1.1.10. Best Practices

• Minimize shared mutable state.

Minimizing shared mutable state means reducing the amount of data that can be changed by multiple threads at the same time. This is important because if multiple threads modify the same data concurrently, it can lead to unpredictable outcomes, known as race conditions. By limiting shared data, you decrease the chances of conflicts.

Think of a group project where multiple people are editing a shared document at once. If one person changes a section while another is editing the same section, it can lead to confusion and errors. If they each work on separate documents and only merge when necessary, it reduces the chances of mistakes.

• Prefer java.util.concurrent over low-level constructs.

The java.util.concurrent package provides a higher-level abstraction for managing concurrency, making it easier and safer than using lower-level thread management constructs. It includes classes and interfaces like ExecutorService, which help manage threads efficiently, handle shared data safely, and prevent common pitfalls in multi-threaded programming.

Imagine you are managing a group of workers (threads). If you let each worker handle scheduling and tasks on their own (low-level constructs), it can lead to disorganization. However, if you hire a manager (java.util.concurrent) to assign tasks and monitor progress, everything runs smoother and more efficiently.

• Use thread pools.

Thread pools are a way to manage a set of threads efficiently. Instead of creating and destroying threads for each task, which can be resource-intensive, you create a fixed number of threads that can be reused for different tasks. This leads to better performance and resource management.

Consider a restaurant kitchen. If every time a customer placed an order, a new chef was hired, it would be very inefficient. Instead, having a set number of chefs who handle multiple orders ensures the kitchen runs smoothly and efficiently, just like thread pools do for tasks.

• Avoid nested locks to prevent deadlocks.

Nested locks occur when one thread holds a lock while trying to acquire another lock that another thread is holding. This can lead to deadlocks, where two or more threads are waiting on each other forever. To avoid this, developers should design their locking strategy to prevent locks from being nested.

Imagine two friends trying to pass each other a gift while holding onto their own. If each is waiting for the other to release their gift, they will be stuck forever. If they first place their gifts down before trying to exchange them, they can do so without problem, similar to avoiding nested locks.

• Prefer Atomic variables (AtomicInteger, etc.) for counters.

Atomic variables are special types of variables that support lock-free thread-safe operations. Instead of using synchronization to manage access, these variables can be updated in a way that prevents race conditions without complex locking mechanisms, making them a preferred choice for counters and other shared variables.

Think of a bank account balance being updated by multiple tellers (threads). Using standard checks and approvals (synchronization) for every transaction takes time. Atomic operations are like having a single, trusted system in place that updates the balance immediately and accurately, allowing for faster and more efficient transactions.

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