Addresses: []string{"10.1.1.1"},
		}}
		eps.Ports = []discovery.EndpointPort{{
			Name:     ptr.To("p11"),
			Port:     ptr.To[int32](11),
			Protocol: ptr.To(v1.ProtocolUDP),
		}}
	}
	subset2 := func(eps *discovery.EndpointSlice) {
		eps.AddressType = discovery.AddressTypeIPv4
		eps.Endpoints = []discovery.Endpoint{{
			Addresses: []string{"10.1.1.2"},
		}}

        and:
        failure.assertHasDescription("Invalid version specified for argument '--gradle-version'")
        failure.assertHasCause("'$badVersion' is not a valid Gradle version string (examples: '1.0', '1.0-rc-1')")
        failure.assertHasResolution("Specify a valid Gradle release listed on https://gradle.org/releases/.")

	case AREMW, ASDIVW:
		return S32 | OPDP2(3)

	case ASMULL, ASMADDL:
		return OPDP3(1, 0, 1, 0)

	case ASMNEGL, ASMSUBL:
		return OPDP3(1, 0, 1, 1)

	case ASMULH:
		return OPDP3(1, 0, 2, 0)

	case AUMULL, AUMADDL:
		return OPDP3(1, 0, 5, 0)

	case AUMNEGL, AUMSUBL:
		return OPDP3(1, 0, 5, 1)

	case AUMULH:
		return OPDP3(1, 0, 6, 0)

	case AUREM, AUDIV:

	} else {
		s.version = uint16(rand.Intn(VersionTLS13))
	}
	s.isClient = rand.Intn(10) > 5
	s.cipherSuite = uint16(rand.Intn(math.MaxUint16))
	s.createdAt = uint64(rand.Int63())
	s.secret = randomBytes(rand.Intn(100)+1, rand)
	for n, i := rand.Intn(3), 0; i < n; i++ {
		s.Extra = append(s.Extra, randomBytes(rand.Intn(100), rand))
	}
	if rand.Intn(10) > 5 {
		s.EarlyData = true
	}
	if rand.Intn(10) > 5 {

array with a utility function" suppressId="manual_array_contains" problemDescriptor="Replace manual array-contains check with utility function" text="for ($TYPE$ $ITEM$ : $ARR$) {
    if ($ITEM$.equals($TARGET$)) {
       return $RES$;
    }
}" recursive="false" caseInsensitive="false" type="JAVA" pattern_context="default" reformatAccordingToStyle="true" shortenFQN="true" useStaticImport="true" replacement="if (org.gradle.util.internal.ArrayUtils.contains($ARR$, $TARGET$)) {
 ...

    %0 = stablehlo.convolution(%arg0, %arg1) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {pad = [[0, 1], [1, 1]]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x3x4x3xf32>, tensor<2x3x3x2xf32>) -> tensor<1x3x4x2xf32>
    return %0 : tensor<1x3x4x2xf32>
  }
}

// CHECK-LABEL: quantize_conv_fn

        0 * spec.lineInFileLocation(_, _)
        0 * spec.lineInFileLocation(_, _, _)
        1 * spec.lineInFileLocation("SomeFile.java", 1, 1, 10)
        1 * spec.offsetInFileLocation("SomeFile.java", 10, 10)
    }

// converting TensorFlow op attributes to HLO op attributes.
//
// Sample result for Conv2D:
//
//   %conv = "mhlo.convolution"(%input, %filter) {
//     strides = [1, 2],
//     paddings = [[1, 0], [1, 1]],
//     ...
//   }
//
// This pattern is not defined using declarative rewrite rules as computation of
// the paddings attribute anyway requires multiple source op attributes and

	_ = make([]int, 0, - /* ERROR "must not be negative" */ 1)
	_ = make([]int, - /* ERROR "must not be negative" */ 1, - /* ERROR "must not be negative" */ 1)
	_ = make([]int, 1 /* ERROR "overflows" */ <<100, 1 /* ERROR "overflows" */ <<100)
	_ = make([]int, 10 /* ERROR "length and capacity swapped" */ , 9)
	_ = make([]int, 1 /* ERROR "overflows" */ <<100, 12345)
	_ = make([]int, m /* ERROR "must be integer" */ )

//  1. Perform SetCookies with fromURL and the cookies from setCookies.
//     (Done at time tNow + 0 ms.)
//  2. Check that the entries in the jar matches content.
//     (Done at time tNow + 1001 ms.)
//  3. For each query in tests: Check that Cookies with toURL yields the
//     cookies in want.
//     (Query n done at tNow + (n+2)*1001 ms.)
type jarTest struct {