This article explains why locks are essential for preventing dirty reads and data inconsistency, explores the principles behind volatile, synchronized, monitor, CAS, and AQS, and illustrates Java’s lock implementations, optimizations, and practical usage examples such as ConcurrentHashMap.
The article explains why Java concurrency is essential, outlines its risks, and details how thread communication and synchronization work, covering the Java Memory Model, the roles of volatile and synchronized for visibility and ordering, and illustrating these concepts with code examples.
This article explains the Java volatile keyword, covering its memory‑model semantics, how it guarantees visibility and ordering, why it does not provide atomicity, and demonstrates typical usage patterns such as flag signaling and double‑checked locking for singletons.
This article walks through multiple Java Singleton implementations—lazy initialization, double‑checked locking, volatile‑protected, static‑inner‑class, and enum—explaining their thread‑safety characteristics, the pitfalls of instruction reordering, and how reflection and serialization can break or preserve the pattern.
The article presents a Java program where 100 threads each increment a volatile int 1,000 times, showing that the final value may be less than the expected 100,000, and explains that volatile only guarantees visibility, not atomicity, making it unsuitable for concurrent modifications.
This article explains the Java volatile keyword, covering its definition, lightweight nature compared to synchronized, visibility guarantees, usage conditions, and practical patterns such as state flags, safe publication, volatile beans, and low‑cost read‑write lock strategies, illustrated with code examples.
