diff --git a/atrace/1.0/default/AtraceDevice.cpp b/atrace/1.0/default/AtraceDevice.cpp
index 35d11e9..4e82b0a 100644
--- a/atrace/1.0/default/AtraceDevice.cpp
+++ b/atrace/1.0/default/AtraceDevice.cpp
@@ -94,7 +94,7 @@
     for (auto& c : kTracingMap) {
         for (auto& p : c.second.paths) {
             if (!android::base::WriteStringToFile("0", p.first)) {
-                LOG(ERROR) << "Failed to enable tracing on: " << p.first;
+                LOG(ERROR) << "Failed to disable tracing on: " << p.first;
                 if (p.second) {
                     ret = Status::ERROR_TRACING_POINT;
                 }
diff --git a/current.txt b/current.txt
index cea2bed..e717b7a 100644
--- a/current.txt
+++ b/current.txt
@@ -399,8 +399,8 @@
 65a021fa89085b62fc96b2b6d3bef2f9103cf4d63379c68bc154fd9eef672852 android.hardware.health@1.0::types
 b7ecf29927055ec422ec44bf776223f07d79ad9f92ccf9becf167e62c2607e7a android.hardware.keymaster@4.0::IKeymasterDevice
 574e8f1499436fb4075894dcae0b36682427956ecb114f17f1fe22d116a83c6b android.hardware.neuralnetworks@1.0::IPreparedModel
-567de4ebb3a224721eabae40c4484fad2cd1608eb0e66ec9214eb88e9b15d3c9 android.hardware.neuralnetworks@1.0::types
-d51937a3567a50f239589e40300264c4b57f2c3582c6fc6df082f45eb74d90e3 android.hardware.neuralnetworks@1.1::types
+e75759b40a1c5f97b463b30aab91954012c9ea9e454dde308db853a56796e5a6 android.hardware.neuralnetworks@1.0::types
+eb754b58c93e5591613208b4c972811288b0fa16a82430d602f107c91a908b22 android.hardware.neuralnetworks@1.1::types
 1d4a5776614c08b5d794a5ec5ab04697260cbd4b3441d5935cd53ee71d19da02 android.hardware.radio@1.0::IRadioResponse
 ed9da80ec0c96991fd03f0a46107815d0e50f764656e49dba4980fa5c31d5bc3 android.hardware.radio@1.0::types
 1d19720d4fd38b1095f0f555a4bd92b3b12c9b1d0f560b0e9a474cd6dcc20db6 android.hardware.radio@1.2::IRadio
@@ -451,7 +451,7 @@
 92714960d1a53fc2ec557302b41c7cc93d2636d8364a44bd0f85be0c92927ff8 android.hardware.neuralnetworks@1.2::IExecutionCallback
 36e1064c869965dee533c537cefbe87e54db8bd8cd45be7e0e93e00e8a43863a android.hardware.neuralnetworks@1.2::IPreparedModel
 e1c734d1545e1a4ae749ff1dd9704a8e594c59aea7c8363159dc258e93e0df3b android.hardware.neuralnetworks@1.2::IPreparedModelCallback
-51725cd8541bf459190d8a911f9aae9a0825678256b88fc39fac81d69feb04af android.hardware.neuralnetworks@1.2::types
+e3b6176e3bf235c4e0e4e451b0166e396c7ee176cfe167c9147c3d46d7b34f0c android.hardware.neuralnetworks@1.2::types
 cf7a4ba516a638f9b82a249c91fb603042c2d9ca43fd5aad9cf6c0401ed2a5d7 android.hardware.nfc@1.2::INfc
 abf98c2ae08bf765db54edc8068e36d52eb558cff6706b6fd7c18c65a1f3fc18 android.hardware.nfc@1.2::types
 4cb252dc6372a874aef666b92a6e9529915aa187521a700f0789065c3c702ead android.hardware.power.stats@1.0::IPowerStats
diff --git a/keymaster/4.0/vts/functional/VerificationTokenTest.cpp b/keymaster/4.0/vts/functional/VerificationTokenTest.cpp
index 3876b16..de28683 100644
--- a/keymaster/4.0/vts/functional/VerificationTokenTest.cpp
+++ b/keymaster/4.0/vts/functional/VerificationTokenTest.cpp
@@ -124,6 +124,65 @@
     // report if times aren't nearly always <1ms apart.
     EXPECT_LE(host_time_delta, km_time_delta + 2);
     EXPECT_LE(km_time_delta, host_time_delta + 2);
+    ASSERT_EQ(result1.token.mac.size(), result2.token.mac.size());
+    ASSERT_NE(0,
+              memcmp(result1.token.mac.data(), result2.token.mac.data(), result1.token.mac.size()));
+}
+
+/*
+ * Test that the mac changes when the time stamp changes. This is does not guarantee that the time
+ * stamp is included in the mac but on failure we know that it is not. Other than in the test
+ * case above we call verifyAuthorization with the exact same set of parameters.
+ */
+TEST_F(VerificationTokenTest, MacChangesOnChangingTimestamp) {
+    auto result1 =
+            verifyAuthorization(0 /* operation handle */,
+                                AuthorizationSet() /* paramtersToVerify */, HardwareAuthToken());
+    ASSERT_TRUE(result1.callSuccessful);
+    auto result1_time = getTime();
+
+    if (SecLevel() == SecurityLevel::STRONGBOX) {
+        // StrongBox should not implement verifyAuthorization.
+        EXPECT_EQ(ErrorCode::UNIMPLEMENTED, result1.error);
+        return;
+    }
+
+    EXPECT_EQ(ErrorCode::OK, result1.error);
+    EXPECT_EQ(0U, result1.token.challenge);
+    EXPECT_EQ(SecLevel(), result1.token.securityLevel);
+    EXPECT_EQ(0U, result1.token.parametersVerified.size())
+            << "We didn't supply any parameters to verify";
+    EXPECT_GT(result1.token.timestamp, 0U);
+
+    constexpr uint32_t time_to_sleep = 200;
+    sleep_ms(time_to_sleep);
+
+    auto result2 =
+            verifyAuthorization(0 /* operation handle */,
+                                AuthorizationSet() /* paramtersToVerify */, HardwareAuthToken());
+    ASSERT_TRUE(result2.callSuccessful);
+    auto result2_time = getTime();
+    EXPECT_EQ(ErrorCode::OK, result2.error);
+    EXPECT_EQ(0U, result2.token.challenge);
+    EXPECT_EQ(SecLevel(), result2.token.securityLevel);
+    EXPECT_EQ(0U, result2.token.parametersVerified.size())
+            << "We didn't supply any parameters to verify";
+
+    auto host_time_delta = result2_time - result1_time;
+
+    EXPECT_GE(host_time_delta, time_to_sleep)
+            << "We slept for " << time_to_sleep << " ms, the clock must have advanced by that much";
+    EXPECT_LE(host_time_delta, time_to_sleep + 20)
+            << "The verifyAuthorization call took " << (host_time_delta - time_to_sleep)
+            << " ms?  That's awful!";
+
+    auto km_time_delta = result2.token.timestamp - result1.token.timestamp;
+
+    EXPECT_LE(host_time_delta, km_time_delta + 2);
+    EXPECT_LE(km_time_delta, host_time_delta + 2);
+    ASSERT_EQ(result1.token.mac.size(), result2.token.mac.size());
+    ASSERT_NE(0,
+              memcmp(result1.token.mac.data(), result2.token.mac.data(), result1.token.mac.size()));
 }
 
 }  // namespace test
diff --git a/neuralnetworks/1.0/types.hal b/neuralnetworks/1.0/types.hal
index a358946..b0a1c1a 100644
--- a/neuralnetworks/1.0/types.hal
+++ b/neuralnetworks/1.0/types.hal
@@ -1225,9 +1225,9 @@
      * * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
      *      the input.
      * * 1: An {@link OperandType::INT32} scalar, specifying the output
-     *      height of the output tensor.
-     * * 2: An {@link OperandType::INT32} scalar, specifying the output
      *      width of the output tensor.
+     * * 2: An {@link OperandType::INT32} scalar, specifying the output
+     *      height of the output tensor.
      *
      * Outputs:
      * * 0: The output 4-D tensor, of shape
diff --git a/neuralnetworks/1.0/vts/functional/ValidateRequest.cpp b/neuralnetworks/1.0/vts/functional/ValidateRequest.cpp
index 72a5007..f0c93b7 100644
--- a/neuralnetworks/1.0/vts/functional/ValidateRequest.cpp
+++ b/neuralnetworks/1.0/vts/functional/ValidateRequest.cpp
@@ -34,7 +34,6 @@
 namespace functional {
 
 using ::android::hardware::neuralnetworks::V1_2::implementation::ExecutionCallback;
-using ::android::hardware::neuralnetworks::V1_2::implementation::PreparedModelCallback;
 using ::android::hidl::memory::V1_0::IMemory;
 using test_helper::for_all;
 using test_helper::MixedTyped;
@@ -42,53 +41,6 @@
 
 ///////////////////////// UTILITY FUNCTIONS /////////////////////////
 
-static void createPreparedModel(const sp<IDevice>& device, const V1_0::Model& model,
-                                sp<IPreparedModel>* preparedModel) {
-    ASSERT_NE(nullptr, preparedModel);
-
-    // see if service can handle model
-    bool fullySupportsModel = false;
-    Return<void> supportedOpsLaunchStatus = device->getSupportedOperations(
-        model, [&fullySupportsModel](ErrorStatus status, const hidl_vec<bool>& supported) {
-            ASSERT_EQ(ErrorStatus::NONE, status);
-            ASSERT_NE(0ul, supported.size());
-            fullySupportsModel =
-                std::all_of(supported.begin(), supported.end(), [](bool valid) { return valid; });
-        });
-    ASSERT_TRUE(supportedOpsLaunchStatus.isOk());
-
-    // launch prepare model
-    sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
-    ASSERT_NE(nullptr, preparedModelCallback.get());
-    Return<ErrorStatus> prepareLaunchStatus = device->prepareModel(model, preparedModelCallback);
-    ASSERT_TRUE(prepareLaunchStatus.isOk());
-    ASSERT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(prepareLaunchStatus));
-
-    // retrieve prepared model
-    preparedModelCallback->wait();
-    ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
-    *preparedModel = preparedModelCallback->getPreparedModel();
-
-    // The getSupportedOperations call returns a list of operations that are
-    // guaranteed not to fail if prepareModel is called, and
-    // 'fullySupportsModel' is true i.f.f. the entire model is guaranteed.
-    // If a driver has any doubt that it can prepare an operation, it must
-    // return false. So here, if a driver isn't sure if it can support an
-    // operation, but reports that it successfully prepared the model, the test
-    // can continue.
-    if (!fullySupportsModel && prepareReturnStatus != ErrorStatus::NONE) {
-        ASSERT_EQ(nullptr, preparedModel->get());
-        LOG(INFO) << "NN VTS: Unable to test Request validation because vendor service cannot "
-                     "prepare model that it does not support.";
-        std::cout << "[          ]   Unable to test Request validation because vendor service "
-                     "cannot prepare model that it does not support."
-                  << std::endl;
-        return;
-    }
-    ASSERT_EQ(ErrorStatus::NONE, prepareReturnStatus);
-    ASSERT_NE(nullptr, preparedModel->get());
-}
-
 // Primary validation function. This function will take a valid request, apply a
 // mutation to it to invalidate the request, then pass it to interface calls
 // that use the request. Note that the request here is passed by value, and any
@@ -237,15 +189,8 @@
     return requests;
 }
 
-void ValidationTest::validateRequests(const V1_0::Model& model,
+void ValidationTest::validateRequests(const sp<IPreparedModel>& preparedModel,
                                       const std::vector<Request>& requests) {
-    // create IPreparedModel
-    sp<IPreparedModel> preparedModel;
-    ASSERT_NO_FATAL_FAILURE(createPreparedModel(device, model, &preparedModel));
-    if (preparedModel == nullptr) {
-        return;
-    }
-
     // validate each request
     for (const Request& request : requests) {
         removeInputTest(preparedModel, request);
diff --git a/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.cpp b/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.cpp
index 8883057..aee2f85 100644
--- a/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.cpp
+++ b/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.cpp
@@ -18,6 +18,10 @@
 
 #include "VtsHalNeuralnetworks.h"
 
+#include <android-base/logging.h>
+
+#include "Callbacks.h"
+
 namespace android {
 namespace hardware {
 namespace neuralnetworks {
@@ -25,6 +29,55 @@
 namespace vts {
 namespace functional {
 
+using ::android::hardware::neuralnetworks::V1_2::implementation::PreparedModelCallback;
+
+static void createPreparedModel(const sp<IDevice>& device, const V1_0::Model& model,
+                                sp<IPreparedModel>* preparedModel) {
+    ASSERT_NE(nullptr, preparedModel);
+
+    // see if service can handle model
+    bool fullySupportsModel = false;
+    Return<void> supportedOpsLaunchStatus = device->getSupportedOperations(
+            model, [&fullySupportsModel](ErrorStatus status, const hidl_vec<bool>& supported) {
+                ASSERT_EQ(ErrorStatus::NONE, status);
+                ASSERT_NE(0ul, supported.size());
+                fullySupportsModel = std::all_of(supported.begin(), supported.end(),
+                                                 [](bool valid) { return valid; });
+            });
+    ASSERT_TRUE(supportedOpsLaunchStatus.isOk());
+
+    // launch prepare model
+    sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
+    ASSERT_NE(nullptr, preparedModelCallback.get());
+    Return<ErrorStatus> prepareLaunchStatus = device->prepareModel(model, preparedModelCallback);
+    ASSERT_TRUE(prepareLaunchStatus.isOk());
+    ASSERT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(prepareLaunchStatus));
+
+    // retrieve prepared model
+    preparedModelCallback->wait();
+    ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
+    *preparedModel = preparedModelCallback->getPreparedModel();
+
+    // The getSupportedOperations call returns a list of operations that are
+    // guaranteed not to fail if prepareModel is called, and
+    // 'fullySupportsModel' is true i.f.f. the entire model is guaranteed.
+    // If a driver has any doubt that it can prepare an operation, it must
+    // return false. So here, if a driver isn't sure if it can support an
+    // operation, but reports that it successfully prepared the model, the test
+    // can continue.
+    if (!fullySupportsModel && prepareReturnStatus != ErrorStatus::NONE) {
+        ASSERT_EQ(nullptr, preparedModel->get());
+        LOG(INFO) << "NN VTS: Unable to test Request validation because vendor service cannot "
+                     "prepare model that it does not support.";
+        std::cout << "[          ]   Unable to test Request validation because vendor service "
+                     "cannot prepare model that it does not support."
+                  << std::endl;
+        return;
+    }
+    ASSERT_EQ(ErrorStatus::NONE, prepareReturnStatus);
+    ASSERT_NE(nullptr, preparedModel->get());
+}
+
 // A class for test environment setup
 NeuralnetworksHidlEnvironment::NeuralnetworksHidlEnvironment() {}
 
@@ -68,6 +121,19 @@
     ::testing::VtsHalHidlTargetTestBase::TearDown();
 }
 
+void ValidationTest::validateEverything(const Model& model, const std::vector<Request>& requests) {
+    validateModel(model);
+
+    // create IPreparedModel
+    sp<IPreparedModel> preparedModel;
+    ASSERT_NO_FATAL_FAILURE(createPreparedModel(device, model, &preparedModel));
+    if (preparedModel == nullptr) {
+        return;
+    }
+
+    validateRequests(preparedModel, requests);
+}
+
 }  // namespace functional
 }  // namespace vts
 }  // namespace V1_0
diff --git a/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.h b/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.h
index d4c114d..22285be 100644
--- a/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.h
+++ b/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.h
@@ -63,8 +63,12 @@
 // Tag for the validation tests
 class ValidationTest : public NeuralnetworksHidlTest {
    protected:
-    void validateModel(const Model& model);
-    void validateRequests(const Model& model, const std::vector<Request>& request);
+     void validateEverything(const Model& model, const std::vector<Request>& request);
+
+   private:
+     void validateModel(const Model& model);
+     void validateRequests(const sp<IPreparedModel>& preparedModel,
+                           const std::vector<Request>& requests);
 };
 
 // Tag for the generated tests
diff --git a/neuralnetworks/1.1/types.hal b/neuralnetworks/1.1/types.hal
index 335b803..73705bb 100644
--- a/neuralnetworks/1.1/types.hal
+++ b/neuralnetworks/1.1/types.hal
@@ -138,7 +138,7 @@
      *
      * Supported tensor {@link OperandType}:
      * * {@link OperandType::TENSOR_FLOAT32}
-     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM} (the pad value is undefined)
      *
      * Supported tensor rank: up to 4
      *
@@ -161,6 +161,9 @@
      *          output0.dimension[i] =
      *              padding[i, 0] + input0.dimension[i] + padding[i, 1]
      *
+     *      NOTE: The pad value for {@link ANEURALNETWORKS_TENSOR_QUANT8_ASYMM}
+     *      is undefined.
+     *
      * Available since API level 28.
      */
     PAD = 32,
diff --git a/neuralnetworks/1.1/vts/functional/ValidateRequest.cpp b/neuralnetworks/1.1/vts/functional/ValidateRequest.cpp
index 5225bf7..f4adbab 100644
--- a/neuralnetworks/1.1/vts/functional/ValidateRequest.cpp
+++ b/neuralnetworks/1.1/vts/functional/ValidateRequest.cpp
@@ -34,7 +34,6 @@
 namespace functional {
 
 using ::android::hardware::neuralnetworks::V1_2::implementation::ExecutionCallback;
-using ::android::hardware::neuralnetworks::V1_2::implementation::PreparedModelCallback;
 using ::android::hidl::memory::V1_0::IMemory;
 using test_helper::for_all;
 using test_helper::MixedTyped;
@@ -42,54 +41,6 @@
 
 ///////////////////////// UTILITY FUNCTIONS /////////////////////////
 
-static void createPreparedModel(const sp<IDevice>& device, const V1_1::Model& model,
-                                sp<IPreparedModel>* preparedModel) {
-    ASSERT_NE(nullptr, preparedModel);
-
-    // see if service can handle model
-    bool fullySupportsModel = false;
-    Return<void> supportedOpsLaunchStatus = device->getSupportedOperations_1_1(
-        model, [&fullySupportsModel](ErrorStatus status, const hidl_vec<bool>& supported) {
-            ASSERT_EQ(ErrorStatus::NONE, status);
-            ASSERT_NE(0ul, supported.size());
-            fullySupportsModel =
-                std::all_of(supported.begin(), supported.end(), [](bool valid) { return valid; });
-        });
-    ASSERT_TRUE(supportedOpsLaunchStatus.isOk());
-
-    // launch prepare model
-    sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
-    ASSERT_NE(nullptr, preparedModelCallback.get());
-    Return<ErrorStatus> prepareLaunchStatus = device->prepareModel_1_1(
-        model, ExecutionPreference::FAST_SINGLE_ANSWER, preparedModelCallback);
-    ASSERT_TRUE(prepareLaunchStatus.isOk());
-    ASSERT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(prepareLaunchStatus));
-
-    // retrieve prepared model
-    preparedModelCallback->wait();
-    ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
-    *preparedModel = preparedModelCallback->getPreparedModel();
-
-    // The getSupportedOperations_1_1 call returns a list of operations that are
-    // guaranteed not to fail if prepareModel_1_1 is called, and
-    // 'fullySupportsModel' is true i.f.f. the entire model is guaranteed.
-    // If a driver has any doubt that it can prepare an operation, it must
-    // return false. So here, if a driver isn't sure if it can support an
-    // operation, but reports that it successfully prepared the model, the test
-    // can continue.
-    if (!fullySupportsModel && prepareReturnStatus != ErrorStatus::NONE) {
-        ASSERT_EQ(nullptr, preparedModel->get());
-        LOG(INFO) << "NN VTS: Unable to test Request validation because vendor service cannot "
-                     "prepare model that it does not support.";
-        std::cout << "[          ]   Unable to test Request validation because vendor service "
-                     "cannot prepare model that it does not support."
-                  << std::endl;
-        return;
-    }
-    ASSERT_EQ(ErrorStatus::NONE, prepareReturnStatus);
-    ASSERT_NE(nullptr, preparedModel->get());
-}
-
 // Primary validation function. This function will take a valid request, apply a
 // mutation to it to invalidate the request, then pass it to interface calls
 // that use the request. Note that the request here is passed by value, and any
@@ -238,15 +189,8 @@
     return requests;
 }
 
-void ValidationTest::validateRequests(const V1_1::Model& model,
+void ValidationTest::validateRequests(const sp<IPreparedModel>& preparedModel,
                                       const std::vector<Request>& requests) {
-    // create IPreparedModel
-    sp<IPreparedModel> preparedModel;
-    ASSERT_NO_FATAL_FAILURE(createPreparedModel(device, model, &preparedModel));
-    if (preparedModel == nullptr) {
-        return;
-    }
-
     // validate each request
     for (const Request& request : requests) {
         removeInputTest(preparedModel, request);
diff --git a/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.cpp b/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.cpp
index 224a51d..08069f2 100644
--- a/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.cpp
+++ b/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.cpp
@@ -18,6 +18,10 @@
 
 #include "VtsHalNeuralnetworks.h"
 
+#include <android-base/logging.h>
+
+#include "Callbacks.h"
+
 namespace android {
 namespace hardware {
 namespace neuralnetworks {
@@ -25,6 +29,56 @@
 namespace vts {
 namespace functional {
 
+using ::android::hardware::neuralnetworks::V1_2::implementation::PreparedModelCallback;
+
+static void createPreparedModel(const sp<IDevice>& device, const V1_1::Model& model,
+                                sp<IPreparedModel>* preparedModel) {
+    ASSERT_NE(nullptr, preparedModel);
+
+    // see if service can handle model
+    bool fullySupportsModel = false;
+    Return<void> supportedOpsLaunchStatus = device->getSupportedOperations_1_1(
+            model, [&fullySupportsModel](ErrorStatus status, const hidl_vec<bool>& supported) {
+                ASSERT_EQ(ErrorStatus::NONE, status);
+                ASSERT_NE(0ul, supported.size());
+                fullySupportsModel = std::all_of(supported.begin(), supported.end(),
+                                                 [](bool valid) { return valid; });
+            });
+    ASSERT_TRUE(supportedOpsLaunchStatus.isOk());
+
+    // launch prepare model
+    sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
+    ASSERT_NE(nullptr, preparedModelCallback.get());
+    Return<ErrorStatus> prepareLaunchStatus = device->prepareModel_1_1(
+            model, ExecutionPreference::FAST_SINGLE_ANSWER, preparedModelCallback);
+    ASSERT_TRUE(prepareLaunchStatus.isOk());
+    ASSERT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(prepareLaunchStatus));
+
+    // retrieve prepared model
+    preparedModelCallback->wait();
+    ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
+    *preparedModel = preparedModelCallback->getPreparedModel();
+
+    // The getSupportedOperations_1_1 call returns a list of operations that are
+    // guaranteed not to fail if prepareModel_1_1 is called, and
+    // 'fullySupportsModel' is true i.f.f. the entire model is guaranteed.
+    // If a driver has any doubt that it can prepare an operation, it must
+    // return false. So here, if a driver isn't sure if it can support an
+    // operation, but reports that it successfully prepared the model, the test
+    // can continue.
+    if (!fullySupportsModel && prepareReturnStatus != ErrorStatus::NONE) {
+        ASSERT_EQ(nullptr, preparedModel->get());
+        LOG(INFO) << "NN VTS: Unable to test Request validation because vendor service cannot "
+                     "prepare model that it does not support.";
+        std::cout << "[          ]   Unable to test Request validation because vendor service "
+                     "cannot prepare model that it does not support."
+                  << std::endl;
+        return;
+    }
+    ASSERT_EQ(ErrorStatus::NONE, prepareReturnStatus);
+    ASSERT_NE(nullptr, preparedModel->get());
+}
+
 // A class for test environment setup
 NeuralnetworksHidlEnvironment::NeuralnetworksHidlEnvironment() {}
 
@@ -68,6 +122,19 @@
     ::testing::VtsHalHidlTargetTestBase::TearDown();
 }
 
+void ValidationTest::validateEverything(const Model& model, const std::vector<Request>& requests) {
+    validateModel(model);
+
+    // create IPreparedModel
+    sp<IPreparedModel> preparedModel;
+    ASSERT_NO_FATAL_FAILURE(createPreparedModel(device, model, &preparedModel));
+    if (preparedModel == nullptr) {
+        return;
+    }
+
+    validateRequests(preparedModel, requests);
+}
+
 }  // namespace functional
 }  // namespace vts
 }  // namespace V1_1
diff --git a/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.h b/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.h
index 1c8c0e1..f3f587b 100644
--- a/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.h
+++ b/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.h
@@ -72,8 +72,12 @@
 // Tag for the validation tests
 class ValidationTest : public NeuralnetworksHidlTest {
    protected:
-    void validateModel(const Model& model);
-    void validateRequests(const Model& model, const std::vector<Request>& request);
+     void validateEverything(const Model& model, const std::vector<Request>& request);
+
+   private:
+     void validateModel(const Model& model);
+     void validateRequests(const sp<IPreparedModel>& preparedModel,
+                           const std::vector<Request>& requests);
 };
 
 // Tag for the generated tests
diff --git a/neuralnetworks/1.2/types.hal b/neuralnetworks/1.2/types.hal
index 31576fa..c2e8f22 100644
--- a/neuralnetworks/1.2/types.hal
+++ b/neuralnetworks/1.2/types.hal
@@ -1593,9 +1593,9 @@
      *      the input. Since API level 29, zero batches is supported for this
      *      tensor.
      * * 1: An {@link OperandType::INT32} scalar, specifying the output
-     *      height of the output tensor.
-     * * 2: An {@link OperandType::INT32} scalar, specifying the output
      *      width of the output tensor.
+     * * 2: An {@link OperandType::INT32} scalar, specifying the output
+     *      height of the output tensor.
      * * 3: An optional {@link OperandType::BOOL} scalar, default to false.
      *      Set to true to specify NCHW data layout for input0 and output0.
      *      Available since API level 29.
@@ -1603,15 +1603,15 @@
      * Inputs (resizing by scale, since API level 29):
      * * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
      *      the input. Zero batches is supported for this tensor.
-     * * 1: A scalar, specifying height_scale, the scaling factor of the height
+     * * 1: A scalar, specifying width_scale, the scaling factor of the width
      *      dimension from the input tensor to the output tensor. The output
-     *      height is calculated as new_height = floor(height * height_scale).
+     *      width is calculated as new_width = floor(width * width_scale).
      *      The scalar must be of {@link OperandType::FLOAT16} if input0 is
      *      of {@link OperandType::TENSOR_FLOAT16} and of
      *      {@link OperandType::FLOAT32} otherwise.
-     * * 2: A scalar, specifying width_scale, the scaling factor of the width
+     * * 2: A scalar, specifying height_scale, the scaling factor of the height
      *      dimension from the input tensor to the output tensor. The output
-     *      width is calculated as new_width = floor(width * width_scale).
+     *      height is calculated as new_height = floor(height * height_scale).
      *      The scalar must be of {@link OperandType::FLOAT16} if input0 is
      *      of {@link OperandType::TENSOR_FLOAT16} and of
      *      {@link OperandType::FLOAT32} otherwise.
@@ -1999,7 +1999,8 @@
      * Supported tensor {@link OperandType}:
      * * {@link OperandType::TENSOR_FLOAT16} (since API level 29)
      * * {@link OperandType::TENSOR_FLOAT32}
-     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM} (full support since API
+     *   level 29, see the output section)
      *
      * Supported tensor rank: up to 4
      *
@@ -2022,6 +2023,10 @@
      *          output0.dimension[i] =
      *              padding[i, 0] + input0.dimension[i] + padding[i, 1]
      *
+     *      NOTE: Before API level 29, the pad value for
+     *      {@link ANEURALNETWORKS_TENSOR_QUANT8_ASYMM} is undefined.
+     *      Since API level 29, the pad value is always the logical zero.
+     *
      * Available since API level 28.
      */
     PAD = @1.1::OperationType:PAD,
@@ -4663,24 +4668,24 @@
      * * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
      *      the input. Zero batches is supported for this tensor.
      * * 1: An {@link OperandType::INT32} scalar, specifying the output
-     *      height of the output tensor.
-     * * 2: An {@link OperandType::INT32} scalar, specifying the output
      *      width of the output tensor.
+     * * 2: An {@link OperandType::INT32} scalar, specifying the output
+     *      height of the output tensor.
      * * 3: An {@link OperandType::BOOL} scalar, default to false.
      *      Set to true to specify NCHW data layout for input0 and output0.
      *
      * Inputs (resizing by scale):
      * * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
      *      the input. Zero batches is supported for this tensor.
-     * * 1: A scalar, specifying height_scale, the scaling factor of the height
+     * * 1: A scalar, specifying width_scale, the scaling factor of the width
      *      dimension from the input tensor to the output tensor. The output
-     *      height is calculated as new_height = floor(height * height_scale).
+     *      width is calculated as new_width = floor(width * width_scale).
      *      The scalar must be of {@link OperandType::FLOAT16} if input0 is
      *      of {@link OperandType::TENSOR_FLOAT16} and of
      *      {@link OperandType::FLOAT32} otherwise.
-     * * 2: A scalar, specifying width_scale, the scaling factor of the width
+     * * 2: A scalar, specifying height_scale, the scaling factor of the height
      *      dimension from the input tensor to the output tensor. The output
-     *      width is calculated as new_width = floor(width * width_scale).
+     *      height is calculated as new_height = floor(height * height_scale).
      *      The scalar must be of {@link OperandType::FLOAT16} if input0 is
      *      of {@link OperandType::TENSOR_FLOAT16} and of
      *      {@link OperandType::FLOAT32} otherwise.
diff --git a/neuralnetworks/1.2/vts/functional/Android.bp b/neuralnetworks/1.2/vts/functional/Android.bp
index 891b414..6c26820 100644
--- a/neuralnetworks/1.2/vts/functional/Android.bp
+++ b/neuralnetworks/1.2/vts/functional/Android.bp
@@ -20,6 +20,7 @@
     defaults: ["VtsHalNeuralNetworksTargetTestDefaults"],
     srcs: [
         "GeneratedTestsV1_0.cpp",
+        "ValidateBurst.cpp",
     ],
     cflags: [
         "-DNN_TEST_DYNAMIC_OUTPUT_SHAPE"
@@ -32,6 +33,7 @@
     defaults: ["VtsHalNeuralNetworksTargetTestDefaults"],
     srcs: [
         "GeneratedTestsV1_1.cpp",
+        "ValidateBurst.cpp",
     ],
     cflags: [
         "-DNN_TEST_DYNAMIC_OUTPUT_SHAPE"
@@ -46,6 +48,7 @@
         "BasicTests.cpp",
         "CompilationCachingTests.cpp",
         "GeneratedTests.cpp",
+        "ValidateBurst.cpp",
     ],
     cflags: [
         "-DNN_TEST_DYNAMIC_OUTPUT_SHAPE"
@@ -58,6 +61,7 @@
     srcs: [
         "BasicTests.cpp",
         "GeneratedTests.cpp",
+        "ValidateBurst.cpp",
     ],
     cflags: [
         "-DNN_TEST_DYNAMIC_OUTPUT_SHAPE",
diff --git a/neuralnetworks/1.2/vts/functional/CompilationCachingTests.cpp b/neuralnetworks/1.2/vts/functional/CompilationCachingTests.cpp
index 167fc09..4411b90 100644
--- a/neuralnetworks/1.2/vts/functional/CompilationCachingTests.cpp
+++ b/neuralnetworks/1.2/vts/functional/CompilationCachingTests.cpp
@@ -16,21 +16,22 @@
 
 #define LOG_TAG "neuralnetworks_hidl_hal_test"
 
-#include "VtsHalNeuralnetworks.h"
+#include <android-base/logging.h>
+#include <android/hidl/memory/1.0/IMemory.h>
+#include <ftw.h>
+#include <gtest/gtest.h>
+#include <hidlmemory/mapping.h>
+#include <unistd.h>
+
+#include <cstdio>
+#include <cstdlib>
+#include <random>
 
 #include "Callbacks.h"
 #include "GeneratedTestHarness.h"
 #include "TestHarness.h"
 #include "Utils.h"
-
-#include <android-base/logging.h>
-#include <android/hidl/memory/1.0/IMemory.h>
-#include <hidlmemory/mapping.h>
-#include <cstdio>
-#include <cstdlib>
-#include <random>
-
-#include <gtest/gtest.h>
+#include "VtsHalNeuralnetworks.h"
 
 namespace android {
 namespace hardware {
@@ -44,9 +45,9 @@
 using ::android::nn::allocateSharedMemory;
 using ::test_helper::MixedTypedExample;
 
-namespace {
+namespace float32_model {
 
-// In frameworks/ml/nn/runtime/tests/generated/, creates a hidl model of mobilenet.
+// In frameworks/ml/nn/runtime/test/generated/, creates a hidl model of float32 mobilenet.
 #include "examples/mobilenet_224_gender_basic_fixed.example.cpp"
 #include "vts_models/mobilenet_224_gender_basic_fixed.model.cpp"
 
@@ -54,6 +55,44 @@
 [[maybe_unused]] auto dummy_createTestModel = createTestModel_dynamic_output_shape;
 [[maybe_unused]] auto dummy_get_examples = get_examples_dynamic_output_shape;
 
+// MixedTypedExample is defined in frameworks/ml/nn/tools/test_generator/include/TestHarness.h.
+// This function assumes the operation is always ADD.
+std::vector<MixedTypedExample> getLargeModelExamples(uint32_t len) {
+    float outputValue = 1.0f + static_cast<float>(len);
+    return {{.operands = {
+                     // Input
+                     {.operandDimensions = {{0, {1}}}, .float32Operands = {{0, {1.0f}}}},
+                     // Output
+                     {.operandDimensions = {{0, {1}}}, .float32Operands = {{0, {outputValue}}}}}}};
+}
+
+}  // namespace float32_model
+
+namespace quant8_model {
+
+// In frameworks/ml/nn/runtime/test/generated/, creates a hidl model of quant8 mobilenet.
+#include "examples/mobilenet_quantized.example.cpp"
+#include "vts_models/mobilenet_quantized.model.cpp"
+
+// Prevent the compiler from complaining about an otherwise unused function.
+[[maybe_unused]] auto dummy_createTestModel = createTestModel_dynamic_output_shape;
+[[maybe_unused]] auto dummy_get_examples = get_examples_dynamic_output_shape;
+
+// MixedTypedExample is defined in frameworks/ml/nn/tools/test_generator/include/TestHarness.h.
+// This function assumes the operation is always ADD.
+std::vector<MixedTypedExample> getLargeModelExamples(uint32_t len) {
+    uint8_t outputValue = 1 + static_cast<uint8_t>(len);
+    return {{.operands = {// Input
+                          {.operandDimensions = {{0, {1}}}, .quant8AsymmOperands = {{0, {1}}}},
+                          // Output
+                          {.operandDimensions = {{0, {1}}},
+                           .quant8AsymmOperands = {{0, {outputValue}}}}}}};
+}
+
+}  // namespace quant8_model
+
+namespace {
+
 enum class AccessMode { READ_WRITE, READ_ONLY, WRITE_ONLY };
 
 // Creates cache handles based on provided file groups.
@@ -89,11 +128,137 @@
     createCacheHandles(fileGroups, std::vector<AccessMode>(fileGroups.size(), mode), handles);
 }
 
+// Create a chain of broadcast operations. The second operand is always constant tensor [1].
+// For simplicity, activation scalar is shared. The second operand is not shared
+// in the model to let driver maintain a non-trivial size of constant data and the corresponding
+// data locations in cache.
+//
+//                --------- activation --------
+//                ↓      ↓      ↓             ↓
+// E.g. input -> ADD -> ADD -> ADD -> ... -> ADD -> output
+//                ↑      ↑      ↑             ↑
+//               [1]    [1]    [1]           [1]
+//
+// This function assumes the operation is either ADD or MUL.
+template <typename CppType, OperandType operandType>
+Model createLargeTestModelImpl(OperationType op, uint32_t len) {
+    EXPECT_TRUE(op == OperationType::ADD || op == OperationType::MUL);
+
+    // Model operations and operands.
+    std::vector<Operation> operations(len);
+    std::vector<Operand> operands(len * 2 + 2);
+
+    // The constant buffer pool. This contains the activation scalar, followed by the
+    // per-operation constant operands.
+    std::vector<uint8_t> operandValues(sizeof(int32_t) + len * sizeof(CppType));
+
+    // The activation scalar, value = 0.
+    operands[0] = {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = len,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = sizeof(int32_t)},
+    };
+    memset(operandValues.data(), 0, sizeof(int32_t));
+
+    // The buffer value of the constant second operand. The logical value is always 1.0f.
+    CppType bufferValue;
+    // The scale of the first and second operand.
+    float scale1, scale2;
+    if (operandType == OperandType::TENSOR_FLOAT32) {
+        bufferValue = 1.0f;
+        scale1 = 0.0f;
+        scale2 = 0.0f;
+    } else if (op == OperationType::ADD) {
+        bufferValue = 1;
+        scale1 = 1.0f;
+        scale2 = 1.0f;
+    } else {
+        // To satisfy the constraint on quant8 MUL: input0.scale * input1.scale < output.scale,
+        // set input1 to have scale = 0.5f and bufferValue = 2, i.e. 1.0f in floating point.
+        bufferValue = 2;
+        scale1 = 1.0f;
+        scale2 = 0.5f;
+    }
+
+    for (uint32_t i = 0; i < len; i++) {
+        const uint32_t firstInputIndex = i * 2 + 1;
+        const uint32_t secondInputIndex = firstInputIndex + 1;
+        const uint32_t outputIndex = secondInputIndex + 1;
+
+        // The first operation input.
+        operands[firstInputIndex] = {
+                .type = operandType,
+                .dimensions = {1},
+                .numberOfConsumers = 1,
+                .scale = scale1,
+                .zeroPoint = 0,
+                .lifetime = (i == 0 ? OperandLifeTime::MODEL_INPUT
+                                    : OperandLifeTime::TEMPORARY_VARIABLE),
+                .location = {},
+        };
+
+        // The second operation input, value = 1.
+        operands[secondInputIndex] = {
+                .type = operandType,
+                .dimensions = {1},
+                .numberOfConsumers = 1,
+                .scale = scale2,
+                .zeroPoint = 0,
+                .lifetime = OperandLifeTime::CONSTANT_COPY,
+                .location = {.poolIndex = 0,
+                             .offset = static_cast<uint32_t>(i * sizeof(CppType) + sizeof(int32_t)),
+                             .length = sizeof(CppType)},
+        };
+        memcpy(operandValues.data() + sizeof(int32_t) + i * sizeof(CppType), &bufferValue,
+               sizeof(CppType));
+
+        // The operation. All operations share the same activation scalar.
+        // The output operand is created as an input in the next iteration of the loop, in the case
+        // of all but the last member of the chain; and after the loop as a model output, in the
+        // case of the last member of the chain.
+        operations[i] = {
+                .type = op,
+                .inputs = {firstInputIndex, secondInputIndex, /*activation scalar*/ 0},
+                .outputs = {outputIndex},
+        };
+    }
+
+    // The model output.
+    operands.back() = {
+            .type = operandType,
+            .dimensions = {1},
+            .numberOfConsumers = 0,
+            .scale = scale1,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {},
+    };
+
+    const std::vector<uint32_t> inputIndexes = {1};
+    const std::vector<uint32_t> outputIndexes = {len * 2 + 1};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+            .operands = operands,
+            .operations = operations,
+            .inputIndexes = inputIndexes,
+            .outputIndexes = outputIndexes,
+            .operandValues = operandValues,
+            .pools = pools,
+    };
+}
+
 }  // namespace
 
 // Tag for the compilation caching tests.
-class CompilationCachingTest : public NeuralnetworksHidlTest {
+class CompilationCachingTestBase : public NeuralnetworksHidlTest {
   protected:
+    CompilationCachingTestBase(OperandType type) : kOperandType(type) {}
+
     void SetUp() override {
         NeuralnetworksHidlTest::SetUp();
         ASSERT_NE(device.get(), nullptr);
@@ -139,21 +304,53 @@
     }
 
     void TearDown() override {
-        // The tmp directory is only removed when the driver reports caching not supported,
-        // otherwise it is kept for debugging purpose.
-        if (!mIsCachingSupported) {
-            remove(mTmpCache.c_str());
-            rmdir(mCacheDir.c_str());
+        // If the test passes, remove the tmp directory.  Otherwise, keep it for debugging purposes.
+        if (!::testing::Test::HasFailure()) {
+            // Recursively remove the cache directory specified by mCacheDir.
+            auto callback = [](const char* entry, const struct stat*, int, struct FTW*) {
+                return remove(entry);
+            };
+            nftw(mCacheDir.c_str(), callback, 128, FTW_DEPTH | FTW_MOUNT | FTW_PHYS);
         }
         NeuralnetworksHidlTest::TearDown();
     }
 
-    void saveModelToCache(const V1_2::Model& model, const hidl_vec<hidl_handle>& modelCache,
-                          const hidl_vec<hidl_handle>& dataCache, bool* supported,
-                          sp<IPreparedModel>* preparedModel = nullptr) {
-        if (preparedModel != nullptr) *preparedModel = nullptr;
+    // Model and examples creators. According to kOperandType, the following methods will return
+    // either float32 model/examples or the quant8 variant.
+    Model createTestModel() {
+        if (kOperandType == OperandType::TENSOR_FLOAT32) {
+            return float32_model::createTestModel();
+        } else {
+            return quant8_model::createTestModel();
+        }
+    }
 
-        // See if service can handle model.
+    std::vector<MixedTypedExample> get_examples() {
+        if (kOperandType == OperandType::TENSOR_FLOAT32) {
+            return float32_model::get_examples();
+        } else {
+            return quant8_model::get_examples();
+        }
+    }
+
+    Model createLargeTestModel(OperationType op, uint32_t len) {
+        if (kOperandType == OperandType::TENSOR_FLOAT32) {
+            return createLargeTestModelImpl<float, OperandType::TENSOR_FLOAT32>(op, len);
+        } else {
+            return createLargeTestModelImpl<uint8_t, OperandType::TENSOR_QUANT8_ASYMM>(op, len);
+        }
+    }
+
+    std::vector<MixedTypedExample> getLargeModelExamples(uint32_t len) {
+        if (kOperandType == OperandType::TENSOR_FLOAT32) {
+            return float32_model::getLargeModelExamples(len);
+        } else {
+            return quant8_model::getLargeModelExamples(len);
+        }
+    }
+
+    // See if the service can handle the model.
+    bool isModelFullySupported(const V1_2::Model& model) {
         bool fullySupportsModel = false;
         Return<void> supportedCall = device->getSupportedOperations_1_2(
                 model,
@@ -163,9 +360,14 @@
                     fullySupportsModel = std::all_of(supported.begin(), supported.end(),
                                                      [](bool valid) { return valid; });
                 });
-        ASSERT_TRUE(supportedCall.isOk());
-        *supported = fullySupportsModel;
-        if (!fullySupportsModel) return;
+        EXPECT_TRUE(supportedCall.isOk());
+        return fullySupportsModel;
+    }
+
+    void saveModelToCache(const V1_2::Model& model, const hidl_vec<hidl_handle>& modelCache,
+                          const hidl_vec<hidl_handle>& dataCache,
+                          sp<IPreparedModel>* preparedModel = nullptr) {
+        if (preparedModel != nullptr) *preparedModel = nullptr;
 
         // Launch prepare model.
         sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
@@ -199,8 +401,8 @@
         return false;
     }
 
-    bool checkEarlyTermination(bool supported) {
-        if (!supported) {
+    bool checkEarlyTermination(const V1_2::Model& model) {
+        if (!isModelFullySupported(model)) {
             LOG(INFO) << "NN VTS: Early termination of test because vendor service cannot "
                          "prepare model that it does not support.";
             std::cout << "[          ]   Early termination of test because vendor service cannot "
@@ -250,21 +452,31 @@
     uint32_t mNumModelCache;
     uint32_t mNumDataCache;
     uint32_t mIsCachingSupported;
+
+    // The primary data type of the testModel.
+    const OperandType kOperandType;
 };
 
-TEST_F(CompilationCachingTest, CacheSavingAndRetrieval) {
+// A parameterized fixture of CompilationCachingTestBase. Every test will run twice, with the first
+// pass running with float32 models and the second pass running with quant8 models.
+class CompilationCachingTest : public CompilationCachingTestBase,
+                               public ::testing::WithParamInterface<OperandType> {
+  protected:
+    CompilationCachingTest() : CompilationCachingTestBase(GetParam()) {}
+};
+
+TEST_P(CompilationCachingTest, CacheSavingAndRetrieval) {
     // Create test HIDL model and compile.
-    Model testModel = createTestModel();
+    const Model testModel = createTestModel();
+    if (checkEarlyTermination(testModel)) return;
     sp<IPreparedModel> preparedModel = nullptr;
 
     // Save the compilation to cache.
     {
-        bool supported;
         hidl_vec<hidl_handle> modelCache, dataCache;
         createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
         createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
-        saveModelToCache(testModel, modelCache, dataCache, &supported);
-        if (checkEarlyTermination(supported)) return;
+        saveModelToCache(testModel, modelCache, dataCache);
     }
 
     // Retrieve preparedModel from cache.
@@ -294,14 +506,14 @@
                                            /*testDynamicOutputShape=*/false);
 }
 
-TEST_F(CompilationCachingTest, CacheSavingAndRetrievalNonZeroOffset) {
+TEST_P(CompilationCachingTest, CacheSavingAndRetrievalNonZeroOffset) {
     // Create test HIDL model and compile.
-    Model testModel = createTestModel();
+    const Model testModel = createTestModel();
+    if (checkEarlyTermination(testModel)) return;
     sp<IPreparedModel> preparedModel = nullptr;
 
     // Save the compilation to cache.
     {
-        bool supported;
         hidl_vec<hidl_handle> modelCache, dataCache;
         createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
         createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
@@ -318,8 +530,7 @@
                     write(dataCache[i].getNativeHandle()->data[0], &dummyBytes, sizeof(dummyBytes)),
                     sizeof(dummyBytes));
         }
-        saveModelToCache(testModel, modelCache, dataCache, &supported);
-        if (checkEarlyTermination(supported)) return;
+        saveModelToCache(testModel, modelCache, dataCache);
     }
 
     // Retrieve preparedModel from cache.
@@ -358,13 +569,13 @@
                                            /*testDynamicOutputShape=*/false);
 }
 
-TEST_F(CompilationCachingTest, SaveToCacheInvalidNumCache) {
+TEST_P(CompilationCachingTest, SaveToCacheInvalidNumCache) {
     // Create test HIDL model and compile.
-    Model testModel = createTestModel();
+    const Model testModel = createTestModel();
+    if (checkEarlyTermination(testModel)) return;
 
     // Test with number of model cache files greater than mNumModelCache.
     {
-        bool supported;
         hidl_vec<hidl_handle> modelCache, dataCache;
         // Pass an additional cache file for model cache.
         mModelCache.push_back({mTmpCache});
@@ -372,8 +583,7 @@
         createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
         mModelCache.pop_back();
         sp<IPreparedModel> preparedModel = nullptr;
-        saveModelToCache(testModel, modelCache, dataCache, &supported, &preparedModel);
-        if (checkEarlyTermination(supported)) return;
+        saveModelToCache(testModel, modelCache, dataCache, &preparedModel);
         ASSERT_NE(preparedModel, nullptr);
         // Execute and verify results.
         generated_tests::EvaluatePreparedModel(preparedModel, [](int) { return false; },
@@ -392,7 +602,6 @@
 
     // Test with number of model cache files smaller than mNumModelCache.
     if (mModelCache.size() > 0) {
-        bool supported;
         hidl_vec<hidl_handle> modelCache, dataCache;
         // Pop out the last cache file.
         auto tmp = mModelCache.back();
@@ -401,8 +610,7 @@
         createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
         mModelCache.push_back(tmp);
         sp<IPreparedModel> preparedModel = nullptr;
-        saveModelToCache(testModel, modelCache, dataCache, &supported, &preparedModel);
-        if (checkEarlyTermination(supported)) return;
+        saveModelToCache(testModel, modelCache, dataCache, &preparedModel);
         ASSERT_NE(preparedModel, nullptr);
         // Execute and verify results.
         generated_tests::EvaluatePreparedModel(preparedModel, [](int) { return false; },
@@ -421,7 +629,6 @@
 
     // Test with number of data cache files greater than mNumDataCache.
     {
-        bool supported;
         hidl_vec<hidl_handle> modelCache, dataCache;
         // Pass an additional cache file for data cache.
         mDataCache.push_back({mTmpCache});
@@ -429,8 +636,7 @@
         createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
         mDataCache.pop_back();
         sp<IPreparedModel> preparedModel = nullptr;
-        saveModelToCache(testModel, modelCache, dataCache, &supported, &preparedModel);
-        if (checkEarlyTermination(supported)) return;
+        saveModelToCache(testModel, modelCache, dataCache, &preparedModel);
         ASSERT_NE(preparedModel, nullptr);
         // Execute and verify results.
         generated_tests::EvaluatePreparedModel(preparedModel, [](int) { return false; },
@@ -449,7 +655,6 @@
 
     // Test with number of data cache files smaller than mNumDataCache.
     if (mDataCache.size() > 0) {
-        bool supported;
         hidl_vec<hidl_handle> modelCache, dataCache;
         // Pop out the last cache file.
         auto tmp = mDataCache.back();
@@ -458,8 +663,7 @@
         createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
         mDataCache.push_back(tmp);
         sp<IPreparedModel> preparedModel = nullptr;
-        saveModelToCache(testModel, modelCache, dataCache, &supported, &preparedModel);
-        if (checkEarlyTermination(supported)) return;
+        saveModelToCache(testModel, modelCache, dataCache, &preparedModel);
         ASSERT_NE(preparedModel, nullptr);
         // Execute and verify results.
         generated_tests::EvaluatePreparedModel(preparedModel, [](int) { return false; },
@@ -477,18 +681,17 @@
     }
 }
 
-TEST_F(CompilationCachingTest, PrepareModelFromCacheInvalidNumCache) {
+TEST_P(CompilationCachingTest, PrepareModelFromCacheInvalidNumCache) {
     // Create test HIDL model and compile.
-    Model testModel = createTestModel();
+    const Model testModel = createTestModel();
+    if (checkEarlyTermination(testModel)) return;
 
     // Save the compilation to cache.
     {
-        bool supported;
         hidl_vec<hidl_handle> modelCache, dataCache;
         createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
         createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
-        saveModelToCache(testModel, modelCache, dataCache, &supported);
-        if (checkEarlyTermination(supported)) return;
+        saveModelToCache(testModel, modelCache, dataCache);
     }
 
     // Test with number of model cache files greater than mNumModelCache.
@@ -558,13 +761,13 @@
     }
 }
 
-TEST_F(CompilationCachingTest, SaveToCacheInvalidNumFd) {
+TEST_P(CompilationCachingTest, SaveToCacheInvalidNumFd) {
     // Create test HIDL model and compile.
-    Model testModel = createTestModel();
+    const Model testModel = createTestModel();
+    if (checkEarlyTermination(testModel)) return;
 
     // Go through each handle in model cache, test with NumFd greater than 1.
     for (uint32_t i = 0; i < mNumModelCache; i++) {
-        bool supported;
         hidl_vec<hidl_handle> modelCache, dataCache;
         // Pass an invalid number of fds for handle i.
         mModelCache[i].push_back(mTmpCache);
@@ -572,8 +775,7 @@
         createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
         mModelCache[i].pop_back();
         sp<IPreparedModel> preparedModel = nullptr;
-        saveModelToCache(testModel, modelCache, dataCache, &supported, &preparedModel);
-        if (checkEarlyTermination(supported)) return;
+        saveModelToCache(testModel, modelCache, dataCache, &preparedModel);
         ASSERT_NE(preparedModel, nullptr);
         // Execute and verify results.
         generated_tests::EvaluatePreparedModel(preparedModel, [](int) { return false; },
@@ -592,7 +794,6 @@
 
     // Go through each handle in model cache, test with NumFd equal to 0.
     for (uint32_t i = 0; i < mNumModelCache; i++) {
-        bool supported;
         hidl_vec<hidl_handle> modelCache, dataCache;
         // Pass an invalid number of fds for handle i.
         auto tmp = mModelCache[i].back();
@@ -601,8 +802,7 @@
         createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
         mModelCache[i].push_back(tmp);
         sp<IPreparedModel> preparedModel = nullptr;
-        saveModelToCache(testModel, modelCache, dataCache, &supported, &preparedModel);
-        if (checkEarlyTermination(supported)) return;
+        saveModelToCache(testModel, modelCache, dataCache, &preparedModel);
         ASSERT_NE(preparedModel, nullptr);
         // Execute and verify results.
         generated_tests::EvaluatePreparedModel(preparedModel, [](int) { return false; },
@@ -621,7 +821,6 @@
 
     // Go through each handle in data cache, test with NumFd greater than 1.
     for (uint32_t i = 0; i < mNumDataCache; i++) {
-        bool supported;
         hidl_vec<hidl_handle> modelCache, dataCache;
         // Pass an invalid number of fds for handle i.
         mDataCache[i].push_back(mTmpCache);
@@ -629,8 +828,7 @@
         createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
         mDataCache[i].pop_back();
         sp<IPreparedModel> preparedModel = nullptr;
-        saveModelToCache(testModel, modelCache, dataCache, &supported, &preparedModel);
-        if (checkEarlyTermination(supported)) return;
+        saveModelToCache(testModel, modelCache, dataCache, &preparedModel);
         ASSERT_NE(preparedModel, nullptr);
         // Execute and verify results.
         generated_tests::EvaluatePreparedModel(preparedModel, [](int) { return false; },
@@ -649,7 +847,6 @@
 
     // Go through each handle in data cache, test with NumFd equal to 0.
     for (uint32_t i = 0; i < mNumDataCache; i++) {
-        bool supported;
         hidl_vec<hidl_handle> modelCache, dataCache;
         // Pass an invalid number of fds for handle i.
         auto tmp = mDataCache[i].back();
@@ -658,8 +855,7 @@
         createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
         mDataCache[i].push_back(tmp);
         sp<IPreparedModel> preparedModel = nullptr;
-        saveModelToCache(testModel, modelCache, dataCache, &supported, &preparedModel);
-        if (checkEarlyTermination(supported)) return;
+        saveModelToCache(testModel, modelCache, dataCache, &preparedModel);
         ASSERT_NE(preparedModel, nullptr);
         // Execute and verify results.
         generated_tests::EvaluatePreparedModel(preparedModel, [](int) { return false; },
@@ -677,18 +873,17 @@
     }
 }
 
-TEST_F(CompilationCachingTest, PrepareModelFromCacheInvalidNumFd) {
+TEST_P(CompilationCachingTest, PrepareModelFromCacheInvalidNumFd) {
     // Create test HIDL model and compile.
-    Model testModel = createTestModel();
+    const Model testModel = createTestModel();
+    if (checkEarlyTermination(testModel)) return;
 
     // Save the compilation to cache.
     {
-        bool supported;
         hidl_vec<hidl_handle> modelCache, dataCache;
         createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
         createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
-        saveModelToCache(testModel, modelCache, dataCache, &supported);
-        if (checkEarlyTermination(supported)) return;
+        saveModelToCache(testModel, modelCache, dataCache);
     }
 
     // Go through each handle in model cache, test with NumFd greater than 1.
@@ -758,23 +953,22 @@
     }
 }
 
-TEST_F(CompilationCachingTest, SaveToCacheInvalidAccessMode) {
+TEST_P(CompilationCachingTest, SaveToCacheInvalidAccessMode) {
     // Create test HIDL model and compile.
-    Model testModel = createTestModel();
+    const Model testModel = createTestModel();
+    if (checkEarlyTermination(testModel)) return;
     std::vector<AccessMode> modelCacheMode(mNumModelCache, AccessMode::READ_WRITE);
     std::vector<AccessMode> dataCacheMode(mNumDataCache, AccessMode::READ_WRITE);
 
     // Go through each handle in model cache, test with invalid access mode.
     for (uint32_t i = 0; i < mNumModelCache; i++) {
-        bool supported;
         hidl_vec<hidl_handle> modelCache, dataCache;
         modelCacheMode[i] = AccessMode::READ_ONLY;
         createCacheHandles(mModelCache, modelCacheMode, &modelCache);
         createCacheHandles(mDataCache, dataCacheMode, &dataCache);
         modelCacheMode[i] = AccessMode::READ_WRITE;
         sp<IPreparedModel> preparedModel = nullptr;
-        saveModelToCache(testModel, modelCache, dataCache, &supported, &preparedModel);
-        if (checkEarlyTermination(supported)) return;
+        saveModelToCache(testModel, modelCache, dataCache, &preparedModel);
         ASSERT_NE(preparedModel, nullptr);
         // Execute and verify results.
         generated_tests::EvaluatePreparedModel(preparedModel, [](int) { return false; },
@@ -793,15 +987,13 @@
 
     // Go through each handle in data cache, test with invalid access mode.
     for (uint32_t i = 0; i < mNumDataCache; i++) {
-        bool supported;
         hidl_vec<hidl_handle> modelCache, dataCache;
         dataCacheMode[i] = AccessMode::READ_ONLY;
         createCacheHandles(mModelCache, modelCacheMode, &modelCache);
         createCacheHandles(mDataCache, dataCacheMode, &dataCache);
         dataCacheMode[i] = AccessMode::READ_WRITE;
         sp<IPreparedModel> preparedModel = nullptr;
-        saveModelToCache(testModel, modelCache, dataCache, &supported, &preparedModel);
-        if (checkEarlyTermination(supported)) return;
+        saveModelToCache(testModel, modelCache, dataCache, &preparedModel);
         ASSERT_NE(preparedModel, nullptr);
         // Execute and verify results.
         generated_tests::EvaluatePreparedModel(preparedModel, [](int) { return false; },
@@ -819,20 +1011,19 @@
     }
 }
 
-TEST_F(CompilationCachingTest, PrepareModelFromCacheInvalidAccessMode) {
+TEST_P(CompilationCachingTest, PrepareModelFromCacheInvalidAccessMode) {
     // Create test HIDL model and compile.
-    Model testModel = createTestModel();
+    const Model testModel = createTestModel();
+    if (checkEarlyTermination(testModel)) return;
     std::vector<AccessMode> modelCacheMode(mNumModelCache, AccessMode::READ_WRITE);
     std::vector<AccessMode> dataCacheMode(mNumDataCache, AccessMode::READ_WRITE);
 
     // Save the compilation to cache.
     {
-        bool supported;
         hidl_vec<hidl_handle> modelCache, dataCache;
         createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
         createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
-        saveModelToCache(testModel, modelCache, dataCache, &supported);
-        if (checkEarlyTermination(supported)) return;
+        saveModelToCache(testModel, modelCache, dataCache);
     }
 
     // Go through each handle in model cache, test with invalid access mode.
@@ -864,129 +1055,198 @@
     }
 }
 
-class CompilationCachingSecurityTest : public CompilationCachingTest,
-                                       public ::testing::WithParamInterface<uint32_t> {
-  protected:
-    void SetUp() {
-        CompilationCachingTest::SetUp();
-        generator.seed(kSeed);
-    }
+// Copy file contents between file groups.
+// The outer vector corresponds to handles and the inner vector is for fds held by each handle.
+// The outer vector sizes must match and the inner vectors must have size = 1.
+static void copyCacheFiles(const std::vector<std::vector<std::string>>& from,
+                           const std::vector<std::vector<std::string>>& to) {
+    constexpr size_t kBufferSize = 1000000;
+    uint8_t buffer[kBufferSize];
 
-    // Get a random integer within a closed range [lower, upper].
-    template <typename T>
-    T getRandomInt(T lower, T upper) {
-        std::uniform_int_distribution<T> dis(lower, upper);
-        return dis(generator);
-    }
+    ASSERT_EQ(from.size(), to.size());
+    for (uint32_t i = 0; i < from.size(); i++) {
+        ASSERT_EQ(from[i].size(), 1u);
+        ASSERT_EQ(to[i].size(), 1u);
+        int fromFd = open(from[i][0].c_str(), O_RDONLY);
+        int toFd = open(to[i][0].c_str(), O_WRONLY | O_CREAT, S_IRUSR | S_IWUSR);
+        ASSERT_GE(fromFd, 0);
+        ASSERT_GE(toFd, 0);
 
-    const uint32_t kSeed = GetParam();
-    std::mt19937 generator;
-};
-
-TEST_P(CompilationCachingSecurityTest, CorruptedSecuritySensitiveCache) {
-    if (!mIsCachingSupported) return;
-
-    // Create test HIDL model and compile.
-    Model testModel = createTestModel();
-
-    for (uint32_t i = 0; i < mNumModelCache; i++) {
-        // Save the compilation to cache.
-        {
-            bool supported;
-            hidl_vec<hidl_handle> modelCache, dataCache;
-            createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
-            createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
-            saveModelToCache(testModel, modelCache, dataCache, &supported);
-            if (checkEarlyTermination(supported)) return;
+        ssize_t readBytes;
+        while ((readBytes = read(fromFd, &buffer, kBufferSize)) > 0) {
+            ASSERT_EQ(write(toFd, &buffer, readBytes), readBytes);
         }
+        ASSERT_GE(readBytes, 0);
 
-        // Randomly flip one single bit of the cache entry.
-        FILE* pFile = fopen(mModelCache[i][0].c_str(), "r+");
-        ASSERT_EQ(fseek(pFile, 0, SEEK_END), 0);
-        long int fileSize = ftell(pFile);
-        if (fileSize == 0) {
-            fclose(pFile);
-            continue;
-        }
-        ASSERT_EQ(fseek(pFile, getRandomInt(0l, fileSize - 1), SEEK_SET), 0);
-        int readByte = fgetc(pFile);
-        ASSERT_NE(readByte, EOF);
-        ASSERT_EQ(fseek(pFile, -1, SEEK_CUR), 0);
-        ASSERT_NE(fputc(static_cast<uint8_t>(readByte) ^ (1U << getRandomInt(0, 7)), pFile), EOF);
-        fclose(pFile);
-
-        // Retrieve preparedModel from cache, expect failure.
-        {
-            sp<IPreparedModel> preparedModel = nullptr;
-            ErrorStatus status;
-            hidl_vec<hidl_handle> modelCache, dataCache;
-            createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
-            createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
-            prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
-            ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
-            ASSERT_EQ(preparedModel, nullptr);
-        }
+        close(fromFd);
+        close(toFd);
     }
 }
 
-TEST_P(CompilationCachingSecurityTest, WrongLengthSecuritySensitiveCache) {
+// Number of operations in the large test model.
+constexpr uint32_t kLargeModelSize = 100;
+constexpr uint32_t kNumIterationsTOCTOU = 100;
+
+TEST_P(CompilationCachingTest, SaveToCache_TOCTOU) {
     if (!mIsCachingSupported) return;
 
-    // Create test HIDL model and compile.
-    Model testModel = createTestModel();
+    // Create test models and check if fully supported by the service.
+    const Model testModelMul = createLargeTestModel(OperationType::MUL, kLargeModelSize);
+    if (checkEarlyTermination(testModelMul)) return;
+    const Model testModelAdd = createLargeTestModel(OperationType::ADD, kLargeModelSize);
+    if (checkEarlyTermination(testModelAdd)) return;
 
-    for (uint32_t i = 0; i < mNumModelCache; i++) {
-        // Save the compilation to cache.
-        {
-            bool supported;
-            hidl_vec<hidl_handle> modelCache, dataCache;
-            createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
-            createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
-            saveModelToCache(testModel, modelCache, dataCache, &supported);
-            if (checkEarlyTermination(supported)) return;
-        }
-
-        // Randomly append bytes to the cache entry.
-        FILE* pFile = fopen(mModelCache[i][0].c_str(), "a");
-        uint32_t appendLength = getRandomInt(1, 256);
-        for (uint32_t i = 0; i < appendLength; i++) {
-            ASSERT_NE(fputc(getRandomInt<uint8_t>(0, 255), pFile), EOF);
-        }
-        fclose(pFile);
-
-        // Retrieve preparedModel from cache, expect failure.
-        {
-            sp<IPreparedModel> preparedModel = nullptr;
-            ErrorStatus status;
-            hidl_vec<hidl_handle> modelCache, dataCache;
-            createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
-            createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
-            prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
-            ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
-            ASSERT_EQ(preparedModel, nullptr);
-        }
+    // Save the testModelMul compilation to cache.
+    auto modelCacheMul = mModelCache;
+    for (auto& cache : modelCacheMul) {
+        cache[0].append("_mul");
     }
-}
-
-TEST_P(CompilationCachingSecurityTest, WrongToken) {
-    if (!mIsCachingSupported) return;
-
-    // Create test HIDL model and compile.
-    Model testModel = createTestModel();
-
-    // Save the compilation to cache.
     {
-        bool supported;
+        hidl_vec<hidl_handle> modelCache, dataCache;
+        createCacheHandles(modelCacheMul, AccessMode::READ_WRITE, &modelCache);
+        createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
+        saveModelToCache(testModelMul, modelCache, dataCache);
+    }
+
+    // Use a different token for testModelAdd.
+    mToken[0]++;
+
+    // This test is probabilistic, so we run it multiple times.
+    for (uint32_t i = 0; i < kNumIterationsTOCTOU; i++) {
+        // Save the testModelAdd compilation to cache.
+        {
+            hidl_vec<hidl_handle> modelCache, dataCache;
+            createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
+            createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
+
+            // Spawn a thread to copy the cache content concurrently while saving to cache.
+            std::thread thread(copyCacheFiles, std::cref(modelCacheMul), std::cref(mModelCache));
+            saveModelToCache(testModelAdd, modelCache, dataCache);
+            thread.join();
+        }
+
+        // Retrieve preparedModel from cache.
+        {
+            sp<IPreparedModel> preparedModel = nullptr;
+            ErrorStatus status;
+            hidl_vec<hidl_handle> modelCache, dataCache;
+            createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
+            createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
+            prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+
+            // The preparation may fail or succeed, but must not crash. If the preparation succeeds,
+            // the prepared model must be executed with the correct result and not crash.
+            if (status != ErrorStatus::NONE) {
+                ASSERT_EQ(preparedModel, nullptr);
+            } else {
+                ASSERT_NE(preparedModel, nullptr);
+                generated_tests::EvaluatePreparedModel(
+                        preparedModel, [](int) { return false; },
+                        getLargeModelExamples(kLargeModelSize),
+                        testModelAdd.relaxComputationFloat32toFloat16,
+                        /*testDynamicOutputShape=*/false);
+            }
+        }
+    }
+}
+
+TEST_P(CompilationCachingTest, PrepareFromCache_TOCTOU) {
+    if (!mIsCachingSupported) return;
+
+    // Create test models and check if fully supported by the service.
+    const Model testModelMul = createLargeTestModel(OperationType::MUL, kLargeModelSize);
+    if (checkEarlyTermination(testModelMul)) return;
+    const Model testModelAdd = createLargeTestModel(OperationType::ADD, kLargeModelSize);
+    if (checkEarlyTermination(testModelAdd)) return;
+
+    // Save the testModelMul compilation to cache.
+    auto modelCacheMul = mModelCache;
+    for (auto& cache : modelCacheMul) {
+        cache[0].append("_mul");
+    }
+    {
+        hidl_vec<hidl_handle> modelCache, dataCache;
+        createCacheHandles(modelCacheMul, AccessMode::READ_WRITE, &modelCache);
+        createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
+        saveModelToCache(testModelMul, modelCache, dataCache);
+    }
+
+    // Use a different token for testModelAdd.
+    mToken[0]++;
+
+    // This test is probabilistic, so we run it multiple times.
+    for (uint32_t i = 0; i < kNumIterationsTOCTOU; i++) {
+        // Save the testModelAdd compilation to cache.
+        {
+            hidl_vec<hidl_handle> modelCache, dataCache;
+            createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
+            createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
+            saveModelToCache(testModelAdd, modelCache, dataCache);
+        }
+
+        // Retrieve preparedModel from cache.
+        {
+            sp<IPreparedModel> preparedModel = nullptr;
+            ErrorStatus status;
+            hidl_vec<hidl_handle> modelCache, dataCache;
+            createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
+            createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
+
+            // Spawn a thread to copy the cache content concurrently while preparing from cache.
+            std::thread thread(copyCacheFiles, std::cref(modelCacheMul), std::cref(mModelCache));
+            prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+            thread.join();
+
+            // The preparation may fail or succeed, but must not crash. If the preparation succeeds,
+            // the prepared model must be executed with the correct result and not crash.
+            if (status != ErrorStatus::NONE) {
+                ASSERT_EQ(preparedModel, nullptr);
+            } else {
+                ASSERT_NE(preparedModel, nullptr);
+                generated_tests::EvaluatePreparedModel(
+                        preparedModel, [](int) { return false; },
+                        getLargeModelExamples(kLargeModelSize),
+                        testModelAdd.relaxComputationFloat32toFloat16,
+                        /*testDynamicOutputShape=*/false);
+            }
+        }
+    }
+}
+
+TEST_P(CompilationCachingTest, ReplaceSecuritySensitiveCache) {
+    if (!mIsCachingSupported) return;
+
+    // Create test models and check if fully supported by the service.
+    const Model testModelMul = createLargeTestModel(OperationType::MUL, kLargeModelSize);
+    if (checkEarlyTermination(testModelMul)) return;
+    const Model testModelAdd = createLargeTestModel(OperationType::ADD, kLargeModelSize);
+    if (checkEarlyTermination(testModelAdd)) return;
+
+    // Save the testModelMul compilation to cache.
+    auto modelCacheMul = mModelCache;
+    for (auto& cache : modelCacheMul) {
+        cache[0].append("_mul");
+    }
+    {
+        hidl_vec<hidl_handle> modelCache, dataCache;
+        createCacheHandles(modelCacheMul, AccessMode::READ_WRITE, &modelCache);
+        createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
+        saveModelToCache(testModelMul, modelCache, dataCache);
+    }
+
+    // Use a different token for testModelAdd.
+    mToken[0]++;
+
+    // Save the testModelAdd compilation to cache.
+    {
         hidl_vec<hidl_handle> modelCache, dataCache;
         createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
         createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
-        saveModelToCache(testModel, modelCache, dataCache, &supported);
-        if (checkEarlyTermination(supported)) return;
+        saveModelToCache(testModelAdd, modelCache, dataCache);
     }
 
-    // Randomly flip one single bit in mToken.
-    uint32_t ind = getRandomInt(0u, static_cast<uint32_t>(Constant::BYTE_SIZE_OF_CACHE_TOKEN) - 1);
-    mToken[ind] ^= (1U << getRandomInt(0, 7));
+    // Replace the model cache of testModelAdd with testModelMul.
+    copyCacheFiles(modelCacheMul, mModelCache);
 
     // Retrieve the preparedModel from cache, expect failure.
     {
@@ -1001,8 +1261,153 @@
     }
 }
 
+static const auto kOperandTypeChoices =
+        ::testing::Values(OperandType::TENSOR_FLOAT32, OperandType::TENSOR_QUANT8_ASYMM);
+
+INSTANTIATE_TEST_CASE_P(TestCompilationCaching, CompilationCachingTest, kOperandTypeChoices);
+
+class CompilationCachingSecurityTest
+    : public CompilationCachingTestBase,
+      public ::testing::WithParamInterface<std::tuple<OperandType, uint32_t>> {
+  protected:
+    CompilationCachingSecurityTest() : CompilationCachingTestBase(std::get<0>(GetParam())) {}
+
+    void SetUp() {
+        CompilationCachingTestBase::SetUp();
+        generator.seed(kSeed);
+    }
+
+    // Get a random integer within a closed range [lower, upper].
+    template <typename T>
+    T getRandomInt(T lower, T upper) {
+        std::uniform_int_distribution<T> dis(lower, upper);
+        return dis(generator);
+    }
+
+    // Randomly flip one single bit of the cache entry.
+    void flipOneBitOfCache(const std::string& filename, bool* skip) {
+        FILE* pFile = fopen(filename.c_str(), "r+");
+        ASSERT_EQ(fseek(pFile, 0, SEEK_END), 0);
+        long int fileSize = ftell(pFile);
+        if (fileSize == 0) {
+            fclose(pFile);
+            *skip = true;
+            return;
+        }
+        ASSERT_EQ(fseek(pFile, getRandomInt(0l, fileSize - 1), SEEK_SET), 0);
+        int readByte = fgetc(pFile);
+        ASSERT_NE(readByte, EOF);
+        ASSERT_EQ(fseek(pFile, -1, SEEK_CUR), 0);
+        ASSERT_NE(fputc(static_cast<uint8_t>(readByte) ^ (1U << getRandomInt(0, 7)), pFile), EOF);
+        fclose(pFile);
+        *skip = false;
+    }
+
+    // Randomly append bytes to the cache entry.
+    void appendBytesToCache(const std::string& filename, bool* skip) {
+        FILE* pFile = fopen(filename.c_str(), "a");
+        uint32_t appendLength = getRandomInt(1, 256);
+        for (uint32_t i = 0; i < appendLength; i++) {
+            ASSERT_NE(fputc(getRandomInt<uint8_t>(0, 255), pFile), EOF);
+        }
+        fclose(pFile);
+        *skip = false;
+    }
+
+    enum class ExpectedResult { GENERAL_FAILURE, NOT_CRASH };
+
+    // Test if the driver behaves as expected when given corrupted cache or token.
+    // The modifier will be invoked after save to cache but before prepare from cache.
+    // The modifier accepts one pointer argument "skip" as the returning value, indicating
+    // whether the test should be skipped or not.
+    void testCorruptedCache(ExpectedResult expected, std::function<void(bool*)> modifier) {
+        const Model testModel = createTestModel();
+        if (checkEarlyTermination(testModel)) return;
+
+        // Save the compilation to cache.
+        {
+            hidl_vec<hidl_handle> modelCache, dataCache;
+            createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
+            createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
+            saveModelToCache(testModel, modelCache, dataCache);
+        }
+
+        bool skip = false;
+        modifier(&skip);
+        if (skip) return;
+
+        // Retrieve preparedModel from cache.
+        {
+            sp<IPreparedModel> preparedModel = nullptr;
+            ErrorStatus status;
+            hidl_vec<hidl_handle> modelCache, dataCache;
+            createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
+            createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
+            prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+
+            switch (expected) {
+                case ExpectedResult::GENERAL_FAILURE:
+                    ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
+                    ASSERT_EQ(preparedModel, nullptr);
+                    break;
+                case ExpectedResult::NOT_CRASH:
+                    ASSERT_EQ(preparedModel == nullptr, status != ErrorStatus::NONE);
+                    break;
+                default:
+                    FAIL();
+            }
+        }
+    }
+
+    const uint32_t kSeed = std::get<1>(GetParam());
+    std::mt19937 generator;
+};
+
+TEST_P(CompilationCachingSecurityTest, CorruptedModelCache) {
+    if (!mIsCachingSupported) return;
+    for (uint32_t i = 0; i < mNumModelCache; i++) {
+        testCorruptedCache(ExpectedResult::GENERAL_FAILURE,
+                           [this, i](bool* skip) { flipOneBitOfCache(mModelCache[i][0], skip); });
+    }
+}
+
+TEST_P(CompilationCachingSecurityTest, WrongLengthModelCache) {
+    if (!mIsCachingSupported) return;
+    for (uint32_t i = 0; i < mNumModelCache; i++) {
+        testCorruptedCache(ExpectedResult::GENERAL_FAILURE,
+                           [this, i](bool* skip) { appendBytesToCache(mModelCache[i][0], skip); });
+    }
+}
+
+TEST_P(CompilationCachingSecurityTest, CorruptedDataCache) {
+    if (!mIsCachingSupported) return;
+    for (uint32_t i = 0; i < mNumDataCache; i++) {
+        testCorruptedCache(ExpectedResult::NOT_CRASH,
+                           [this, i](bool* skip) { flipOneBitOfCache(mDataCache[i][0], skip); });
+    }
+}
+
+TEST_P(CompilationCachingSecurityTest, WrongLengthDataCache) {
+    if (!mIsCachingSupported) return;
+    for (uint32_t i = 0; i < mNumDataCache; i++) {
+        testCorruptedCache(ExpectedResult::NOT_CRASH,
+                           [this, i](bool* skip) { appendBytesToCache(mDataCache[i][0], skip); });
+    }
+}
+
+TEST_P(CompilationCachingSecurityTest, WrongToken) {
+    if (!mIsCachingSupported) return;
+    testCorruptedCache(ExpectedResult::GENERAL_FAILURE, [this](bool* skip) {
+        // Randomly flip one single bit in mToken.
+        uint32_t ind =
+                getRandomInt(0u, static_cast<uint32_t>(Constant::BYTE_SIZE_OF_CACHE_TOKEN) - 1);
+        mToken[ind] ^= (1U << getRandomInt(0, 7));
+        *skip = false;
+    });
+}
+
 INSTANTIATE_TEST_CASE_P(TestCompilationCaching, CompilationCachingSecurityTest,
-                        ::testing::Range(0U, 10U));
+                        ::testing::Combine(kOperandTypeChoices, ::testing::Range(0U, 10U)));
 
 }  // namespace functional
 }  // namespace vts
diff --git a/neuralnetworks/1.2/vts/functional/ValidateBurst.cpp b/neuralnetworks/1.2/vts/functional/ValidateBurst.cpp
new file mode 100644
index 0000000..43bd400
--- /dev/null
+++ b/neuralnetworks/1.2/vts/functional/ValidateBurst.cpp
@@ -0,0 +1,337 @@
+/*
+ * Copyright (C) 2019 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "neuralnetworks_hidl_hal_test"
+
+#include "VtsHalNeuralnetworks.h"
+
+#include "Callbacks.h"
+#include "ExecutionBurstController.h"
+#include "ExecutionBurstServer.h"
+#include "TestHarness.h"
+#include "Utils.h"
+
+#include <android-base/logging.h>
+
+namespace android {
+namespace hardware {
+namespace neuralnetworks {
+namespace V1_2 {
+namespace vts {
+namespace functional {
+
+using ::android::nn::ExecutionBurstController;
+using ::android::nn::RequestChannelSender;
+using ::android::nn::ResultChannelReceiver;
+using ExecutionBurstCallback = ::android::nn::ExecutionBurstController::ExecutionBurstCallback;
+
+// This constant value represents the length of an FMQ that is large enough to
+// return a result from a burst execution for all of the generated test cases.
+constexpr size_t kExecutionBurstChannelLength = 1024;
+
+// This constant value represents a length of an FMQ that is not large enough
+// to return a result from a burst execution for some of the generated test
+// cases.
+constexpr size_t kExecutionBurstChannelSmallLength = 8;
+
+///////////////////////// UTILITY FUNCTIONS /////////////////////////
+
+static bool badTiming(Timing timing) {
+    return timing.timeOnDevice == UINT64_MAX && timing.timeInDriver == UINT64_MAX;
+}
+
+static void createBurst(const sp<IPreparedModel>& preparedModel, const sp<IBurstCallback>& callback,
+                        std::unique_ptr<RequestChannelSender>* sender,
+                        std::unique_ptr<ResultChannelReceiver>* receiver,
+                        sp<IBurstContext>* context,
+                        size_t resultChannelLength = kExecutionBurstChannelLength) {
+    ASSERT_NE(nullptr, preparedModel.get());
+    ASSERT_NE(nullptr, sender);
+    ASSERT_NE(nullptr, receiver);
+    ASSERT_NE(nullptr, context);
+
+    // create FMQ objects
+    auto [fmqRequestChannel, fmqRequestDescriptor] =
+            RequestChannelSender::create(kExecutionBurstChannelLength, /*blocking=*/true);
+    auto [fmqResultChannel, fmqResultDescriptor] =
+            ResultChannelReceiver::create(resultChannelLength, /*blocking=*/true);
+    ASSERT_NE(nullptr, fmqRequestChannel.get());
+    ASSERT_NE(nullptr, fmqResultChannel.get());
+    ASSERT_NE(nullptr, fmqRequestDescriptor);
+    ASSERT_NE(nullptr, fmqResultDescriptor);
+
+    // configure burst
+    ErrorStatus errorStatus;
+    sp<IBurstContext> burstContext;
+    const Return<void> ret = preparedModel->configureExecutionBurst(
+            callback, *fmqRequestDescriptor, *fmqResultDescriptor,
+            [&errorStatus, &burstContext](ErrorStatus status, const sp<IBurstContext>& context) {
+                errorStatus = status;
+                burstContext = context;
+            });
+    ASSERT_TRUE(ret.isOk());
+    ASSERT_EQ(ErrorStatus::NONE, errorStatus);
+    ASSERT_NE(nullptr, burstContext.get());
+
+    // return values
+    *sender = std::move(fmqRequestChannel);
+    *receiver = std::move(fmqResultChannel);
+    *context = burstContext;
+}
+
+static void createBurstWithResultChannelLength(
+        const sp<IPreparedModel>& preparedModel, size_t resultChannelLength,
+        std::shared_ptr<ExecutionBurstController>* controller) {
+    ASSERT_NE(nullptr, preparedModel.get());
+    ASSERT_NE(nullptr, controller);
+
+    // create FMQ objects
+    std::unique_ptr<RequestChannelSender> sender;
+    std::unique_ptr<ResultChannelReceiver> receiver;
+    sp<ExecutionBurstCallback> callback = new ExecutionBurstCallback();
+    sp<IBurstContext> context;
+    ASSERT_NO_FATAL_FAILURE(createBurst(preparedModel, callback, &sender, &receiver, &context,
+                                        resultChannelLength));
+    ASSERT_NE(nullptr, sender.get());
+    ASSERT_NE(nullptr, receiver.get());
+    ASSERT_NE(nullptr, context.get());
+
+    // return values
+    *controller = std::make_shared<ExecutionBurstController>(std::move(sender), std::move(receiver),
+                                                             context, callback);
+}
+
+// Primary validation function. This function will take a valid serialized
+// request, apply a mutation to it to invalidate the serialized request, then
+// pass it to interface calls that use the serialized request. Note that the
+// serialized request here is passed by value, and any mutation to the
+// serialized request does not leave this function.
+static void validate(RequestChannelSender* sender, ResultChannelReceiver* receiver,
+                     const std::string& message, std::vector<FmqRequestDatum> serialized,
+                     const std::function<void(std::vector<FmqRequestDatum>*)>& mutation) {
+    mutation(&serialized);
+
+    // skip if packet is too large to send
+    if (serialized.size() > kExecutionBurstChannelLength) {
+        return;
+    }
+
+    SCOPED_TRACE(message);
+
+    // send invalid packet
+    ASSERT_TRUE(sender->sendPacket(serialized));
+
+    // receive error
+    auto results = receiver->getBlocking();
+    ASSERT_TRUE(results.has_value());
+    const auto [status, outputShapes, timing] = std::move(*results);
+    EXPECT_NE(ErrorStatus::NONE, status);
+    EXPECT_EQ(0u, outputShapes.size());
+    EXPECT_TRUE(badTiming(timing));
+}
+
+// For validation, valid packet entries are mutated to invalid packet entries,
+// or invalid packet entries are inserted into valid packets. This function
+// creates pre-set invalid packet entries for convenience.
+static std::vector<FmqRequestDatum> createBadRequestPacketEntries() {
+    const FmqRequestDatum::PacketInformation packetInformation = {
+            /*.packetSize=*/10, /*.numberOfInputOperands=*/10, /*.numberOfOutputOperands=*/10,
+            /*.numberOfPools=*/10};
+    const FmqRequestDatum::OperandInformation operandInformation = {
+            /*.hasNoValue=*/false, /*.location=*/{}, /*.numberOfDimensions=*/10};
+    const int32_t invalidPoolIdentifier = std::numeric_limits<int32_t>::max();
+    std::vector<FmqRequestDatum> bad(7);
+    bad[0].packetInformation(packetInformation);
+    bad[1].inputOperandInformation(operandInformation);
+    bad[2].inputOperandDimensionValue(0);
+    bad[3].outputOperandInformation(operandInformation);
+    bad[4].outputOperandDimensionValue(0);
+    bad[5].poolIdentifier(invalidPoolIdentifier);
+    bad[6].measureTiming(MeasureTiming::YES);
+    return bad;
+}
+
+// For validation, valid packet entries are mutated to invalid packet entries,
+// or invalid packet entries are inserted into valid packets. This function
+// retrieves pre-set invalid packet entries for convenience. This function
+// caches these data so they can be reused on subsequent validation checks.
+static const std::vector<FmqRequestDatum>& getBadRequestPacketEntries() {
+    static const std::vector<FmqRequestDatum> bad = createBadRequestPacketEntries();
+    return bad;
+}
+
+///////////////////////// REMOVE DATUM ////////////////////////////////////
+
+static void removeDatumTest(RequestChannelSender* sender, ResultChannelReceiver* receiver,
+                            const std::vector<FmqRequestDatum>& serialized) {
+    for (size_t index = 0; index < serialized.size(); ++index) {
+        const std::string message = "removeDatum: removed datum at index " + std::to_string(index);
+        validate(sender, receiver, message, serialized,
+                 [index](std::vector<FmqRequestDatum>* serialized) {
+                     serialized->erase(serialized->begin() + index);
+                 });
+    }
+}
+
+///////////////////////// ADD DATUM ////////////////////////////////////
+
+static void addDatumTest(RequestChannelSender* sender, ResultChannelReceiver* receiver,
+                         const std::vector<FmqRequestDatum>& serialized) {
+    const std::vector<FmqRequestDatum>& extra = getBadRequestPacketEntries();
+    for (size_t index = 0; index <= serialized.size(); ++index) {
+        for (size_t type = 0; type < extra.size(); ++type) {
+            const std::string message = "addDatum: added datum type " + std::to_string(type) +
+                                        " at index " + std::to_string(index);
+            validate(sender, receiver, message, serialized,
+                     [index, type, &extra](std::vector<FmqRequestDatum>* serialized) {
+                         serialized->insert(serialized->begin() + index, extra[type]);
+                     });
+        }
+    }
+}
+
+///////////////////////// MUTATE DATUM ////////////////////////////////////
+
+static bool interestingCase(const FmqRequestDatum& lhs, const FmqRequestDatum& rhs) {
+    using Discriminator = FmqRequestDatum::hidl_discriminator;
+
+    const bool differentValues = (lhs != rhs);
+    const bool sameDiscriminator = (lhs.getDiscriminator() == rhs.getDiscriminator());
+    const auto discriminator = rhs.getDiscriminator();
+    const bool isDimensionValue = (discriminator == Discriminator::inputOperandDimensionValue ||
+                                   discriminator == Discriminator::outputOperandDimensionValue);
+
+    return differentValues && !(sameDiscriminator && isDimensionValue);
+}
+
+static void mutateDatumTest(RequestChannelSender* sender, ResultChannelReceiver* receiver,
+                            const std::vector<FmqRequestDatum>& serialized) {
+    const std::vector<FmqRequestDatum>& change = getBadRequestPacketEntries();
+    for (size_t index = 0; index < serialized.size(); ++index) {
+        for (size_t type = 0; type < change.size(); ++type) {
+            if (interestingCase(serialized[index], change[type])) {
+                const std::string message = "mutateDatum: changed datum at index " +
+                                            std::to_string(index) + " to datum type " +
+                                            std::to_string(type);
+                validate(sender, receiver, message, serialized,
+                         [index, type, &change](std::vector<FmqRequestDatum>* serialized) {
+                             (*serialized)[index] = change[type];
+                         });
+            }
+        }
+    }
+}
+
+///////////////////////// BURST VALIATION TESTS ////////////////////////////////////
+
+static void validateBurstSerialization(const sp<IPreparedModel>& preparedModel,
+                                       const std::vector<Request>& requests) {
+    // create burst
+    std::unique_ptr<RequestChannelSender> sender;
+    std::unique_ptr<ResultChannelReceiver> receiver;
+    sp<ExecutionBurstCallback> callback = new ExecutionBurstCallback();
+    sp<IBurstContext> context;
+    ASSERT_NO_FATAL_FAILURE(createBurst(preparedModel, callback, &sender, &receiver, &context));
+    ASSERT_NE(nullptr, sender.get());
+    ASSERT_NE(nullptr, receiver.get());
+    ASSERT_NE(nullptr, context.get());
+
+    // validate each request
+    for (const Request& request : requests) {
+        // load memory into callback slots
+        std::vector<intptr_t> keys;
+        keys.reserve(request.pools.size());
+        std::transform(request.pools.begin(), request.pools.end(), std::back_inserter(keys),
+                       [](const auto& pool) { return reinterpret_cast<intptr_t>(&pool); });
+        const std::vector<int32_t> slots = callback->getSlots(request.pools, keys);
+
+        // ensure slot std::numeric_limits<int32_t>::max() doesn't exist (for
+        // subsequent slot validation testing)
+        ASSERT_TRUE(std::all_of(slots.begin(), slots.end(), [](int32_t slot) {
+            return slot != std::numeric_limits<int32_t>::max();
+        }));
+
+        // serialize the request
+        const auto serialized = ::android::nn::serialize(request, MeasureTiming::YES, slots);
+
+        // validations
+        removeDatumTest(sender.get(), receiver.get(), serialized);
+        addDatumTest(sender.get(), receiver.get(), serialized);
+        mutateDatumTest(sender.get(), receiver.get(), serialized);
+    }
+}
+
+// This test validates that when the Result message size exceeds length of the
+// result FMQ, the service instance gracefully fails and returns an error.
+static void validateBurstFmqLength(const sp<IPreparedModel>& preparedModel,
+                                   const std::vector<Request>& requests) {
+    // create regular burst
+    std::shared_ptr<ExecutionBurstController> controllerRegular;
+    ASSERT_NO_FATAL_FAILURE(createBurstWithResultChannelLength(
+            preparedModel, kExecutionBurstChannelLength, &controllerRegular));
+    ASSERT_NE(nullptr, controllerRegular.get());
+
+    // create burst with small output channel
+    std::shared_ptr<ExecutionBurstController> controllerSmall;
+    ASSERT_NO_FATAL_FAILURE(createBurstWithResultChannelLength(
+            preparedModel, kExecutionBurstChannelSmallLength, &controllerSmall));
+    ASSERT_NE(nullptr, controllerSmall.get());
+
+    // validate each request
+    for (const Request& request : requests) {
+        // load memory into callback slots
+        std::vector<intptr_t> keys(request.pools.size());
+        for (size_t i = 0; i < keys.size(); ++i) {
+            keys[i] = reinterpret_cast<intptr_t>(&request.pools[i]);
+        }
+
+        // collect serialized result by running regular burst
+        const auto [statusRegular, outputShapesRegular, timingRegular] =
+                controllerRegular->compute(request, MeasureTiming::NO, keys);
+
+        // skip test if regular burst output isn't useful for testing a failure
+        // caused by having too small of a length for the result FMQ
+        const std::vector<FmqResultDatum> serialized =
+                ::android::nn::serialize(statusRegular, outputShapesRegular, timingRegular);
+        if (statusRegular != ErrorStatus::NONE ||
+            serialized.size() <= kExecutionBurstChannelSmallLength) {
+            continue;
+        }
+
+        // by this point, execution should fail because the result channel isn't
+        // large enough to return the serialized result
+        const auto [statusSmall, outputShapesSmall, timingSmall] =
+                controllerSmall->compute(request, MeasureTiming::NO, keys);
+        EXPECT_NE(ErrorStatus::NONE, statusSmall);
+        EXPECT_EQ(0u, outputShapesSmall.size());
+        EXPECT_TRUE(badTiming(timingSmall));
+    }
+}
+
+///////////////////////////// ENTRY POINT //////////////////////////////////
+
+void ValidationTest::validateBurst(const sp<IPreparedModel>& preparedModel,
+                                   const std::vector<Request>& requests) {
+    ASSERT_NO_FATAL_FAILURE(validateBurstSerialization(preparedModel, requests));
+    ASSERT_NO_FATAL_FAILURE(validateBurstFmqLength(preparedModel, requests));
+}
+
+}  // namespace functional
+}  // namespace vts
+}  // namespace V1_2
+}  // namespace neuralnetworks
+}  // namespace hardware
+}  // namespace android
diff --git a/neuralnetworks/1.2/vts/functional/ValidateRequest.cpp b/neuralnetworks/1.2/vts/functional/ValidateRequest.cpp
index 870d017..9703c2d 100644
--- a/neuralnetworks/1.2/vts/functional/ValidateRequest.cpp
+++ b/neuralnetworks/1.2/vts/functional/ValidateRequest.cpp
@@ -35,9 +35,7 @@
 namespace functional {
 
 using ::android::hardware::neuralnetworks::V1_2::implementation::ExecutionCallback;
-using ::android::hardware::neuralnetworks::V1_2::implementation::PreparedModelCallback;
 using ::android::hidl::memory::V1_0::IMemory;
-using HidlToken = hidl_array<uint8_t, static_cast<uint32_t>(Constant::BYTE_SIZE_OF_CACHE_TOKEN)>;
 using test_helper::for_all;
 using test_helper::MixedTyped;
 using test_helper::MixedTypedExample;
@@ -48,55 +46,6 @@
     return timing.timeOnDevice == UINT64_MAX && timing.timeInDriver == UINT64_MAX;
 }
 
-static void createPreparedModel(const sp<IDevice>& device, const Model& model,
-                                sp<IPreparedModel>* preparedModel) {
-    ASSERT_NE(nullptr, preparedModel);
-
-    // see if service can handle model
-    bool fullySupportsModel = false;
-    Return<void> supportedOpsLaunchStatus = device->getSupportedOperations_1_2(
-        model, [&fullySupportsModel](ErrorStatus status, const hidl_vec<bool>& supported) {
-            ASSERT_EQ(ErrorStatus::NONE, status);
-            ASSERT_NE(0ul, supported.size());
-            fullySupportsModel =
-                std::all_of(supported.begin(), supported.end(), [](bool valid) { return valid; });
-        });
-    ASSERT_TRUE(supportedOpsLaunchStatus.isOk());
-
-    // launch prepare model
-    sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
-    ASSERT_NE(nullptr, preparedModelCallback.get());
-    Return<ErrorStatus> prepareLaunchStatus = device->prepareModel_1_2(
-            model, ExecutionPreference::FAST_SINGLE_ANSWER, hidl_vec<hidl_handle>(),
-            hidl_vec<hidl_handle>(), HidlToken(), preparedModelCallback);
-    ASSERT_TRUE(prepareLaunchStatus.isOk());
-    ASSERT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(prepareLaunchStatus));
-
-    // retrieve prepared model
-    preparedModelCallback->wait();
-    ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
-    *preparedModel = getPreparedModel_1_2(preparedModelCallback);
-
-    // The getSupportedOperations_1_2 call returns a list of operations that are
-    // guaranteed not to fail if prepareModel_1_2 is called, and
-    // 'fullySupportsModel' is true i.f.f. the entire model is guaranteed.
-    // If a driver has any doubt that it can prepare an operation, it must
-    // return false. So here, if a driver isn't sure if it can support an
-    // operation, but reports that it successfully prepared the model, the test
-    // can continue.
-    if (!fullySupportsModel && prepareReturnStatus != ErrorStatus::NONE) {
-        ASSERT_EQ(nullptr, preparedModel->get());
-        LOG(INFO) << "NN VTS: Unable to test Request validation because vendor service cannot "
-                     "prepare model that it does not support.";
-        std::cout << "[          ]   Unable to test Request validation because vendor service "
-                     "cannot prepare model that it does not support."
-                  << std::endl;
-        return;
-    }
-    ASSERT_EQ(ErrorStatus::NONE, prepareReturnStatus);
-    ASSERT_NE(nullptr, preparedModel->get());
-}
-
 // Primary validation function. This function will take a valid request, apply a
 // mutation to it to invalidate the request, then pass it to interface calls
 // that use the request. Note that the request here is passed by value, and any
@@ -316,14 +265,8 @@
     return requests;
 }
 
-void ValidationTest::validateRequests(const Model& model, const std::vector<Request>& requests) {
-    // create IPreparedModel
-    sp<IPreparedModel> preparedModel;
-    ASSERT_NO_FATAL_FAILURE(createPreparedModel(device, model, &preparedModel));
-    if (preparedModel == nullptr) {
-        return;
-    }
-
+void ValidationTest::validateRequests(const sp<IPreparedModel>& preparedModel,
+                                      const std::vector<Request>& requests) {
     // validate each request
     for (const Request& request : requests) {
         removeInputTest(preparedModel, request);
diff --git a/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.cpp b/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.cpp
index 4728c28..4ddefe8 100644
--- a/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.cpp
+++ b/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.cpp
@@ -18,6 +18,10 @@
 
 #include "VtsHalNeuralnetworks.h"
 
+#include <android-base/logging.h>
+
+#include "Callbacks.h"
+
 namespace android {
 namespace hardware {
 namespace neuralnetworks {
@@ -25,6 +29,60 @@
 namespace vts {
 namespace functional {
 
+using ::android::hardware::neuralnetworks::V1_2::implementation::PreparedModelCallback;
+using HidlToken = hidl_array<uint8_t, static_cast<uint32_t>(Constant::BYTE_SIZE_OF_CACHE_TOKEN)>;
+using V1_1::ExecutionPreference;
+
+// internal helper function
+static void createPreparedModel(const sp<IDevice>& device, const Model& model,
+                                sp<IPreparedModel>* preparedModel) {
+    ASSERT_NE(nullptr, preparedModel);
+
+    // see if service can handle model
+    bool fullySupportsModel = false;
+    Return<void> supportedOpsLaunchStatus = device->getSupportedOperations_1_2(
+            model, [&fullySupportsModel](ErrorStatus status, const hidl_vec<bool>& supported) {
+                ASSERT_EQ(ErrorStatus::NONE, status);
+                ASSERT_NE(0ul, supported.size());
+                fullySupportsModel = std::all_of(supported.begin(), supported.end(),
+                                                 [](bool valid) { return valid; });
+            });
+    ASSERT_TRUE(supportedOpsLaunchStatus.isOk());
+
+    // launch prepare model
+    sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
+    ASSERT_NE(nullptr, preparedModelCallback.get());
+    Return<ErrorStatus> prepareLaunchStatus = device->prepareModel_1_2(
+            model, ExecutionPreference::FAST_SINGLE_ANSWER, hidl_vec<hidl_handle>(),
+            hidl_vec<hidl_handle>(), HidlToken(), preparedModelCallback);
+    ASSERT_TRUE(prepareLaunchStatus.isOk());
+    ASSERT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(prepareLaunchStatus));
+
+    // retrieve prepared model
+    preparedModelCallback->wait();
+    ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
+    *preparedModel = getPreparedModel_1_2(preparedModelCallback);
+
+    // The getSupportedOperations_1_2 call returns a list of operations that are
+    // guaranteed not to fail if prepareModel_1_2 is called, and
+    // 'fullySupportsModel' is true i.f.f. the entire model is guaranteed.
+    // If a driver has any doubt that it can prepare an operation, it must
+    // return false. So here, if a driver isn't sure if it can support an
+    // operation, but reports that it successfully prepared the model, the test
+    // can continue.
+    if (!fullySupportsModel && prepareReturnStatus != ErrorStatus::NONE) {
+        ASSERT_EQ(nullptr, preparedModel->get());
+        LOG(INFO) << "NN VTS: Unable to test Request validation because vendor service cannot "
+                     "prepare model that it does not support.";
+        std::cout << "[          ]   Unable to test Request validation because vendor service "
+                     "cannot prepare model that it does not support."
+                  << std::endl;
+        return;
+    }
+    ASSERT_EQ(ErrorStatus::NONE, prepareReturnStatus);
+    ASSERT_NE(nullptr, preparedModel->get());
+}
+
 // A class for test environment setup
 NeuralnetworksHidlEnvironment::NeuralnetworksHidlEnvironment() {}
 
@@ -68,6 +126,20 @@
     ::testing::VtsHalHidlTargetTestBase::TearDown();
 }
 
+void ValidationTest::validateEverything(const Model& model, const std::vector<Request>& requests) {
+    validateModel(model);
+
+    // create IPreparedModel
+    sp<IPreparedModel> preparedModel;
+    ASSERT_NO_FATAL_FAILURE(createPreparedModel(device, model, &preparedModel));
+    if (preparedModel == nullptr) {
+        return;
+    }
+
+    validateRequests(preparedModel, requests);
+    validateBurst(preparedModel, requests);
+}
+
 sp<IPreparedModel> getPreparedModel_1_2(
     const sp<V1_2::implementation::PreparedModelCallback>& callback) {
     sp<V1_0::IPreparedModel> preparedModelV1_0 = callback->getPreparedModel();
diff --git a/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.h b/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.h
index 404eec0..8d1acbe 100644
--- a/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.h
+++ b/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.h
@@ -72,8 +72,14 @@
 // Tag for the validation tests
 class ValidationTest : public NeuralnetworksHidlTest {
    protected:
-    void validateModel(const Model& model);
-    void validateRequests(const Model& model, const std::vector<Request>& request);
+     void validateEverything(const Model& model, const std::vector<Request>& requests);
+
+   private:
+     void validateModel(const Model& model);
+     void validateRequests(const sp<IPreparedModel>& preparedModel,
+                           const std::vector<Request>& requests);
+     void validateBurst(const sp<IPreparedModel>& preparedModel,
+                        const std::vector<Request>& requests);
 };
 
 // Tag for the generated tests
diff --git a/wifi/1.2/default/wifi_legacy_hal.cpp b/wifi/1.2/default/wifi_legacy_hal.cpp
index 55ec96d..375204c 100644
--- a/wifi/1.2/default/wifi_legacy_hal.cpp
+++ b/wifi/1.2/default/wifi_legacy_hal.cpp
@@ -550,7 +550,6 @@
                 }
                 // Fall through if failed. Failure to retrieve cached scan
                 // results should trigger a background scan failure.
-                [[fallthrough]];
                 case WIFI_SCAN_FAILED:
                     on_failure_user_callback(id);
                     on_gscan_event_internal_callback = nullptr;