Interpreted language in the context of Cross-platform software

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.

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.

A command language is a language for job control in computing. It is a domain-specific and interpreted language; common examples of a command language are shell or batch programming languages.

These languages can be used directly at the command line, but can also automate tasks that would normally be performed manually at the command line. They share this domain—lightweight automation—with scripting languages, though a command language usually has stronger coupling to the underlying operating system. Command languages often have either very simple grammars or syntaxes very close to natural language, making them more intuitive to learn, as with many other domain-specific languages.

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.

In computer programming, a global variable is a variable with global scope, meaning that it is visible (hence accessible) throughout the program, unless shadowed. The set of all global variables is known as the global environment or global state. In compiled languages, global variables are generally static variables, whose extent (lifetime) is the entire runtime of the program, though in interpreted languages (including command-line interpreters), global variables are generally dynamically allocated when declared, since they are not known ahead of time.

In some languages, all variables are global, or global by default, while in most modern languages variables have limited scope, generally lexical scope, though global variables are often available by declaring a variable at the top level of the program. In other languages, however, global variables do not exist; these are generally modular programming languages that enforce a module structure, or class-based object-oriented programming languages that enforce a class structure.