Code Snippet Generator for Scheduling Algorithms

Real-World Examples

Example 1: Round Robin Scheduling in Python

Use Case: Implementing a fair scheduling algorithm for a web server request handler

def round_robin(processes, quantum):
    n = len(processes)
    remaining_time = [p['burst'] for p in processes]
    waiting_time = [0] * n
    current_time = 0
    queue = []
    
    while True:
        for i in range(n):
            if processes[i]['arrival'] <= current_time and remaining_time[i] > 0:
                queue.append(i)
        
        if not queue:
            break
            
        current_process = queue.pop(0)
        exec_time = min(quantum, remaining_time[current_process])
        remaining_time[current_process] -= exec_time
        current_time += exec_time
        
        for i in range(n):
            if i != current_process and remaining_time[i] > 0 and processes[i]['arrival'] <= current_time:
                waiting_time[i] += exec_time
                
        if remaining_time[current_process] > 0:
            queue.append(current_process)
    
    return waiting_time

Example 2: Priority Scheduling in Java

Use Case: Task scheduling in a real-time embedded system

public class PriorityScheduler {
    static class Process {
        int pid, arrival, burst, priority;
        
        public Process(int pid, int arrival, int burst, int priority) {
            this.pid = pid;
            this.arrival = arrival;
            this.burst = burst;
            this.priority = priority;
        }
    }
    
    public static void schedule(Process[] processes) {
        Arrays.sort(processes, (a, b) -> {
            if (a.arrival != b.arrival) return a.arrival - b.arrival;
            return a.priority - b.priority;
        });
        
        int currentTime = 0;
        for (Process p : processes) {
            if (currentTime < p.arrival) currentTime = p.arrival;
            System.out.println("Process " + p.pid + " starts at " + currentTime);
            currentTime += p.burst;
        }
    }
}

Example 3: Multilevel Feedback Queue in C++

Use Case: Operating system process scheduler simulation

void MLFQ(vector& processes) {
    vector> queues(3); // 3 priority levels
    vector quantums = {4, 8, 16}; // Increasing quantums
    
    // Initial assignment to highest priority queue
    for (auto& p : processes) {
        queues[0].push(&p);
    }
    
    int time = 0;
    while (!all_queues_empty(queues)) {
        for (int i = 0; i < queues.size(); i++) {
            if (!queues[i].empty()) {
                Process* p = queues[i].front();
                queues[i].pop();
                
                int exec_time = min(quantums[i], p->remaining_time);
                p->remaining_time -= exec_time;
                time += exec_time;
                
                if (p->remaining_time > 0) {
                    // Demote to lower priority queue if not finished
                    if (i < queues.size() - 1) {
                        queues[i+1].push(p);
                    } else {
                        queues[i].push(p); // Stay in lowest queue
                    }
                }
                break;
            }
        }
    }
}

Formulas and Algorithms

The generator implements the following scheduling algorithms with their respective formulas and logic:

Turnaround Time = Completion Time - Arrival Time
Waiting Time = Turnaround Time - Burst Time

Average Waiting Time = (Σ Waiting Time) / n
Optimal for minimizing average waiting time

Time Quantum (TQ) = Fixed time slice
Context Switches = ceil(Burst Time / TQ) - 1

Priority can be:
- Static (assigned initially)
- Dynamic (calculated based on metrics)

Response Ratio = (Waiting Time + Burst Time) / Burst Time

Multiple queues with different priorities
Each queue can have its own scheduling algorithm

Processes can move between queues
Aging prevents starvation

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