var rangePanicError = error(errorString("range function continued iteration after loop body panic"))
var rangeExhaustedError = error(errorString("range function continued iteration after whole loop exit"))
var rangeMissingPanicError = error(errorString("range function recovered a loop body panic and did not resume panicking"))

//go:noinline

	loop := body                       // target of back-edge
	if s.Cond != nil {
		loop = b.newBlock(KindForLoop, s)
	}
	cont := loop // target of 'continue'
	if s.Post != nil {
		cont = b.newBlock(KindForPost, s)
	}
	if label != nil {
		label._break = done
		label._continue = cont
	}
	b.jump(loop)
	b.current = loop
	if loop != body {
		b.add(s.Cond)

# flood reviews with unnecessary requests to demonstrate Istio rate limiting


def floodReviews(product_id, headers):
    loop = asyncio.new_event_loop()
    loop.run_until_complete(floodReviewsAsynchronously(product_id, headers))
    loop.close()


@app.route('/productpage')
def front():
    product_id = 0  # TODO: replace default value
    headers = getForwardHeaders(request)

	CMP   R5, $0
	MOVD  R5, CTR         // Set up loop counter
	BEQ   tail            // If R5 = 0, we can't use the loop

	// Process 4 elements per iteration. Unrolling this loop
	// means a performance trade-off: we will lose performance
	// for small values of z_len (0.90x in the worst case), but
	// gain significant performance as z_len increases (up to
	// 1.45x).

	PCALIGN $16
loop:
	MOVD  8(R8), R11      // R11 = x[i]

  for (const NodeMatcherProperties& prop : props) {
    if (prop.name()) {
      DCHECK(!matcher->name);
      matcher->name = prop.name();
    }

    if (prop.op()) {
      DCHECK(!matcher->op);
      matcher->op = prop.op();
    }

    if (prop.constant_value()) {
      DCHECK(!matcher->constant_value);
      matcher->constant_value = prop.constant_value();
    }

  "tf_saved_model.session_initializer"() {initializers = [@NoOp]} : () -> ()
  func.func @NoOp() attributes {tf_saved_model.exported_names = ["__tf_saved_model_session_initializer_NoOp"]} {
    func.return
  }
// CHECK: func @NoOp() attributes {tf_saved_model.exported_names = ["__tf_saved_model_session_initializer_NoOp"]}

			}
		} else {
			idx = globalEndpoints.GetPoolIdx(pool)
			if idx == -1 {
				// We didn't find any matching pools, invalid input
				writeErrorResponseJSON(ctx, w, toAdminAPIErr(ctx, errInvalidArgument), r.URL)
				return
			}
		}
		var pool *erasureSets
		for pidx := range z.serverPools {
			if pidx == idx {
				pool = z.serverPools[idx]
				break
			}
		}
		if pool == nil {

		return nodes[i].Host < nodes[j].Host
	})
	return
}

// GetPoolIdx return pool index
func (l EndpointServerPools) GetPoolIdx(pool string) int {
	for id, ep := range globalEndpoints {
		if ep.CmdLine != pool {
			continue
		}
		return id
	}
	return -1
}

// GetLocalPoolIdx returns the pool which endpoint belongs to locally.
// if ep is remote this code will return -1 poolIndex

}

func (m *machine) init(ncap int) {
	for _, t := range m.pool {
		t.cap = t.cap[:ncap]
	}
	m.matchcap = m.matchcap[:ncap]
}

// alloc allocates a new thread with the given instruction.
// It uses the free pool if possible.
func (m *machine) alloc(i *syntax.Inst) *thread {
	var t *thread
	if n := len(m.pool); n > 0 {
		t = m.pool[n-1]
		m.pool = m.pool[:n-1]
	} else {
		t = new(thread)

            it.parameters.prop = "value 1"
        }
        def parameters = registry.registrations.getByName("service").parameters
        def service = provider.get()

        when:
        parameters.prop = "ignore me 1"

        then:
        service.prop == "value 1"

        when:
        service.parameters.prop = "ignore me 2"

        then: