t.Skipf("can't open %q: %v", nonPollable, err)
		}
		t.Fatal(err)
	}
	f.Close()

	// On a Linux laptop, before the problem was fixed,
	// this test failed about 50% of the time with this
	// number of iterations.
	// It takes about 1/2 second when it passes.
	const attempts = 20000

	start := make(chan bool)
	var wg sync.WaitGroup
	wg.Add(1)
	defer wg.Wait()
	go func() {
		defer wg.Done()
		close(start)

	default:
		a2 = 0
	}

	// Since we are calculating with full words to avoid overflow,
	// we use 'even' to track the sign of the cosequences.
	// For even iterations: u0, v1 >= 0 && u1, v0 <= 0
	// For odd  iterations: u0, v1 <= 0 && u1, v0 >= 0
	// The first iteration starts with k=1 (odd).
	even = false
	// variables to track the cosequences
	u0, u1, u2 = 0, 1, 0
	v0, v1, v2 = 0, 0, 1

	pos token.Pos
	typ Type
}

func (check *Checker) monomorph() {
	// We detect unbounded instantiation cycles using a variant of
	// Bellman-Ford's algorithm. Namely, instead of always running |V|
	// iterations, we run until we either reach a fixed point or we've
	// found a path of length |V|. This allows us to terminate earlier
	// when there are no cycles, which should be the common case.

	again := true
	for again {

	pos syntax.Pos
	typ Type
}

func (check *Checker) monomorph() {
	// We detect unbounded instantiation cycles using a variant of
	// Bellman-Ford's algorithm. Namely, instead of always running |V|
	// iterations, we run until we either reach a fixed point or we've
	// found a path of length |V|. This allows us to terminate earlier
	// when there are no cycles, which should be the common case.

	again := true
	for again {

        kube::log::usage "'$0': argument to -p must be numeric and greater than 0"
        kube::test::usage
        exit 1
      fi
      ;;
    i)
      kube::log::usage "'$0': use GOFLAGS='-count <num-iterations>'"
      kube::test::usage
      exit 1
      ;;
    :)
      kube::log::usage "Option -${OPTARG} <value>"
      kube::test::usage
      exit 1
      ;;
    ?)
      kube::test::usage

			c = 0
			ng = nng
		}
		if c >= 100 {
			// The same value 100 times in a row is good enough.
			return ng
		}
		runtime.Gosched()
	}
	panic("failed to stabilize NumGoroutine after 1000 iterations")
}

func TestPullDoubleNext(t *testing.T) {
	next, _ := Pull(doDoubleNext())
	nextSlot = next
	next()
	if nextSlot != nil {
		t.Fatal("double next did not fail")
	}
}

	MOVD y+48(FP), R4	// R4 = y = c
	MOVD z_len+8(FP), R11	// R11 = z_len

	CMP   R11, $0		// If z_len is zero, return
	BEQ   done

	// We will process the first iteration out of the loop so we capture
	// the value of c. In the subsequent iterations, we will rely on the
	// value of CA set here.
	MOVD  0(R8), R20	// R20 = x[i]
	ADD   $-1, R11		// R11 = z_len - 1
	ADDC  R20, R4, R6	// R6 = x[i] + c

// true on iteration 0, 1, 2 respectively.  This is made more precise in the
// comment on the AndRecurrence class.
//
// The general algorithm that deals with cycles does two topological-order
// iterations over the graph.  On the first iteration it assigns a symbolic
// predicate to merge nodes with backedges.  On the second iteration it tries

                }
              },
              directExecutor());
      for (int i = 0; i < 50_000; i++) {
        if (i % DIRECT_EXECUTIONS_PER_THREAD == 0) {
          // after some number of iterations, switch threads
          unused =
              serializer.submit(
                  new Callable<@Nullable Void>() {
                    @Override
                    public @Nullable Void call() {

	}

	tries++ // tried already once

	// Wait on each try for an update.
	ticker := time.NewTicker(1 * time.Second)
	defer ticker.Stop()

	for {
		// Only log once every 10 iterations, then reset the tries count.
		verbose = tries >= 10
		if verbose {
			tries = 1
		}