java-topology/defects/opencv/unit/OpenCVOnnxInt8OutputTest.java

package unit;

import java.util.ArrayList;
import java.util.HashSet;
import java.util.List;
import java.util.Set;

/**
 * CWE-407 unit test: opencv-0003 — ifInt8Output() O(N*I*L) vs O(N*I)
 *
 * Models modules/dnn/src/onnx/onnx_importer.cpp ifInt8Output():
 *
 *   slow() = static vector<String> + std::find, O(L) per lookup
 *            called N*I times during ONNX model import (N nodes, I inputs each)
 *            total: O(N * I * L)
 *
 *   fast() = static unordered_set<String>, O(1) per lookup
 *            total: O(N * I)
 *
 * L=35 (size of input8output8 list), N=1000 nodes, I=3 inputs/node
 * Expected ratio: >30x op-count reduction.
 */
public class OpenCVOnnxInt8OutputTest {

    static long slowOps = 0;
    static long fastOps = 0;

    // The 35-entry list from op_timvx.cpp
    static final List<String> INPUT8OUTPUT8_LIST = new ArrayList<>();
    static final Set<String> INPUT8OUTPUT8_SET = new HashSet<>();

    static {
        String[] types = {
            "QuantizeLinear", "QLinearAdd", "QLinearMul",
            "QLinearAveragePool", "QLinearGlobalAveragePool",
            "QLinearLeakyRelu", "QLinearSigmoid", "QLinearConcat",
            "QGemm", "QLinearSoftmax", "QLinearConv", "QLinearMatMul",
            "MaxPool", "ReduceMax", "ReduceMin", "Split", "Clip",
            "Abs", "Transpose", "Squeeze", "Flatten", "Unsqueeze",
            "Expand", "Reshape", "Pad", "Gather", "Concat", "Resize",
            "SpaceToDepth", "DepthToSpace", "Pow", "Add", "Sub", "Mul", "Div"
        };
        for (String t : types) {
            INPUT8OUTPUT8_LIST.add(t);
            INPUT8OUTPUT8_SET.add(t);
        }
    }

    /**
     * Slow: O(L) linear scan per call — models std::find on static vector.
     */
    static boolean ifInt8OutputSlow(String layerType) {
        for (String s : INPUT8OUTPUT8_LIST) {
            slowOps++;
            if (s.equals(layerType)) return true;
        }
        return false;
    }

    /**
     * Fast: O(1) hash lookup — models unordered_set::count.
     */
    static boolean ifInt8OutputFast(String layerType) {
        fastOps++;
        return INPUT8OUTPUT8_SET.contains(layerType);
    }

    /**
     * Simulate ONNX populateNet(): loop over N nodes, I inputs each,
     * call ifInt8Output() per input.
     */
    static void simulatePopulateNet(int nNodes, int inputsPerNode, boolean useSlow) {
        // Mix of types: half match, half do not
        String[] layerTypes = {"Conv", "Relu", "Add", "Reshape", "BatchNormalization"};
        for (int n = 0; n < nNodes; n++) {
            String layerType = layerTypes[n % layerTypes.length];
            for (int i = 0; i < inputsPerNode; i++) {
                if (useSlow) {
                    ifInt8OutputSlow(layerType);
                } else {
                    ifInt8OutputFast(layerType);
                }
            }
        }
    }

    public static void main(String[] args) {
        final int N_NODES = 1000;
        final int INPUTS_PER_NODE = 3;

        // Warm up
        simulatePopulateNet(10, 3, true);
        simulatePopulateNet(10, 3, false);
        slowOps = 0;
        fastOps = 0;

        // Measure
        simulatePopulateNet(N_NODES, INPUTS_PER_NODE, true);
        long measuredSlowOps = slowOps;
        slowOps = 0;

        simulatePopulateNet(N_NODES, INPUTS_PER_NODE, false);
        long measuredFastOps = fastOps;

        double ratio = (double) measuredSlowOps / measuredFastOps;

        System.out.printf("opencv-0003 ifInt8Output O(N*I*L) vs O(N*I)%n");
        System.out.printf("  N=%d nodes, I=%d inputs, L=%d list entries%n",
            N_NODES, INPUTS_PER_NODE, INPUT8OUTPUT8_LIST.size());
        System.out.printf("  slow ops (vector+find): %d%n", measuredSlowOps);
        System.out.printf("  fast ops (hash set):    %d%n", measuredFastOps);
        System.out.printf("  ratio:                  %.1fx%n", ratio);

        // Verify correctness: both return same result
        boolean slowResult = ifInt8OutputSlow("Add");
        boolean fastResult = ifInt8OutputFast("Add");
        boolean slowMiss = ifInt8OutputSlow("Conv");
        boolean fastMiss = ifInt8OutputFast("Conv");

        assert slowResult == fastResult : "hit mismatch";
        assert slowMiss == fastMiss : "miss mismatch";
        assert slowResult : "Add should be in int8output set";
        assert !slowMiss : "Conv should not be in int8output set";

        assert ratio > 10.0 :
            "Expected >10x ratio, got " + ratio;

        System.out.println("PASS");
    }
}