Thread synchronization with Mutex in Ruby

Introduction

Mutex helps threads take turns so they don't mess up shared data. It keeps things safe and organized.

When multiple threads need to update the same bank account balance.

When threads write to the same file and you want to avoid mixed-up content.

When you have a shared list and threads add or remove items from it.

When you want to make sure only one thread changes a setting at a time.

Syntax

Ruby

mutex = Mutex.new
mutex.synchronize do
  # critical section code here
end

The Mutex.new creates a new lock.

The synchronize method makes sure only one thread runs the code inside at a time.

Examples

This example locks the code that prints a message so only one thread can print at once.

Ruby

mutex = Mutex.new
mutex.synchronize do
  puts "Only one thread here!"
end

Multiple threads safely increase count using the mutex to avoid mistakes.

Ruby

mutex = Mutex.new
count = 0
threads = 5.times.map do
  Thread.new do
    mutex.synchronize do
      count += 1
    end
  end
end
threads.each(&:join)
puts count

Sample Program

This program creates 10 threads. Each thread adds 1 to counter 1000 times. The mutex makes sure the counter updates safely without errors.

Ruby

mutex = Mutex.new
counter = 0
threads = 10.times.map do
  Thread.new do
    1000.times do
      mutex.synchronize do
        counter += 1
      end
    end
  end
end
threads.each(&:join)
puts "Final counter value: #{counter}"

Important Notes

Always use mutex.synchronize to wrap code that changes shared data.

Without mutex, threads can overwrite each other's changes, causing wrong results.

Mutex only locks one thread at a time; others wait patiently.

Summary

Mutex helps threads work together without breaking shared data.

Use mutex.synchronize to protect critical code sections.

Thread synchronization avoids bugs from simultaneous changes.

Practice

1. What is the main purpose of using a Mutex in Ruby threads?

easy

A. To create new threads automatically

B. To prevent multiple threads from accessing shared data at the same time

C. To speed up thread execution by running them in parallel

D. To stop threads from running

Solution

1. Step 1: Understand what shared data means in threads

   Shared data is information that multiple threads can access or change.

2. Step 2: Identify the role of Mutex

   Mutex ensures only one thread changes shared data at a time to avoid errors.

3. Final Answer:

   To prevent multiple threads from accessing shared data at the same time -> Option B

4. Quick Check:

   Mutex protects shared data = prevent simultaneous access [OK]

Hint: Mutex locks shared data to avoid conflicts between threads [OK]

Common Mistakes:

• Thinking Mutex speeds up threads
• Believing Mutex creates threads
• Assuming Mutex stops threads completely

2. Which of the following is the correct way to use a Mutex to protect a critical section in Ruby?

easy

A. mutex.synchronize { critical_code }

B. mutex.lock; critical_code

C. mutex.run(critical_code)

D. mutex.start { critical_code }

Solution

1. Step 1: Recall Mutex usage in Ruby

   Ruby's Mutex class provides a synchronize method to wrap critical code safely.

2. Step 2: Compare options

   Only mutex.synchronize { critical_code } is the correct and safe syntax.

3. Final Answer:

   mutex.synchronize { critical_code } -> Option A

4. Quick Check:

   Use synchronize method to protect code [OK]

Hint: Use mutex.synchronize { } to wrap critical code [OK]

Common Mistakes:

• Forgetting to unlock mutex after lock
• Using non-existent methods like run or start
• Not wrapping critical code in a block

3. What will be the output of this Ruby code?

require 'thread'
mutex = Mutex.new
counter = 0
threads = 3.times.map do
  Thread.new do
    2.times do
      mutex.synchronize { counter += 1 }
    end
  end
end
threads.each(&:join)
puts counter

medium

A. 2

B. 3

C. 6

D. 0

Solution

1. Step 1: Count total increments

   There are 3 threads, each increments counter 2 times, total 3*2=6 increments.

2. Step 2: Understand mutex effect

   Mutex ensures increments happen safely without losing counts, so final counter is 6.

3. Final Answer:

   6 -> Option C

4. Quick Check:

   3 threads * 2 increments each = 6 [OK]

Hint: Multiply threads by increments inside synchronize block [OK]

Common Mistakes:

• Ignoring mutex and expecting wrong count
• Counting only one thread's increments
• Confusing thread join effect

4. Identify the problem in this Ruby code using Mutex and how to fix it:

require 'thread'
mutex = Mutex.new
counter = 0
threads = 2.times.map do
  Thread.new do
    mutex.lock
    counter += 1
  end
end
threads.each(&:join)
puts counter

medium

A. Threads are not joined properly; fix by joining inside the thread block

B. Mutex is not needed here; remove mutex.lock

C. counter should be initialized inside the thread

D. Missing mutex.unlock causes deadlock; fix by adding mutex.unlock after increment

Solution

1. Step 1: Check mutex usage

   Mutex is locked but never unlocked, causing threads to wait forever (deadlock).

2. Step 2: Fix by unlocking mutex

   After increment, call mutex.unlock or better use mutex.synchronize to auto-handle locking/unlocking.

3. Final Answer:

   Missing mutex.unlock causes deadlock; fix by adding mutex.unlock after increment -> Option D

4. Quick Check:

   Always unlock mutex after lock to avoid deadlock [OK]

Hint: Always unlock mutex or use synchronize block [OK]

Common Mistakes:

• Forgetting to unlock mutex
• Removing mutex when needed
• Initializing shared data inside threads incorrectly

5. You want to safely update a shared hash from multiple threads in Ruby. Which approach correctly uses Mutex to avoid race conditions?

shared_hash = {}
mutex = Mutex.new
threads = 5.times.map do |i|
  Thread.new do
    10.times do |j|
      # What goes here?
    end
  end
end
threads.each(&:join)
puts shared_hash.size

hard

A. mutex.synchronize { shared_hash[i * 10 + j] = "value" }

B. shared_hash[i * 10 + j] = "value"

C. mutex.lock; shared_hash[i * 10 + j] = "value";

D. Thread.pass; shared_hash[i * 10 + j] = "value"

Solution

1. Step 1: Understand thread safety for shared hash

   Multiple threads writing to shared_hash need protection to avoid data corruption.

2. Step 2: Use mutex.synchronize for safe updates

   mutex.synchronize { shared_hash[i * 10 + j] = "value" } wraps the update inside mutex.synchronize, ensuring only one thread writes at a time.

3. Final Answer:

   mutex.synchronize { shared_hash[i * 10 + j] = "value" } -> Option A

4. Quick Check:

   Use synchronize block to protect shared hash updates [OK]

Hint: Wrap shared data updates inside mutex.synchronize { } [OK]

Common Mistakes:

• Updating shared hash without mutex
• Locking mutex without unlocking
• Using Thread.pass instead of mutex