Bytecode in the context of Opcode

In computing, source code, or simply code or source, is human readable plain text that can eventually result in controlling the behavior of a computer. In order to control a computer, it must be processed by a computer program – either executed directly via an interpreter or translated into a more computer-consumable form such as via a compiler. Sometimes, code is compiled directly to machine code so that it can be run in the native language of the computer without further processing. But, many modern environments involve compiling to an intermediate representation such as bytecode that can either run via an interpreter or be compiled on-demand to machine code via just-in-time compilation.

In computing, an interpreter is software that executes source code without first compiling it to machine code. An interpreted runtime environment differs from one that processes CPU-native executable code which requires translating source code before executing it. An interpreter may translate the source code to an intermediate format, such as bytecode. A hybrid environment may translate the bytecode to machine code via just-in-time compilation, as in the case of .NET and Java, instead of interpreting the bytecode directly.

Before the widespread adoption of interpreters, the execution of computer programs often relied on compilers, which translate and compile source code into machine code. Early runtime environments for Lisp and BASIC could parse source code directly. Thereafter, runtime environments were developed for languages (such as Perl, Raku, Python, MATLAB, and Ruby), which translated source code into an intermediate format before executing to enhance runtime performance.

A semantics encoding is a translation between formal languages. For programmers, the most familiar form of encoding is the compilation of a programming language into machine code or byte-code. Conversion between document formats are also forms of encoding. Compilation of TeX or LaTeX documents to PostScript are also commonly encountered encoding processes. Some high-level preprocessors, such as OCaml's Camlp4, also involve encoding of a programming language into another.

Formally, an encoding of a language A into language B is a mapping of all terms of A into B. If there is a satisfactory encoding of A into B, B is considered at least as powerful (or at least as expressive) as A.

A binary code is the value of a data-encoding convention represented in a binary notation that usually is a sequence of 0s and 1s; sometimes called a bit string. For example, ASCII is an 8-bit text encoding that in addition to the human readable form (letters) can be represented as binary. Binary code can also refer to the mass noun code that is not human readable in nature such as machine code and bytecode.

Even though all modern computer data is binary in nature, and therefore can be represented as binary, other numerical bases may be used. Power of 2 bases (including hex and octal) are sometimes considered binary code since their power-of-2 nature makes them inherently linked to binary. Decimal is, of course, a commonly used representation. For example, ASCII characters are often represented as either decimal or hex. Some types of data such as image data is sometimes represented as hex, but rarely as decimal.

In computing, an executable is a resource that a computer can use to control its behavior. As with all information in computing, it is data, but distinct from data that does not imply a flow of control. Terms such as executable code, executable file, executable program, and executable image describe forms in which the information is represented and stored. A native executable is machine code and is directly executable at the instruction level of a CPU. A script is also executable although indirectly via an interpreter. Intermediate executable code (such as bytecode) may be interpreted or converted to native code at runtime via just-in-time compilation.

An intermediate representation (IR) is the data structure or code used internally by a compiler or virtual machine to represent source code. An IR is designed to be conducive to further processing, such as optimization and translation. A "good" IR must be accurate – capable of representing the source code without loss of information – and independent of any particular source or target language. An IR may take one of several forms: an in-memory data structure, or a special tuple- or stack-based code readable by the program. In the latter case it is also called an intermediate language.

A canonical example is found in most modern compilers. For example, the CPython interpreter transforms the linear human-readable text representing a program into an intermediate graph structure that allows flow analysis and re-arrangement before execution. Use of an intermediate representation such as this allows compiler systems like the GNU Compiler Collection and LLVM to be used by many different source languages to generate code for many different target architectures.

In computing, just-in-time (JIT) compilation (also dynamic translation or run-time compilations) is compilation (of computer code) 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, which 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 compiling and linking (not just interpreting). JIT compilation is a form of dynamic compilation, and allows adaptive optimization such as dynamic recompilation and microarchitecture-specific speedups. Interpretation and JIT compilation are particularly suited for dynamic programming languages, as the runtime system can handle late-bound data types and enforce security guarantees.

Informally, a compiled language is a programming language that is usually implemented with a compiler rather than an interpreter. Because any language can theoretically be either compiled or interpreted, the term lacks clarity: compilation and interpretation are properties of a programming language implementation, not of a programming language. Some languages have both compilers and interpreters. Furthermore, a single implementation can involve both a compiler and an interpreter. For example, in some environments, source code is first compiled to an intermediate form (e.g., bytecode), which is then interpreted by an application virtual machine. In other environments, a just-in-time compiler selectively compiles some code at runtime, blurring the distinction further.

OCaml (/oʊˈkæməl/ oh-KAM-əl, formerly Objective Caml) is a general-purpose, high-level, multi-paradigm programming language which extends the Caml dialect of ML with object-oriented features. OCaml was created in 1996 by Xavier Leroy, Jérôme Vouillon, Damien Doligez, Didier Rémy, Ascánder Suárez, and others.

The OCaml toolchain includes an interactive top-level interpreter, a bytecode compiler, an optimizing native code compiler, a reversible debugger, and a package manager (OPAM) together with a composable build system for OCaml (Dune). OCaml was developed first in the context of automated theorem proving, and is used in static analysis and formal methods software. Beyond these areas, it has found use in systems programming, web development, and specific financial utilities, among other application domains.

Within computing, cross-platform software (also called multi-platform software, platform-agnostic software, or platform-independent software) is computer software that is designed to work in several computing platforms. Some cross-platform software requires a separate build for each platform, but some can be directly run on any platform without special preparation, being written in an interpreted language or compiled to portable bytecode for which the interpreters or run-time packages are common or standard components of all supported platforms.

For example, a cross-platform application may run on Linux, macOS and Microsoft Windows. Cross-platform software may run on many platforms, or as few as two. Some frameworks for cross-platform development are Codename One, ArkUI-X, Kivy, Qt, GTK, Flutter, NativeScript, Xamarin, Apache Cordova, Ionic, and React Native.

In computer programming, a programming language implementation is a system for executing computer programs. There are two general approaches to programming language implementation:

• Interpretation: The program is read as input by an interpreter, which performs the actions written in the program.
• Compilation: The program is read by a compiler, which translates it into some other language, such as bytecode or machine code. The translated code may either be directly executed by hardware or serve as input to another interpreter or another compiler.

In addition to these two extremes, many implementations use hybrid approaches such as just-in-time compilation and bytecode interpreters.

JVM bytecode is the instruction set of the Java virtual machine (JVM), the language to which Java and other JVM-compatible source code is compiled. Each instruction is represented by a single byte, hence the name bytecode, making it a compact form of data.

Due to the nature of bytecode, a JVM bytecode program is runnable on any machine with a compatible JVM, without the lengthy process of compiling from source code.

CPython is the reference implementation of the Python programming language. Written in C and Python, CPython is the default and most widely used implementation of the Python language.

CPython can be defined as both an interpreter and a compiler as it compiles Python code into bytecode before interpreting it. It has a foreign function interface with several languages, including C, in which one must explicitly write bindings in a language other than Python.

In computer programming, a P-code machine (portable code machine) is a virtual machine designed to execute P-code, the assembly language or machine code of a hypothetical central processing unit (CPU). The term P-code machine is applied generically to all such machines (such as the Java virtual machine (JVM) and MATLAB pre-compiled code), as well as specific implementations using those machines. One of the most notable uses of P-Code machines is the P-Machine of the Pascal-P system. The developers of the UCSD Pascal implementation within this system construed the P in P-code to mean pseudo more often than portable; they adopted a unique label for pseudo-code meaning instructions for a pseudo-machine.

Although the concept was first implemented circa 1966 as O-code for the Basic Combined Programming Language (BCPL) and P code for the language Euler, the term P-code first appeared in the early 1970s. Two early compilers generating P-code were the Pascal-P compiler in 1973, by Kesav V. Nori, Urs Ammann, Kathleen Jensen, Hans-Heinrich Nägeli, and Christian Jacobi, and the Pascal-S compiler in 1975, by Niklaus Wirth.

In computing, machine code is data encoded and structured to control a computer's central processing unit (CPU) via its programmable interface. A computer program consists primarily of sequences of machine-code instructions. Machine code is classified as native with respect to its host CPU since it is the language that the CPU interprets directly. Some software interpreters translate the programming language that they interpret into a virtual machine code (bytecode) and process it with a P-code machine.

A machine-code instruction causes the CPU to perform a specific task such as: