
	// `converge * count` requests. When running multiple requests in parallel, this can contribute

	// again. Any downloads that already succeeded will still be in cache.
	// That won't give optimal concurrency (we'll do two batches of concurrent
	// downloads instead of all in one batch), and it might add a little overhead
	// to look up the downloads from the first batch in the module cache when
	// we see them again in the second batch. On the other hand, it's way simpler
	// to implement, and not really any more expensive if the user is requesting

//
// It groups the calls into batches, starting with a group of initialBatchSize.
// Within each batch, it may call the function multiple times concurrently.
//
// If a whole batch succeeds, the next batch may get exponentially larger.
// If there are any failures in a batch, all remaining batches are skipped
// after waiting for the current batch to complete.
//

    /** True if either side has cleanly shut down this stream. We shall send no more bytes. */
    var finished: Boolean = false,
  ) : Sink {
    /**
     * Buffer of outgoing data. This batches writes of small writes into this sink as larges frames
     * written to the outgoing connection. Batching saves the (small) framing overhead.
     */
    private val sendBuffer = Buffer()

// after an object is no longer referenced, the runtime is allowed to perform
// a space-saving optimization that batches objects together in a single
// allocation slot. The finalizer for an unreferenced object in such an
// allocation may never run if it always exists in the same batch as a
// referenced object. Typically, this batching only happens for tiny
// (on the order of 16 bytes or less) and pointer-free objects.
//

	ExpectationsTimeout = 5 * time.Minute
	// When batching pod creates, SlowStartInitialBatchSize is the size of the
	// initial batch.  The size of each successive batch is twice the size of
	// the previous batch.  For example, for a value of 1, batch sizes would be
	// 1, 2, 4, 8, ...  and for a value of 10, batch sizes would be
	// 10, 20, 40, 80, ...  Setting the value higher means that quota denials

const oldQuantum = 1

func (t *LineTable) parse(targetPC uint64, targetLine int) (b []byte, pc uint64, line int) {
	// The PC/line table can be thought of as a sequence of
	//  <pc update>* <line update>
	// batches. Each update batch results in a (pc, line) pair,
	// where line applies to every PC from pc up to but not
	// including the pc of the next pair.
	//
	// Here we process each update individually, which simplifies

        addToGraphAndPopulate([c, d])

        then:
        executes(a, b, c, d)

        where:
        orderingRule << ['mustRunAfter', 'shouldRunAfter']
    }

    def "common tasks in separate batches are schedules only once"() {
        Task a = task("a")
        Task b = task("b")
        Task c = task("c", dependsOn: [a, b])
        Task d = task("d")
        Task e = task("e", dependsOn: [b, d])

				continue
			}
			b.URL(defaultHttpGetAttempts, url)
		default:
			matches, err := expandIfFilePattern(s)
			if err != nil {
				b.errs = append(b.errs, err)
				continue
			}
			if !recursive && len(matches) == 1 {
				b.singleItemImplied = true
			}
			b.Path(recursive, matches...)
		}
	}
	if filenameOptions.Kustomize != "" {
		b.paths = append(
			b.paths,

		// single span is in general a very fast operation, taking as little as 30 ns
		// on modern hardware. (See #54767.)
		//
		// As a result, bgsweep sweeps in batches, and only calls into the scheduler
		// at the end of every batch. Furthermore, it only yields its time if there
		// isn't spare idle time available on other cores. If there's available idle