Perhaps surprisingly, concurrent programming isn't so much about threads or locks, any more than civil engineering is about rivets and I-beams. Of course, building bridges that don't fall down requires the correct use of a lot of rivets and I-beams, just as building concurrent programs require the correct use of threads and locks. But these are just mechanismsmeans to an end. Writing thread-safe code is, at its core, about managing access to state, and in particular to shared, mutable state.
Informally, an object's state is its data, stored in state variables such as instance or static fields. An object's state may include fields from other, dependent objects; a HashMap's state is partially stored in the HashMap object itself, but also in many Map.Entry objects. An object's state encompasses any data that can affect its externally visible behavior.
By shared, we mean that a variable could be accessed by multiple threads; by mutable, we mean that its value could change during its lifetime. We may talk about thread safety as if it were about code, but what we are really trying to do is protect data from uncontrolled concurrent access.
Whether an object needs to be thread-safe depends on whether it will be accessed from multiple threads. This is a property of how the object is used in a program, not what it does. Making an object thread-safe requires using synchronization to coordinate access to its mutable state; failing to do so could result in data corruption and other undesirable consequences.
Whenever more than one thread accesses a given state variable, and one of them might write to it, they all must coordinate their access to it using synchronization. The primary mechanism for synchronization in Java is the synchronized keyword, which provides exclusive locking, but the term "synchronization" also includes the use of volatile variables, explicit locks, and atomic variables.
You should avoid the temptation to think that there are "special" situations in which this rule does not apply. A program that omits needed synchronization might appear to work, passing its tests and performing well for years, but it is still broken and may fail at any moment.
If multiple threads access the same mutable state variable without appropriate synchronization, your program is broken. There are three ways to fix it:
If you haven't considered concurrent access in your class design, some of these approaches can require significant design modifications, so fixing the problem might not be as trivial as this advice makes it sound. It is far easier to design a class to be thread-safe than to retrofit it for thread safety later.
In a large program, identifying whether multiple threads might access a given variable can be complicated. Fortunately, the same object-oriented techniques that help you write well-organized, maintainable classessuch as encapsulation and data hidingcan also help you create thread-safe classes. The less code that has access to a particular variable, the easier it is to ensure that all of it uses the proper synchronization, and the easier it is to reason about the conditions under which a given variable might be accessed. The Java language doesn't force you to encapsulate stateit is perfectly allowable to store state in public fields (even public static fields) or publish a reference to an otherwise internal objectbut the better encapsulated your program state, the easier it is to make your program thread-safe and to help maintainers keep it that way.
When designing thread-safe classes, good object-oriented techniquesencapsulation, immutability, and clear specification of invariantsare your best friends.
There will be times when good object-oriented design techniques are at odds with real-world requirements; it may be necessary in these cases to compromise the rules of good design for the sake of performance or for the sake of backward compatibility with legacy code. Sometimes abstraction and encapsulation are at odds with performancealthough not nearly as often as many developers believebut it is always a good practice first to make your code right, and then make it fast. Even then, pursue optimization only if your performance measurements and requirements tell you that you must, and if those same measurements tell you that your optimizations actually made a difference under realistic conditions. 
 In concurrent code, this practice should be adhered to even more than usual. Because concurrency bugs are so difficult to reproduce and debug, the benefit of a small performance gain on some infrequently used code path may well be dwarfed by the risk that the program will fail in the field.
If you decide that you simply must break encapsulation, all is not lost. It is still possible to make your program thread-safe, it is just a lot harder. Moreover, the thread safety of your program will be more fragile, increasing not only development cost and risk but maintenance cost and risk as well. Chapter 4 characterizes the conditions under which it is safe to relax encapsulation of state variables.
We've used the terms "thread-safe class" and "thread-safe program" nearly interchangeably thus far. Is a thread-safe program one that is constructed entirely of thread-safe classes? Not necessarilya program that consists entirely of thread-safe classes may not be thread-safe, and a thread-safe program may contain classes that are not thread-safe. The issues surrounding the composition of thread-safe classes are also taken up in Chapter 4. In any case, the concept of a thread-safe class makes sense only if the class encapsulates its own state. Thread safety may be a term that is applied to code, but it is about state, and it can only be applied to the entire body of code that encapsulates its state, which may be an object or an entire program.
Part I: Fundamentals
Part II: Structuring Concurrent Applications
Cancellation and Shutdown
Applying Thread Pools
Part III: Liveness, Performance, and Testing
Avoiding Liveness Hazards
Performance and Scalability
Testing Concurrent Programs
Part IV: Advanced Topics
Building Custom Synchronizers
Atomic Variables and Nonblocking Synchronization
The Java Memory Model