Java performance

In software development, the programming language Java was historically considered slower than the fastest 3rd generation typed languages such as C and C++. The main reason being a different language design, where after compiling, Java programs run on a Java virtual machine (JVM) rather than directly on the computer's processor as native code, as do C and C++ programs. Performance was a matter of concern because much business software has been written in Java after the language quickly became popular in the late 1990s and early 2000s. Since the late 1990s, the execution speed of Java programs improved significantly via introduction of just-in-time compilation (JIT) (in 1997 for Java 1.1), the addition of language features supporting better code analysis, and optimizations in the JVM (such as HotSpot becoming the default for Sun's JVM in 2000). Hardware execution of Java bytecode, such as that offered by ARM's Jazelle, can also offer significant performance improvements. The performance of a Java bytecode compiled Java program depends on how optimally its given tasks are managed by the host Java virtual machine (JVM), and how well the JVM exploits the features of the computer hardware and operating system (OS) in doing so. Thus, any Java performance test or comparison has to always report the version, vendor, OS and hardware architecture of the used JVM. In a similar manner, the performance of the equivalent natively compiled program will depend on the quality of its generated machine code, so the test or comparison also has to report the name, version and vendor of the used compiler, and its activated compiler optimization directives. Many optimizations have improved the performance of the JVM over time. However, although Java was often the first Virtual machine to implement them successfully, they have often been used in other similar platforms as well. Early JVMs always interpreted Java bytecodes. This had a large performance penalty of between a factor 10 and 20 for Java versus C in average applications. To combat this, a just-in-time (JIT) compiler was introduced into Java 1.1. Due to the high cost of compiling, an added system called HotSpot was introduced in Java 1.2 and was made the default in Java 1.3. Using this framework, the Java virtual machine continually analyses program performance for hot spots which are executed frequently or repeatedly. These are then targeted for optimizing, leading to high performance execution with a minimum of overhead for less performance-critical code.Some benchmarks show a 10-fold speed gain by this means. However, due to time constraints, the compiler cannot fully optimize the program, and thus the resulting program is slower than native code alternatives. Adaptive optimizing is a method in computer science that performs dynamic recompilation of parts of a program based on the current execution profile. With a simple implementation, an adaptive optimizer may simply make a trade-off between just-in-time compiling and interpreting instructions. At another level, adaptive optimizing may exploit local data conditions to optimize away branches and use inline expansion. A Java virtual machine like HotSpot can also deoptimize code formerly JITed. This allows performing aggressive (and potentially unsafe) optimizations, while still being able to later deoptimize the code and fall back to a safe path. The 1.0 and 1.1 Java virtual machines (JVMs) used a mark-sweep collector, which could fragment the heap after a garbage collection.Starting with Java 1.2, the JVMs changed to a generational collector, which has a much better defragmentation behaviour.Modern JVMs use a variety of methods that have further improved garbage collection performance.