Just-in-time compilation in the context of Dynamic recompilation

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.

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.

The first engines for JavaScript were mere interpreters of the source code, but all relevant modern engines use just-in-time compilation for improved performance. JavaScript engines are typically developed by web browser vendors, and every major browser has one. In a browser, the JavaScript engine runs in concert with the rendering engine via the Document Object Model and Web IDL bindings. However, the use of JavaScript engines is not limited to browsers; for example, the V8 engine is a core component of the Node.js runtime system. They are also called ECMAScript engines, after the official name of the specification. With the advent of WebAssembly, some engines can also execute this code in the same sandbox as regular JavaScript code.

Ruby is a general-purpose programming language. It was designed with an emphasis on programming productivity and simplicity. In Ruby, everything is an object, including primitive data types. It was developed in the mid-1990s by Yukihiro "Matz" Matsumoto in Japan.

Ruby is interpreted, high-level, and dynamically typed; its interpreter uses garbage collection and just-in-time compilation. It supports multiple programming paradigms, including procedural, object-oriented, and functional programming. According to the creator, Ruby was influenced by Perl, Smalltalk, Eiffel, Ada, BASIC, and Lisp.

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.

In computer science, ahead-of-time compilation (AOT compilation) is the act of compiling an (often) higher-level programming language into an (often) lower-level language before execution of a program, usually at build-time, to reduce the amount of work needed to be performed at run time.

It is most commonly associated with the act of compiling a higher-level programming language such as C or C++, or an intermediate representation such as Java bytecode or Common Intermediate Language (CIL) code, into native machine code so that the resulting binary file can execute natively, just like a standard native compiler. When being used in this context, it is often seen as an opposite of just-in-time (JIT) compiling.

Dynamic compilation is a process used by some programming language implementations to gain performance during program execution. Although the technique originated in Smalltalk, the best-known language that uses this technique is Java. Since the machine code emitted by a dynamic compiler is constructed and optimized at program runtime, the use of dynamic compilation enables optimizations for efficiency not available to statically-compiled programs (i.e. those compiled by a so-called "batch compiler", as written below) except through code duplication or metaprogramming.

Runtime environments using dynamic compilation typically have programs run slowly for the first few minutes, and then after that, most of the compilation and recompilation is done and it runs quickly. Due to this initial performance lag, dynamic compilation is undesirable in certain cases. In most implementations of dynamic compilation, some optimizations that could be done at the initial compile time are delayed until further compilation at run-time, causing further unnecessary slowdowns. Just-in-time compilation is a form of dynamic compilation.

Adaptive optimization is a technique in computer science that performs dynamic recompilation of portions 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 compilation and interpreting instructions. At another level, adaptive optimization may take advantage of local data conditions to optimize away branches and to use inline expansion to decrease the cost of procedure calls.

Consider a hypothetical banking application that handles transactions one after another. These transactions may be checks, deposits, and a large number of more obscure transactions. When the program executes, the actual data may consist of clearing tens of thousands of checks without processing a single deposit and without processing a single check with a fraudulent account number. An adaptive optimizer would compile assembly code to optimize for this common case. If the system then started processing tens of thousands of deposits instead, the adaptive optimizer would recompile the assembly code to optimize the new common case. This optimization may include inlining code.