Java long byte length [duplicate]

If Java’s long primitive data type is a 64-bit signed integer, then why do the Java docs state that the static long maximum value is 2^63-1? Is there a larger reason that affects other primitive data types similarly in Java? I’m learning Java and am just genuinely curious about this disparity. Thank you.

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What he means is that there are long values less than zero. In fact, there are more long values less than zero than greater than zero!

in any programming language, the Most Significant Bit will be the sign bit, which denotes the sign of the number. So in your question, for a 64-bit signed integer, leaving the MSB, the remaining 63 bits are used to denote the value of the integer. Which is why 2^63-1

@AshwinKKumar that is wrong. Java uses the “Two`s Complement” and does not just use the most significant bit for the sign (the fact that the msb is 1 for negative numbers is true but the remaining bits are not the same as for the positive number)

“in any programming language, the Most Significant Bit will be the sign bit” – Incorrect. 1) In a programming language with unsigned integers, the top bit is not the sign bit. 2) You are assuming the programming language uses the hardware-provided native (signed) integer representation. In some languages, that is not always true . or never true. (Example of “never true” – the CLU programming language, which “stole” a bit for use by the GC to distinguish scalars from pointers.)

2 Answers 2

Java’s long type is indeed a 64-bit integer, but it is also signed.

With 64-bit, you can represent 2^64 different numbers. If you ignore all the negative numbers, then the maximum value would be 2^64-1, and minimum will be 0. 0 plus all 2^64-1 positive numbers is 2^64 numbers in total.

However, if you consider all the negative numbers as well as the positives, about half of the 2^64 different numbers will be negative. Java just chose to represent 2^63 negative numbers, the number 0, and 2^63-1 positive numbers. If you add all these up, you get 2^64 total numbers.

2^63 + 1 + 2^63 - 1 = 2^64 ^ | this is the number zero 

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Its just a range formula just like range for octal and hexadecimal numbers 2^n -1 different for signed and unsigned numbers. 2^n and 2^n-1 (Range)

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Understanding Java’s Long and Integer Cache

Java’s Integer and Long classes have a built-in caching mechanism that helps reduce memory overhead and improve performance. This cache is used when autoboxing primitive types into their corresponding wrapper classes. The Integer cache range is from -128 to 127 by default, while the Long cache has a fixed range from -128 to 127 as well. The cache size is configurable with -XX:AutoBoxCacheMax=

The cache is created during the initialization of the Integer and Long classes, and the cached objects are stored in an internal array. When a value falls within the cache range, Java reuses the cached object instead of creating a new one, which can be beneficial for performance.

The Pitfalls

While the caching mechanism can improve performance, it can also lead to unexpected behaviors if developers are not aware of it. Here are some common pitfalls associated with Java’s Long and Integer cache:

Equality comparison pitfalls

When comparing two Integer or Long objects, developers might use the == operator instead of the equals() method. This operator compares object references, not the actual values. If two objects fall within the cache range, they will be the same object, and the == operator will return true. However, when comparing two objects outside the cache range, the == operator will return false, even if their values are the same.

Integer a = 127; Integer b = 127; System.out.println(a == b); // true 

Integer c = 128; Integer d = 128; System.out.println(c == d); // false 

The correct approach is to use the equals() method:

System.out.println(c.equals(d)); // true 

If you’re working with a large number of Integer or Long objects, it’s essential to understand the cache’s impact on performance. Values outside the cache range will not benefit from the caching mechanism, resulting in more significant memory overhead and potential performance degradation.

Mutable cache objects

Java’s Integer and Long classes are immutable, meaning their values cannot be changed once created. However, using reflection or other unsafe methods, a developer might inadvertently modify a cached object’s value. This can lead to unpredictable behavior, as other parts of the code that rely on the same cached object will be affected.

Another significant pitfall associated with Java’s Long and Integer cache is its lack of thread safety. The cache is a shared resource, accessible by multiple threads within a Java application. If the cache were to be modified using reflection or other unsafe techniques, as mentioned earlier, it could lead to unpredictable behavior and data inconsistency across different threads.

When multiple threads access the shared cache, they might inadvertently overwrite or modify the cached objects, causing unexpected results. This is particularly concerning when using unsafe methods to alter cached objects. Here’s an example of how this could cause issues:

public class UnsafeCacheModification  public static void main(String[] args) throws NoSuchFieldException, IllegalAccessException  // Access the Integer cache through reflection  Class cacheClass = Integer.class.getDeclaredClasses()[0];  Field cacheField = cacheClass.getDeclaredField("cache");  cacheField.setAccessible(true);  Integer[] cache = (Integer[]) cacheField.get(null);   // Modify the cached value for 42  cache[42 + 128] = 43;   // Use the modified cache value in multiple threads  Runnable printModifiedValue = () ->  Integer modifiedValue = 42;  System.out.println("Expected: 42, Actual: " + modifiedValue);  >;   Thread t1 = new Thread(printModifiedValue);  Thread t2 = new Thread(printModifiedValue);  t1.start();  t2.start();  > > 

In this example, we use reflection to modify the cached value of 42 to 43. When multiple threads access the shared cache, they will all receive the modified value, causing data inconsistency.

To avoid such issues related to thread safety, developers should:

• Refrain from using reflection or other unsafe techniques to modify the cache.
• Always use the equals() method for object comparisons, as it is thread-safe and does not rely on the shared cache.
• Consider using thread-safe alternatives like AtomicInteger or AtomicLong when working with concurrent applications.

Conclusion

The cache mechanisms can improve performance in some cases, but they also introduce potential pitfalls for developers. Remember to use the equals() method for object comparisons and be cautious with object mutability to avoid unexpected behaviors. Understanding the thread safety concerns of Java’s Long and Integer cache is crucial for writing reliable and consistent multi-threaded applications. By being aware of these issues and following the best practices mentioned above, developers can mitigate the risks and ensure the stability and performance of their Java applications.

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