diff --git a/Codes/Code-3.cpp b/Codes/Code-3.cpp
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+// Code-3 (Min, Max, Sum and Average Operations)
+
+/*
+ * THIS CODE HAS BEEN TESTED AND IS FULLY OPERATIONAL.
+ *
+ * Problem Statement: Implement Min, Max, Sum and Average operations using Parallel Reduction.
+ *
+ * Code from HighPerformanceComputing (SPPU - Final Year - Computer Engineering - Content)
+ * repository on KSKA Git: https://git.kska.io/sppu-be-comp-content/HighPerformanceComputing
+ **/
+
+/*
+ * EXECUTION INSTRUCTIONS (Debian-based distributions):
+ *
+ * i) Install g++ with OpenMP support:
+ *   sudo apt update
+ *   sudo apt install g++
+ *
+ * ii) Compile:
+ *   g++ -fopenmp Code-3.cpp -o Code-3
+ *
+ * iii) Execute:
+ *   ./Code-3
+ **/
+
+// BEGINNING OF CODE
+#include <iostream>
+#include <vector>
+#include <omp.h>
+#include <cstdlib>
+
+using namespace std;
+
+int main() {
+    // Uncomment to manually control thread count
+    // omp_set_num_threads(4);
+
+    // --- Input ---
+    int n = 1000000;
+    vector<int> nums(n);
+
+    for (int i = 0; i < n; i++)
+        nums[i] = rand() % 10000;
+
+    cout << "Input: " << n << " random integers in the range [0, 9999]." << endl << endl;
+
+    // long long prevents overflow: up to 1,000,000 * 9,999 ≈ 10 billion,
+    // which exceeds the int limit of ~2.1 billion.
+    long long sum_seq, sum_par;
+    int min_seq, max_seq;
+    int min_par, max_par;
+    double avg_seq, avg_par;
+    double start, end;
+
+    // --- Sequential ---
+    min_seq = max_seq = nums[0];
+    sum_seq = 0;
+
+    start = omp_get_wtime();
+    for (int i = 0; i < n; i++) {
+        if (nums[i] < min_seq) min_seq = nums[i];
+        if (nums[i] > max_seq) max_seq = nums[i];
+        sum_seq += nums[i];
+    }
+    end = omp_get_wtime();
+
+    // Computed after timing so both versions are measured fairly.
+    avg_seq = (double)sum_seq / n;
+    double time_seq = end - start;
+
+    // --- Parallel ---
+    min_par = max_par = nums[0];
+    sum_par = 0;
+
+    start = omp_get_wtime();
+    // reduction(min/max/+) gives each thread its own private copy of the
+    // variable, then combines them at the end, no critical sections needed.
+    // Without reduction, threads would race to update the same variable.
+    #pragma omp parallel for reduction(min: min_par) reduction(max: max_par) reduction(+: sum_par)
+    for (int i = 0; i < n; i++) {
+        if (nums[i] < min_par) min_par = nums[i];
+        if (nums[i] > max_par) max_par = nums[i];
+        sum_par += nums[i];
+    }
+    end = omp_get_wtime();
+
+    avg_par = (double)sum_par / n;
+    double time_par = end - start;
+
+    // --- Output ---
+    cout << "--- Sequential Computation ---" << endl;
+    cout << "Minimum  : " << min_seq << endl;
+    cout << "Maximum  : " << max_seq << endl;
+    cout << "Sum      : " << sum_seq << endl;
+    cout << "Average  : " << avg_seq << endl;
+    cout << "Time     : " << time_seq << " seconds" << endl;
+
+    cout << "\n--- Parallel Computation ---" << endl;
+    cout << "Minimum  : " << min_par << endl;
+    cout << "Maximum  : " << max_par << endl;
+    cout << "Sum      : " << sum_par << endl;
+    cout << "Average  : " << avg_par << endl;
+    cout << "Time     : " << time_par << " seconds" << endl;
+
+    cout << "\nSpeedup (Sequential / Parallel) = " << (time_seq / time_par) << "x" << endl;
+
+    return 0;
+}
+// END OF CODE
+
+/*
+EXAMPLE OUTPUT:
+
+$ ./Code-3 
+Input: 1000000 random integers in the range [0, 9999].
+
+--- Sequential Computation ---
+Minimum  : 0
+Maximum  : 9999
+Sum      : 5000491283
+Average  : 5000.49
+Time     : 0.0205385 seconds
+
+--- Parallel Computation ---
+Minimum  : 0
+Maximum  : 9999
+Sum      : 5000491283
+Average  : 5000.49
+Time     : 0.0135714 seconds
+
+Speedup (Sequential / Parallel) = 1.51336x
+*/