JSR 292
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JSR 292
The Da Vinci Machine, also called the Multi Language Virtual Machine, was a Sun Microsystems project aiming to prototype the extension of the Java Virtual Machine (JVM) to add support for dynamic languages. It was already possible to run dynamic languages on top of the JVM, but the goal is to ease new dynamic language implementations and increase their performance. This project was the reference implementation of JSR 292 (''Supporting Dynamically Typed Languages on the Java Platform''). History Prior to Java 7, the Java Virtual Machine had no built-in support for dynamically typed languages: * The existing JVM instruction set is statically typed. * JVM has limited support for dynamically modifying existing classes and methods. It currently works only in a debugging environment. JSR 292 (''Supporting Dynamically Typed Languages on the Java Platform'') proposes to: * add a new invokedynamic instruction at the JVM level, to allow method invocation relying on dynamic type ...
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Sun Microsystems
Sun Microsystems, Inc. (Sun for short) was an American technology company that sold computers, computer components, software, and information technology services and created the Java programming language, the Solaris operating system, ZFS, the Network File System (NFS), and SPARC microprocessors. Sun contributed significantly to the evolution of several key computing technologies, among them Unix, RISC processors, thin client computing, and virtualized computing. Notable Sun acquisitions include Cray Business Systems Division, Storagetek, and ''Innotek GmbH'', creators of VirtualBox. Sun was founded on February 24, 1982. At its height, the Sun headquarters were in Santa Clara, California (part of Silicon Valley), on the former west campus of the Agnews Developmental Center. Sun products included computer servers and workstations built on its own RISC-based SPARC processor architecture, as well as on x86-based AMD Opteron and Intel Xeon processors. Sun also developed its own ...
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Java Version History
The Java language has undergone several changes since JDK 1.0 as well as numerous additions of classes and packages to the standard library. Since J2SE 1.4, the evolution of the Java language has been governed by the Java Community Process (JCP), which uses ''Java Specification Requests'' (JSRs) to propose and specify additions and changes to the Java platform. The language is specified by the ''Java Language Specification'' (JLS); changes to the JLS are managed undeJSR 901 In September 2017, Mark Reinhold, chief Architect of the Java Platform, proposed to change the release train to "one feature release every six months" rather than the then-current two-year schedule. This proposal took effect for all following versions, and is still the current release schedule. In addition to the language changes, other changes have been made to the Java Class Library over the years, which has grown from a few hundred classes in JDK 1.0 to over three thousand in J2SE  ...
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Dynamic Language Runtime
The Dynamic Language Runtime (DLR) from Microsoft runs on top of the Common Language Runtime (CLR) and provides computer language services for dynamic languages. These services include: * A dynamic type system, to be shared by all languages using the DLR services * Dynamic method dispatch * Dynamic code generation * Hosting API The DLR is used to implement dynamic languages on the .NET Framework, including the IronPython and IronRuby projects. Because the dynamic language implementations share a common underlying system, it should be easier for them to interact with one another. For example, it should be possible to use libraries from any dynamic language in any other dynamic language. In addition, the hosting API allows interoperability with statically typed CLI languages like C# and Visual Basic .NET. History Microsoft's Dynamic Language Runtime project was announced by Microsoft at MIX 2007. Microsoft shipped .NET DLR 0.9 beta in November 2008, and final 0.9 in December ...
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List Of JVM Languages
This list of JVM Languages comprises notable computer programming languages that are used to produce computer software that runs on the Java virtual machine (JVM). Some of these languages are interpreted by a Java program, and some are compiled to Java bytecode and JIT-compiled during execution as regular Java programs to improve performance. The JVM was initially designed to support only the programming language Java. However, as time passed, even more languages were adapted or designed to run on the Java platform. JVM languages High-profile languages As of September 2022, according to the TIOBE Index of the top 100 programming languages, the top JVM languages are: * Java (#3), a statically-typed object-oriented language * Scala (#33), a statically-typed object-oriented and functional programming language * Kotlin (#34, at one point at #27), a statically-typed language from JetBrains, the developers of IntelliJ IDEA and Google's preferred language for Android * Groovy ...
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Scripting For The Java Platform
Scripting for the Java Platform is a framework for embedding scripts into Java source code. There is no requirement for a given Java virtual machine (JVM) to include any engines by default, but the Oracle JVM (Java 6 and later) includes a JavaScript engine, based on Rhino version 1.6R2 before Java 8, and Nashorn since Java 8. Scripting for the Java Platform was developed under the Java Community Process as JSR 223. The final release of JSR 223 happened on December 11, 2006. The specification, however, was withdrawn later on December 13, 2016 after a Maintenance Review Ballot, where it was decided that this functionality would be included as an integral part of Java 9 and onward. See also * Da Vinci Machine * Groovy * List of JVM languages * Apache JMeter References Bibliography * External links JSR 223: Scripting for the Java Platform Specification Request* * * for Java SE Java Platform, Standard Edition (Java SE) is a computing platform for development and ...
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Garbage Collection (computer Science)
In computer science, garbage collection (GC) is a form of automatic memory management. The ''garbage collector'' attempts to reclaim memory which was allocated by the program, but is no longer referenced; such memory is called '' garbage''. Garbage collection was invented by American computer scientist John McCarthy around 1959 to simplify manual memory management in Lisp. Garbage collection relieves the programmer from doing manual memory management, where the programmer specifies what objects to de-allocate and return to the memory system and when to do so. Other, similar techniques include stack allocation, region inference, and memory ownership, and combinations thereof. Garbage collection may take a significant proportion of a program's total processing time, and affect performance as a result. Resources other than memory, such as network sockets, database handles, windows, file descriptors, and device descriptors, are not typically handled by garbage collection, but ...
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Class (computer Science)
In object-oriented programming, a class is an extensible program-code-template for creating objects, providing initial values for state (member variables) and implementations of behavior (member functions or methods). In many languages, the class name is used as the name for the class (the template itself), the name for the default constructor of the class (a subroutine that creates objects), and as the type of objects generated by instantiating the class; these distinct concepts are easily conflated. Although, to the point of conflation, one could argue that is a feature inherent in a language because of its polymorphic nature and why these languages are so powerful, dynamic and adaptable for use compared to languages without polymorphism present. Thus they can model dynamic systems (i.e. the real world, machine learning, AI) more easily. When an object is created by a constructor of the class, the resulting object is called an instance of the class, and the member variabl ...
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Dynamic Memory Allocation
Memory management is a form of resource management applied to computer memory. The essential requirement of memory management is to provide ways to dynamically allocate portions of memory to programs at their request, and free it for reuse when no longer needed. This is critical to any advanced computer system where more than a single process might be underway at any time. Several methods have been devised that increase the effectiveness of memory management. Virtual memory systems separate the memory addresses used by a process from actual physical addresses, allowing separation of processes and increasing the size of the virtual address space beyond the available amount of RAM using paging or swapping to secondary storage. The quality of the virtual memory manager can have an extensive effect on overall system performance. In some operating systems, e.g. OS/360 and successors, memory is managed by the operating system. In other operating systems, e.g. Unix-like operating sy ...
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Parameter (computer Science)
In computer programming, a parameter or a formal argument is a special kind of variable used in a subroutine to refer to one of the pieces of data provided as input to the subroutine. These pieces of data are the values of the arguments (often called ''actual arguments'' or ''actual parameters'') with which the subroutine is going to be called/invoked. An ordered list of parameters is usually included in the definition of a subroutine, so that, each time the subroutine is called, its arguments for that call are evaluated, and the resulting values can be assigned to the corresponding parameters. Unlike ''argument'' in usual mathematical usage, the ''argument'' in computer science is the actual input expression passed/supplied to a function, procedure, or routine in the invocation/call statement, whereas the ''parameter'' is the variable inside the implementation of the subroutine. For example, if one defines the add subroutine as def add(x, y): return x + y, then x, y are paramet ...
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Type Signature
In computer science, a type signature or type annotation defines the inputs and outputs for a function, subroutine or method. A type signature includes the number, types, and order of the arguments contained by a function. A type signature is typically used during overload resolution for choosing the correct definition of a function to be called among many overloaded forms. Examples C/C++ In C and C++, the type signature is declared by what is commonly known as a function prototype. In C/C++, a function declaration reflects its use; for example, a function pointer with the signature would be called as: char c; double d; int retVal = (*fPtr)(c, d); Erlang In Erlang, type signatures may be optionally declared, as: -spec(function_name(type1(), type2(), ...) -> out_type()). For example: -spec(is_even(number()) -> boolean()). Haskell A type signature in Haskell generally takes the following form: functionName :: arg1Type -> arg2Type -> ... -> argNType Notice that t ...
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Reflection (computer Science)
In computer science, reflective programming or reflection is the ability of a process to examine, introspect, and modify its own structure and behavior. Historical background The earliest computers were programmed in their native assembly languages, which were inherently reflective, as these original architectures could be programmed by defining instructions as data and using self-modifying code. As the bulk of programming moved to higher-level compiled languages such as Algol, Cobol, Fortran, Pascal, and C, this reflective ability largely disappeared until new programming languages with reflection built into their type systems appeared. Brian Cantwell Smith's 1982 doctoral dissertation introduced the notion of computational reflection in procedural programming languages and the notion of the meta-circular interpreter as a component of 3-Lisp. Uses Reflection helps programmers make generic software libraries to display data, process different formats of data, perform seri ...
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Just-in-time Compilation
In computing, just-in-time (JIT) compilation (also dynamic translation or run-time compilations) is a way of executing computer code that involves compilation during execution of a program (at run time) rather than before execution. This may consist of source code translation but is more commonly bytecode translation to machine code, which is then executed directly. A system implementing a JIT compiler typically continuously analyses the code being executed and identifies parts of the code where the speedup gained from compilation or recompilation would outweigh the overhead of compiling that code. JIT compilation is a combination of the two traditional approaches to translation to machine code—ahead-of-time compilation (AOT), and interpretation—and combines some advantages and drawbacks of both. Roughly, JIT compilation combines the speed of compiled code with the flexibility of interpretation, with the overhead of an interpreter and the additional overhead of compil ...
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