Step by Step solution about How to resolve the algorithm Dining philosophers step by step in the Kotlin programming language

Dining Philosophers Problem (Kotlin Version)

Overview

The "Dining Philosophers" problem is a classic in computer science used to demonstrate the challenges of concurrency and synchronization. It involves a group of philosophers sitting around a circular table with a fork on either side of each philosopher. To eat, a philosopher must acquire both forks simultaneously. If a philosopher finds that one or both forks are unavailable, they must wait until both forks are free before attempting to eat again.

Kotlin Code Explanation

The Kotlin code provided solves the Dining Philosophers problem using Reentrant Locks to ensure mutual exclusion when philosophers try to pick up forks.

Fork Class

The Fork class represents a fork on the table. It has a name and a lock that controls access to it. Philosophers must acquire the fork's lock before picking it up and release the lock when putting it down.

Philosopher Class

The Philosopher class represents a philosopher sitting at the table. Each philosopher has a name and references to the two forks left and right of them.

The run() method overrides the Thread method to define the philosopher's behavior. It contains a loop that repeats 20 times. In each iteration, the philosopher "picks up" both forks, "eats," and then "puts down" both forks.

Dining Philosophers Function

The diningPhilosophers() function creates a list of forks, a list of philosopher threads, and then starts each philosopher thread. It also waits for all philosopher threads to finish before exiting.

Main Function

The main() function initializes a list of philosopher names and calls the diningPhilosophers() function with this list. This starts the simulation of the dining philosophers problem, and the program terminates when all philosophers have finished eating.

Synchronization with Reentrant Locks

The pickUp() and putDown() methods in the Fork class use Reentrant Locks to ensure mutual exclusion when accessing the forks. This means that only one philosopher can acquire a given lock at a time, preventing multiple philosophers from picking up the same fork simultaneously.

Thread Safety

The use of locks ensures thread safety in the program. Since only one philosopher can acquire a particular fork lock at a time, there is no risk of two philosophers trying to use the same fork concurrently.

Execution

When the program runs, it creates a list of forks and a list of philosopher threads. Each philosopher thread then runs its run() method, repeatedly "eating" 20 times by acquiring and releasing the two forks it needs. The diningPhilosophers() function waits for all philosophers to finish before exiting.

Output

The output of the program shows the actions of each philosopher as they pick up and put down forks to eat. For example:

Aristotle is hungry
 Aristotle picked up Fork 1
 Aristotle picked up Fork 2
Aristotle is eating bite 1
 Aristotle put down Fork 2
 Aristotle put down Fork 1
Marx is hungry
 Marx picked up Fork 5
 Marx picked up Fork 1
Marx is eating bite 1
 Marx put down Fork 1
 Marx put down Fork 5

// Version 1.2.31

import java.util.Random
import java.util.concurrent.locks.Lock
import java.util.concurrent.locks.ReentrantLock

val rand = Random()

class Fork(val name: String) {
    val lock = ReentrantLock()

    fun pickUp(philosopher: String) {
        lock.lock()
        println("  $philosopher picked up $name")
    }

    fun putDown(philosopher: String) {
        lock.unlock()
        println("  $philosopher put down $name")
    }
}

class Philosopher(val pname: String, val f1: Fork, val f2: Fork) : Thread() {
    override fun run() {
        (1..20).forEach {
            println("$pname is hungry")
            f1.pickUp(pname)
            f2.pickUp(pname)
            println("$pname is eating bite $it")
            Thread.sleep(rand.nextInt(300) + 100L)
            f2.putDown(pname)
            f1.putDown(pname)
        }
    }
}

fun diningPhilosophers(names: List<String>) {
    val size = names.size
    val forks = List(size) { Fork("Fork ${it + 1}") }
    val philosophers = mutableListOf<Philosopher>()
    names.forEachIndexed { i, n ->
        var i1 = i
        var i2 = (i + 1) % size
        if (i2 < i1) {
            i1 = i2
            i2 = i
        }
        val p = Philosopher(n, forks[i1], forks[i2])
        p.start()
        philosophers.add(p)
    }
    philosophers.forEach { it.join() }
}

fun main(args: Array<String>) {
    val names = listOf("Aristotle", "Kant", "Spinoza", "Marx", "Russell")
    diningPhilosophers(names)
}