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Sample Master-Level Programming Assignment Questions and Solutions

To demonstrate our expertise, we have provided two sample master-level programming questions along with their solutions.

Question 1: Implementing a Multithreaded File Processor in Java

Problem Statement:
Develop a Java program that reads a large text file, processes each line concurrently using multiple threads, and writes the processed output to another file. The program should ensure thread safety and optimize performance.

Solution:

import java.io.*;
import java.util.concurrent.*;

public class MultithreadedFileProcessor {
    private static final int THREAD_COUNT = 4;
    
    public static void main(String[] args) {
        ExecutorService executor = Executors.newFixedThreadPool(THREAD_COUNT);
        try (BufferedReader reader = new BufferedReader(new FileReader("input.txt"));
             BufferedWriter writer = new BufferedWriter(new FileWriter("output.txt"))) {
            
            String line;
            while ((line = reader.readLine()) != null) {
                final String data = line;
                executor.submit(() -> {
                    String processedData = processLine(data);
                    synchronized (writer) {
                        try {
                            writer.write(processedData + "\n");
                        } catch (IOException e) {
                            e.printStackTrace();
                        }
                    }
                });
            }
        } catch (IOException e) {
            e.printStackTrace();
        } finally {
            executor.shutdown();
        }
    }
    
    private static String processLine(String line) {
        return line.toUpperCase();
    }
}

Explanation:

• The program uses a thread pool with a fixed number of threads.

• Each line from the input file is processed concurrently.

• Synchronization is used to ensure thread-safe writing to the output file.

• The solution ensures optimal performance and efficiency.

Question 2: Implementing Dijkstra’s Algorithm in Python

Problem Statement:
Write a Python program to implement Dijkstra’s shortest path algorithm using a priority queue. The program should take a graph as input and find the shortest path from a given source node.

Solution:

import heapq

def dijkstra(graph, start):
    pq = []
    heapq.heappush(pq, (0, start))
    shortest_paths = {node: float('inf') for node in graph}
    shortest_paths[start] = 0
    
    while pq:
        (current_distance, current_node) = heapq.heappop(pq)
        
        for neighbor, weight in graph[current_node].items():
            distance = current_distance + weight
            if distance < shortest_paths[neighbor]:
                shortest_paths[neighbor] = distance
                heapq.heappush(pq, (distance, neighbor))
    
    return shortest_paths

# Sample graph representation
graph = {
    'A': {'B': 1, 'C': 4},
    'B': {'A': 1, 'C': 2, 'D': 5},
    'C': {'A': 4, 'B': 2, 'D': 1},
    'D': {'B': 5, 'C': 1}
}

source = 'A'
shortest_distances = dijkstra(graph, source)
print(f"Shortest distances from {source}: {shortest_distances}")

Explanation:

• A min-heap (priority queue) is used to pick the next shortest path efficiently.

• The dictionary shortest_paths stores the shortest distance to each node.

• The graph is represented using a dictionary of dictionaries.

• The algorithm updates shortest paths dynamically and runs in O((V+E) log V) time complexity.

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