diff --git a/neuralnetworks/aidl/utils/test/MockPreparedModel.h b/neuralnetworks/aidl/utils/test/MockPreparedModel.h
index 545b491..36e0ec3 100644
--- a/neuralnetworks/aidl/utils/test/MockPreparedModel.h
+++ b/neuralnetworks/aidl/utils/test/MockPreparedModel.h
@@ -39,6 +39,8 @@
                  bool measureTiming, int64_t deadline, int64_t loopTimeoutDuration,
                  int64_t duration, FencedExecutionResult* fencedExecutionResult),
                 (override));
+    MOCK_METHOD(ndk::ScopedAStatus, configureExecutionBurst, (std::shared_ptr<IBurst> * burst),
+                (override));
 };
 
 inline std::shared_ptr<MockPreparedModel> MockPreparedModel::create() {
diff --git a/neuralnetworks/aidl/vts/functional/GeneratedTestHarness.cpp b/neuralnetworks/aidl/vts/functional/GeneratedTestHarness.cpp
index 7a042ed..2dd02dd 100644
--- a/neuralnetworks/aidl/vts/functional/GeneratedTestHarness.cpp
+++ b/neuralnetworks/aidl/vts/functional/GeneratedTestHarness.cpp
@@ -17,6 +17,7 @@
 #include "GeneratedTestHarness.h"
 
 #include <aidl/android/hardware/neuralnetworks/ErrorStatus.h>
+#include <aidl/android/hardware/neuralnetworks/RequestMemoryPool.h>
 #include <android-base/logging.h>
 #include <android/binder_auto_utils.h>
 #include <android/sync.h>
@@ -582,6 +583,53 @@
             }
             break;
         }
+        case Executor::BURST: {
+            SCOPED_TRACE("burst");
+
+            // create burst
+            std::shared_ptr<IBurst> burst;
+            auto ret = preparedModel->configureExecutionBurst(&burst);
+            ASSERT_TRUE(ret.isOk()) << ret.getDescription();
+            ASSERT_NE(nullptr, burst.get());
+
+            // associate a unique slot with each memory pool
+            int64_t currentSlot = 0;
+            std::vector<int64_t> slots;
+            slots.reserve(request.pools.size());
+            for (const auto& pool : request.pools) {
+                if (pool.getTag() == RequestMemoryPool::Tag::pool) {
+                    slots.push_back(currentSlot++);
+                } else {
+                    EXPECT_EQ(pool.getTag(), RequestMemoryPool::Tag::token);
+                    slots.push_back(-1);
+                }
+            }
+
+            ExecutionResult executionResult;
+            // execute
+            ret = burst->executeSynchronously(request, slots, testConfig.measureTiming, kNoDeadline,
+                                              loopTimeoutDuration, &executionResult);
+            ASSERT_TRUE(ret.isOk() || ret.getExceptionCode() == EX_SERVICE_SPECIFIC)
+                    << ret.getDescription();
+            if (ret.isOk()) {
+                executionStatus = executionResult.outputSufficientSize
+                                          ? ErrorStatus::NONE
+                                          : ErrorStatus::OUTPUT_INSUFFICIENT_SIZE;
+                outputShapes = std::move(executionResult.outputShapes);
+                timing = executionResult.timing;
+            } else {
+                executionStatus = static_cast<ErrorStatus>(ret.getServiceSpecificError());
+            }
+
+            // Mark each slot as unused after the execution. This is unnecessary because the burst
+            // is freed after this scope ends, but this is here to test the functionality.
+            for (int64_t slot : slots) {
+                ret = burst->releaseMemoryResource(slot);
+                ASSERT_TRUE(ret.isOk()) << ret.getDescription();
+            }
+
+            break;
+        }
         case Executor::FENCED: {
             SCOPED_TRACE("fenced");
             ErrorStatus result = ErrorStatus::NONE;
@@ -727,19 +775,19 @@
         case TestKind::GENERAL: {
             outputTypesList = {OutputType::FULLY_SPECIFIED};
             measureTimingList = {false, true};
-            executorList = {Executor::SYNC};
+            executorList = {Executor::SYNC, Executor::BURST};
             memoryTypeList = {MemoryType::ASHMEM};
         } break;
         case TestKind::DYNAMIC_SHAPE: {
             outputTypesList = {OutputType::UNSPECIFIED, OutputType::INSUFFICIENT};
             measureTimingList = {false, true};
-            executorList = {Executor::SYNC, Executor::FENCED};
+            executorList = {Executor::SYNC, Executor::BURST, Executor::FENCED};
             memoryTypeList = {MemoryType::ASHMEM};
         } break;
         case TestKind::MEMORY_DOMAIN: {
             outputTypesList = {OutputType::FULLY_SPECIFIED};
             measureTimingList = {false};
-            executorList = {Executor::SYNC, Executor::FENCED};
+            executorList = {Executor::SYNC, Executor::BURST, Executor::FENCED};
             memoryTypeList = {MemoryType::BLOB_AHWB, MemoryType::DEVICE};
         } break;
         case TestKind::FENCED_COMPUTE: {
@@ -755,7 +803,7 @@
         case TestKind::INTINITE_LOOP_TIMEOUT: {
             outputTypesList = {OutputType::MISSED_DEADLINE};
             measureTimingList = {false, true};
-            executorList = {Executor::SYNC, Executor::FENCED};
+            executorList = {Executor::SYNC, Executor::BURST, Executor::FENCED};
             memoryTypeList = {MemoryType::ASHMEM};
         } break;
     }
@@ -779,7 +827,7 @@
                                    const TestModel& coupledModel) {
     const std::vector<OutputType> outputTypesList = {OutputType::FULLY_SPECIFIED};
     const std::vector<bool> measureTimingList = {false, true};
-    const std::vector<Executor> executorList = {Executor::SYNC, Executor::FENCED};
+    const std::vector<Executor> executorList = {Executor::SYNC, Executor::BURST, Executor::FENCED};
 
     for (const OutputType outputType : outputTypesList) {
         for (const bool measureTiming : measureTimingList) {
diff --git a/neuralnetworks/aidl/vts/functional/MemoryDomainTests.cpp b/neuralnetworks/aidl/vts/functional/MemoryDomainTests.cpp
index 57bc1ae..627c26a 100644
--- a/neuralnetworks/aidl/vts/functional/MemoryDomainTests.cpp
+++ b/neuralnetworks/aidl/vts/functional/MemoryDomainTests.cpp
@@ -203,6 +203,10 @@
         return ndk::ScopedAStatus::fromServiceSpecificError(
                 static_cast<int32_t>(ErrorStatus::GENERAL_FAILURE));
     }
+    ndk::ScopedAStatus configureExecutionBurst(std::shared_ptr<IBurst>*) override {
+        return ndk::ScopedAStatus::fromServiceSpecificError(
+                static_cast<int32_t>(ErrorStatus::GENERAL_FAILURE));
+    }
 };
 
 template <typename... Args>
@@ -866,6 +870,9 @@
             case Executor::SYNC:
                 EXPECT_EQ(executeSync(preparedModel, request), expectedStatus);
                 break;
+            case Executor::BURST:
+                EXPECT_EQ(executeBurst(preparedModel, request), expectedStatus);
+                break;
             case Executor::FENCED:
                 EXPECT_EQ(executeFenced(preparedModel, request), expectedStatus);
                 break;
@@ -916,6 +923,35 @@
         return executionStatus;
     }
 
+    ErrorStatus executeBurst(const std::shared_ptr<IPreparedModel>& preparedModel,
+                             const Request& request) {
+        // create burst
+        std::shared_ptr<IBurst> burst;
+        auto ret = preparedModel->configureExecutionBurst(&burst);
+        EXPECT_TRUE(ret.isOk()) << ret.getDescription();
+        EXPECT_NE(nullptr, burst.get());
+        if (!ret.isOk() || burst.get() == nullptr) {
+            return ErrorStatus::GENERAL_FAILURE;
+        }
+
+        // use -1 for all memory identifier tokens
+        const std::vector<int64_t> slots(request.pools.size(), -1);
+
+        ExecutionResult executionResult;
+        ret = burst->executeSynchronously(request, slots, false, kNoDeadline,
+                                          kOmittedTimeoutDuration, &executionResult);
+
+        if (!ret.isOk()) {
+            EXPECT_EQ(ret.getExceptionCode(), EX_SERVICE_SPECIFIC);
+            return static_cast<ErrorStatus>(ret.getServiceSpecificError());
+        }
+        const ErrorStatus executionStatus = executionResult.outputSufficientSize
+                                                    ? ErrorStatus::NONE
+                                                    : ErrorStatus::OUTPUT_INSUFFICIENT_SIZE;
+        EXPECT_EQ(executionResult.timing, kNoTiming);
+        return executionStatus;
+    }
+
     const Executor kExecutor = std::get<Executor>(GetParam());
 };
 
@@ -1159,7 +1195,7 @@
                   ErrorStatus::GENERAL_FAILURE);
 }
 
-const auto kExecutorChoices = testing::Values(Executor::SYNC, Executor::FENCED);
+const auto kExecutorChoices = testing::Values(Executor::SYNC, Executor::BURST, Executor::FENCED);
 
 std::string printMemoryDomainExecutionTest(
         const testing::TestParamInfo<MemoryDomainExecutionTestParam>& info) {
diff --git a/neuralnetworks/aidl/vts/functional/QualityOfServiceTests.cpp b/neuralnetworks/aidl/vts/functional/QualityOfServiceTests.cpp
index 58db98f..9ace1a9 100644
--- a/neuralnetworks/aidl/vts/functional/QualityOfServiceTests.cpp
+++ b/neuralnetworks/aidl/vts/functional/QualityOfServiceTests.cpp
@@ -51,6 +51,10 @@
 using Results = std::tuple<ErrorStatus, std::vector<OutputShape>, Timing>;
 using MaybeResults = std::optional<Results>;
 
+using ExecutionFunction =
+        std::function<MaybeResults(const std::shared_ptr<IPreparedModel>& preparedModel,
+                                   const Request& request, int64_t deadline)>;
+
 static int64_t makeDeadline(DeadlineBoundType deadlineBoundType) {
     const auto getNanosecondsSinceEpoch = [](const auto& time) -> int64_t {
         const auto timeSinceEpoch = time.time_since_epoch();
@@ -177,13 +181,53 @@
                          std::move(executionResult.outputShapes), executionResult.timing});
 }
 
+static MaybeResults executeBurst(const std::shared_ptr<IPreparedModel>& preparedModel,
+                                 const Request& request, int64_t deadline) {
+    SCOPED_TRACE("burst");
+    const bool measure = false;
+
+    // create burst
+    std::shared_ptr<IBurst> burst;
+    auto ret = preparedModel->configureExecutionBurst(&burst);
+    EXPECT_TRUE(ret.isOk()) << ret.getDescription();
+    EXPECT_NE(nullptr, burst.get());
+    if (!ret.isOk() || burst.get() == nullptr) {
+        return std::nullopt;
+    }
+
+    // use -1 for all memory identifier tokens
+    const std::vector<int64_t> slots(request.pools.size(), -1);
+
+    // run execution
+    ExecutionResult executionResult;
+    ret = burst->executeSynchronously(request, slots, measure, deadline, kOmittedTimeoutDuration,
+                                      &executionResult);
+    EXPECT_TRUE(ret.isOk() || ret.getExceptionCode() == EX_SERVICE_SPECIFIC)
+            << ret.getDescription();
+    if (!ret.isOk()) {
+        if (ret.getExceptionCode() != EX_SERVICE_SPECIFIC) {
+            return std::nullopt;
+        }
+        return MaybeResults(
+                {static_cast<ErrorStatus>(ret.getServiceSpecificError()), {}, kNoTiming});
+    }
+
+    // return results
+    return MaybeResults({executionResult.outputSufficientSize
+                                 ? ErrorStatus::NONE
+                                 : ErrorStatus::OUTPUT_INSUFFICIENT_SIZE,
+                         std::move(executionResult.outputShapes), executionResult.timing});
+}
+
 void runExecutionTest(const std::shared_ptr<IPreparedModel>& preparedModel,
                       const TestModel& testModel, const Request& request,
-                      const ExecutionContext& context, DeadlineBoundType deadlineBound) {
+                      const ExecutionContext& context, bool synchronous,
+                      DeadlineBoundType deadlineBound) {
+    const ExecutionFunction execute = synchronous ? executeSynchronously : executeBurst;
     const auto deadline = makeDeadline(deadlineBound);
 
     // Perform execution and unpack results.
-    const auto results = executeSynchronously(preparedModel, request, deadline);
+    const auto results = execute(preparedModel, request, deadline);
     if (!results.has_value()) return;
     const auto& [status, outputShapes, timing] = results.value();
 
@@ -235,8 +279,11 @@
 void runExecutionTests(const std::shared_ptr<IPreparedModel>& preparedModel,
                        const TestModel& testModel, const Request& request,
                        const ExecutionContext& context) {
-    for (auto deadlineBound : deadlineBounds) {
-        runExecutionTest(preparedModel, testModel, request, context, deadlineBound);
+    for (bool synchronous : {false, true}) {
+        for (auto deadlineBound : deadlineBounds) {
+            runExecutionTest(preparedModel, testModel, request, context, synchronous,
+                             deadlineBound);
+        }
     }
 }
 
diff --git a/neuralnetworks/aidl/vts/functional/ValidateRequest.cpp b/neuralnetworks/aidl/vts/functional/ValidateRequest.cpp
index 3be4c1b..29e2471 100644
--- a/neuralnetworks/aidl/vts/functional/ValidateRequest.cpp
+++ b/neuralnetworks/aidl/vts/functional/ValidateRequest.cpp
@@ -16,7 +16,9 @@
 
 #define LOG_TAG "neuralnetworks_aidl_hal_test"
 
+#include <aidl/android/hardware/neuralnetworks/RequestMemoryPool.h>
 #include <android/binder_auto_utils.h>
+#include <variant>
 
 #include <chrono>
 
@@ -77,6 +79,35 @@
         ASSERT_EQ(static_cast<ErrorStatus>(executeStatus.getServiceSpecificError()),
                   ErrorStatus::INVALID_ARGUMENT);
     }
+
+    // burst
+    {
+        SCOPED_TRACE(message + " [burst]");
+
+        // create burst
+        std::shared_ptr<IBurst> burst;
+        auto ret = preparedModel->configureExecutionBurst(&burst);
+        ASSERT_TRUE(ret.isOk()) << ret.getDescription();
+        ASSERT_NE(nullptr, burst.get());
+
+        // use -1 for all memory identifier tokens
+        const std::vector<int64_t> slots(request.pools.size(), -1);
+
+        ExecutionResult executionResult;
+        const auto executeStatus = burst->executeSynchronously(
+                request, slots, measure, kNoDeadline, kOmittedTimeoutDuration, &executionResult);
+        ASSERT_FALSE(executeStatus.isOk());
+        ASSERT_EQ(executeStatus.getExceptionCode(), EX_SERVICE_SPECIFIC);
+        ASSERT_EQ(static_cast<ErrorStatus>(executeStatus.getServiceSpecificError()),
+                  ErrorStatus::INVALID_ARGUMENT);
+    }
+}
+
+std::shared_ptr<IBurst> createBurst(const std::shared_ptr<IPreparedModel>& preparedModel) {
+    std::shared_ptr<IBurst> burst;
+    const auto ret = preparedModel->configureExecutionBurst(&burst);
+    if (!ret.isOk()) return nullptr;
+    return burst;
 }
 
 ///////////////////////// REMOVE INPUT ////////////////////////////////////
@@ -110,6 +141,65 @@
     removeOutputTest(preparedModel, request);
 }
 
+void validateBurst(const std::shared_ptr<IPreparedModel>& preparedModel, const Request& request) {
+    // create burst
+    std::shared_ptr<IBurst> burst;
+    auto ret = preparedModel->configureExecutionBurst(&burst);
+    ASSERT_TRUE(ret.isOk()) << ret.getDescription();
+    ASSERT_NE(nullptr, burst.get());
+
+    const auto test = [&burst, &request](const std::vector<int64_t>& slots) {
+        ExecutionResult executionResult;
+        const auto executeStatus =
+                burst->executeSynchronously(request, slots, /*measure=*/false, kNoDeadline,
+                                            kOmittedTimeoutDuration, &executionResult);
+        ASSERT_FALSE(executeStatus.isOk());
+        ASSERT_EQ(executeStatus.getExceptionCode(), EX_SERVICE_SPECIFIC);
+        ASSERT_EQ(static_cast<ErrorStatus>(executeStatus.getServiceSpecificError()),
+                  ErrorStatus::INVALID_ARGUMENT);
+    };
+
+    int64_t currentSlot = 0;
+    std::vector<int64_t> slots;
+    slots.reserve(request.pools.size());
+    for (const auto& pool : request.pools) {
+        if (pool.getTag() == RequestMemoryPool::Tag::pool) {
+            slots.push_back(currentSlot++);
+        } else {
+            slots.push_back(-1);
+        }
+    }
+
+    constexpr int64_t invalidSlot = -2;
+
+    // validate failure when invalid memory identifier token value
+    for (size_t i = 0; i < request.pools.size(); ++i) {
+        const int64_t oldSlotValue = slots[i];
+
+        slots[i] = invalidSlot;
+        test(slots);
+
+        slots[i] = oldSlotValue;
+    }
+
+    // validate failure when request.pools.size() != memoryIdentifierTokens.size()
+    if (request.pools.size() > 0) {
+        slots = std::vector<int64_t>(request.pools.size() - 1, -1);
+        test(slots);
+    }
+
+    // validate failure when request.pools.size() != memoryIdentifierTokens.size()
+    slots = std::vector<int64_t>(request.pools.size() + 1, -1);
+    test(slots);
+
+    // validate failure when invalid memory identifier token value
+    const auto freeStatus = burst->releaseMemoryResource(invalidSlot);
+    ASSERT_FALSE(freeStatus.isOk());
+    ASSERT_EQ(freeStatus.getExceptionCode(), EX_SERVICE_SPECIFIC);
+    ASSERT_EQ(static_cast<ErrorStatus>(freeStatus.getServiceSpecificError()),
+              ErrorStatus::INVALID_ARGUMENT);
+}
+
 void validateRequestFailure(const std::shared_ptr<IPreparedModel>& preparedModel,
                             const Request& request) {
     SCOPED_TRACE("Expecting request to fail [executeSynchronously]");
diff --git a/neuralnetworks/aidl/vts/functional/VtsHalNeuralnetworks.cpp b/neuralnetworks/aidl/vts/functional/VtsHalNeuralnetworks.cpp
index 2d91b8e..0c3a196 100644
--- a/neuralnetworks/aidl/vts/functional/VtsHalNeuralnetworks.cpp
+++ b/neuralnetworks/aidl/vts/functional/VtsHalNeuralnetworks.cpp
@@ -127,6 +127,8 @@
 // Forward declaration from ValidateRequest.cpp
 void validateRequest(const std::shared_ptr<IPreparedModel>& preparedModel, const Request& request);
 // Forward declaration from ValidateRequest.cpp
+void validateBurst(const std::shared_ptr<IPreparedModel>& preparedModel, const Request& request);
+// Forward declaration from ValidateRequest.cpp
 void validateRequestFailure(const std::shared_ptr<IPreparedModel>& preparedModel,
                             const Request& request);
 
@@ -140,6 +142,7 @@
     if (preparedModel == nullptr) return;
 
     validateRequest(preparedModel, request);
+    validateBurst(preparedModel, request);
     // HIDL also had test that expected executeFenced to fail on received null fd (-1). This is not
     // allowed in AIDL and will result in EX_TRANSACTION_FAILED.
 }
@@ -178,8 +181,6 @@
 
 std::string toString(Executor executor) {
     switch (executor) {
-        case Executor::ASYNC:
-            return "ASYNC";
         case Executor::SYNC:
             return "SYNC";
         case Executor::BURST:
diff --git a/neuralnetworks/aidl/vts/functional/VtsHalNeuralnetworks.h b/neuralnetworks/aidl/vts/functional/VtsHalNeuralnetworks.h
index 9b81ee1..4312d3a 100644
--- a/neuralnetworks/aidl/vts/functional/VtsHalNeuralnetworks.h
+++ b/neuralnetworks/aidl/vts/functional/VtsHalNeuralnetworks.h
@@ -52,7 +52,7 @@
                          std::shared_ptr<IPreparedModel>* preparedModel,
                          bool reportSkipping = true);
 
-enum class Executor { ASYNC, SYNC, BURST, FENCED };
+enum class Executor { SYNC, BURST, FENCED };
 
 std::string toString(Executor executor);