Interpreter (computing)

In computing, an interpreter is software that directly executes encoded logic. Use of an interpreter contrasts the direct execution^[1] of CPU-native executable code that typically involves compiling source code to machine code. Input to an interpreter is a programming language which may be a traditional, well-defined language (such as JavaScript), but can also be a custom language or even a relatively trivial data encoding such as a control table.

W3sDesign Interpreter Design Pattern UML

Historically, programs were either compiled to machine code for native execution or interpreted. Over time, many hybrid approaches were developed. Early versions of Lisp and BASIC runtime environments parsed source code and performed its implied behavior directly. The runtime environments for Perl, Raku, Python, MATLAB, and Ruby translate source code to into an intermediate format before executing to enhance runtime performance. The .NET and Java eco-systems use bytecode for an intermediate format, but in some cases the runtime environment translates the bytecode to machine code (via Just-in-time compilation) instead of interpreting the bytecode directly.

Although each programming language is usually associated with a particular runtime environment, a language can be used in different environments. For example interpreters have been constructed for languages traditionally associated with compilation, such as ALGOL, Fortran, COBOL, C and C++. Thus, the terms interpreted language and compiled language, although commonly used, have little meaning.

History

Interpreters were used as early as 1952 to ease programming within the limitations of computers at the time (e.g. a shortage of program storage space, or no native support for floating point numbers). Interpreters were also used to translate between low-level machine languages, allowing code to be written for machines that were still under construction and tested on computers that already existed.^[2] The first interpreted high-level language was Lisp. Lisp was first implemented by Steve Russell on an IBM 704 computer. Russell had read John McCarthy's paper, "Recursive Functions of Symbolic Expressions and Their Computation by Machine, Part I", and realized (to McCarthy's surprise) that the Lisp eval function could be implemented in machine code.^[3] The result was a working Lisp interpreter which could be used to run Lisp programs, or more properly, "evaluate Lisp expressions".

The development of editing interpreters was influenced by the need for interactive computing. In the 1960s, the introduction of time-sharing systems allowed multiple users to access a computer simultaneously, and editing interpreters became essential for managing and modifying code in real-time. The first editing interpreters were likely developed for mainframe computers, where they were used to create and modify programs on the fly. One of the earliest examples of an editing interpreter is the EDT (Editor and Debugger for the TECO) system, which was developed in the late 1960s for the PDP-1 computer. EDT allowed users to edit and debug programs using a combination of commands and macros, paving the way for modern text editors and interactive development environments.^{[citation needed]}

Use

Notable uses for interpreters include:

Commands and scripts

Interpreters are frequently used to execute commands and scripts

Virtualization

An interpreter acts as a virtual machine to execute machine code for a hardware architecture different from the one running the interpreter.

Emulation

An interpreter (virtual machine) can emulate another computer system in order to run code written for a that system.

Sandboxing

While some types of sandboxes rely on operating system protections, an interpreter (virtual machine) an offer additional control such as blocking code that violates security rules.^{[citation needed]}

Self-modifying code

Self-modifying code can be implemented in an interpreted language. This relates to the origins of interpretation in Lisp and artificial intelligence research.^{[citation needed]}

Compilers versus interpreters

An illustration of the linking process. Object files and static libraries are assembled into a new library or executable.

Programs written in a high-level language are either directly executed by some kind of interpreter or converted into machine code by a compiler (and assembler and linker) for the CPU to execute.

While compilers (and assemblers) generally produce machine code directly executable by computer hardware, they can often (optionally) produce an intermediate form called object code. This is basically the same machine specific code but augmented with a symbol table with names and tags to make executable blocks (or modules) identifiable and relocatable. Compiled programs will typically use building blocks (functions) kept in a library of such object code modules. A linker is used to combine (pre-made) library files with the object file(s) of the application to form a single executable file. The object files that are used to generate an executable file are thus often produced at different times, and sometimes even by different languages (capable of generating the same object format).

A simple interpreter written in a low-level language (e.g. assembly) may have similar machine code blocks implementing functions of the high-level language stored, and executed when a function's entry in a look up table points to that code. However, an interpreter written in a high-level language typically uses another approach, such as generating and then walking a parse tree, or by generating and executing intermediate software-defined instructions, or both.

Thus, both compilers and interpreters generally turn source code (text files) into tokens, both may (or may not) generate a parse tree, and both may generate immediate instructions (for a stack machine, quadruple code, or by other means). The basic difference is that a compiler system, including a (built in or separate) linker, generates a stand-alone machine code program, while an interpreter system instead performs the actions described by the high-level program.

A compiler can thus make almost all the conversions from source code semantics to the machine level once and for all (i.e. until the program has to be changed) while an interpreter has to do some of this conversion work every time a statement or function is executed. However, in an efficient interpreter, much of the translation work (including analysis of types, and similar) is factored out and done only the first time a program, module, function, or even statement, is run, thus quite akin to how a compiler works. However, a compiled program still runs much faster, under most circumstances, in part because compilers are designed to optimize code, and may be given ample time for this. This is especially true for simpler high-level languages without (many) dynamic data structures, checks, or type checking.

In traditional compilation, the executable output of the linkers (.exe files or .dll files or a library, see picture) is typically relocatable when run under a general operating system, much like the object code modules are but with the difference that this relocation is done dynamically at run time, i.e. when the program is loaded for execution. On the other hand, compiled and linked programs for small embedded systems are typically statically allocated, often hard coded in a NOR flash memory, as there is often no secondary storage and no operating system in this sense.

Historically, most interpreter systems have had a self-contained editor built in. This is becoming more common also for compilers (then often called an IDE), although some programmers prefer to use an editor of their choice and run the compiler, linker and other tools manually. Historically, compilers predate interpreters because hardware at that time could not support both the interpreter and interpreted code and the typical batch environment of the time limited the advantages of interpretation.^[4]

Development cycle

During the software development cycle, programmers make frequent changes to source code. When using a compiler, each time a change is made to the source code, they must wait for the compiler to translate the altered source files and link all of the binary code files together before the program can be executed. The larger the program, the longer the wait. By contrast, a programmer using an interpreter does a lot less waiting, as the interpreter usually just needs to translate the code being worked on to an intermediate representation (or not translate it at all), thus requiring much less time before the changes can be tested. Effects are evident upon saving the source code and reloading the program. Compiled code is generally less readily debugged as editing, compiling, and linking are sequential processes that have to be conducted in the proper sequence with a proper set of commands. For this reason, many compilers also have an executive aid, known as a Makefile and program. The Makefile lists compiler and linker command lines and program source code files, but might take a simple command line menu input (e.g. "Make 3") which selects the third group (set) of instructions then issues the commands to the compiler, and linker feeding the specified source code files.

Distribution

A compiler converts source code into binary instruction for a specific processor's architecture, thus making it less portable. This conversion is made just once, on the developer's environment, and after that the same binary can be distributed to the user's machines where it can be executed without further translation. A cross compiler can generate binary code for the user machine even if it has a different processor than the machine where the code is compiled.

An interpreted program can be distributed as source code. It needs to be translated in each final machine, which takes more time but makes the program distribution independent of the machine's architecture. However, the portability of interpreted source code is dependent on the target machine actually having a suitable interpreter. If the interpreter needs to be supplied along with the source, the overall installation process is more complex than delivery of a monolithic executable, since the interpreter itself is part of what needs to be installed.

The fact that interpreted code can easily be read and copied by humans can be of concern from the point of view of copyright. However, various systems of encryption and obfuscation exist. Delivery of intermediate code, such as bytecode, has a similar effect to obfuscation, but bytecode could be decoded with a decompiler or disassembler.^{[citation needed]}

Efficiency

The main disadvantage of interpreters is that an interpreted program typically runs more slowly than if it had been compiled. The difference in speeds could be tiny or great; often an order of magnitude and sometimes more. It generally takes longer to run a program under an interpreter than to run the compiled code but it can take less time to interpret it than the total time required to compile and run it. This is especially important when prototyping and testing code when an edit-interpret-debug cycle can often be much shorter than an edit-compile-run-debug cycle.^[5][6]

Interpreting code is slower than running the compiled code because the interpreter must analyze each statement in the program each time it is executed and then perform the desired action, whereas the compiled code just performs the action within a fixed context determined by the compilation. This run-time analysis is known as "interpretive overhead". Access to variables is also slower in an interpreter because the mapping of identifiers to storage locations must be done repeatedly at run-time rather than at compile time.^[5]

There are various compromises between the development speed when using an interpreter and the execution speed when using a compiler. Some systems (such as some Lisps) allow interpreted and compiled code to call each other and to share variables. This means that once a routine has been tested and debugged under the interpreter it can be compiled and thus benefit from faster execution while other routines are being developed.^{[citation needed]} Many interpreters do not execute the source code as it stands but convert it into some more compact internal form. Many BASIC interpreters replace keywords with single byte tokens which can be used to find the instruction in a jump table.^[5] A few interpreters, such as the PBASIC interpreter, achieve even higher levels of program compaction by using a bit-oriented rather than a byte-oriented program memory structure, where commands tokens occupy perhaps 5 bits, nominally "16-bit" constants are stored in a variable-length code requiring 3, 6, 10, or 18 bits, and address operands include a "bit offset". Many BASIC interpreters can store and read back their own tokenized internal representation.

Toy C expression interpreter

// data types for abstract syntax tree enum _kind { kVar, kConst, kSum, kDiff, kMult, kDiv, kPlus, kMinus, kNot }; struct _variable { int *memory; }; struct _constant { int value; }; struct _unaryOperation { struct _node *right; }; struct _binaryOperation { struct _node *left, *right; }; struct _node { enum _kind kind; union _expression { struct _variable variable; struct _constant constant; struct _binaryOperation binary; struct _unaryOperation unary; } e; }; // interpreter procedure int executeIntExpression(const struct _node *n) { int leftValue, rightValue; switch (n->kind) { case kVar: return *n->e.variable.memory; case kConst: return n->e.constant.value; case kSum: case kDiff: case kMult: case kDiv: leftValue = executeIntExpression(n->e.binary.left); rightValue = executeIntExpression(n->e.binary.right); switch (n->kind) { case kSum: return leftValue + rightValue; case kDiff: return leftValue - rightValue; case kMult: return leftValue * rightValue; case kDiv: if (rightValue == 0) exception("division by zero"); // doesn't return return leftValue / rightValue; } case kPlus: case kMinus: case kNot: rightValue = executeIntExpression(n->e.unary.right); switch (n->kind) { case kPlus: return + rightValue; case kMinus: return - rightValue; case kNot: return ! rightValue; } default: exception("internal error: illegal expression kind"); } }

An interpreter might well use the same lexical analyzer and parser as the compiler and then interpret the resulting abstract syntax tree. Example data type definitions for the latter, and a toy interpreter for syntax trees obtained from C expressions are shown in the box.

Regression

Interpretation cannot be used as the sole method of execution: even though an interpreter can itself be interpreted and so on, a directly executed program is needed somewhere at the bottom of the stack because the code being interpreted is not, by definition, the same as the machine code that the CPU can execute.^[7][8]

Just-in-time compilation

Just-in-time (JIT) compilation is the process of converting an intermediate format (i.e. bytecode) to native code at runtime. As this results in native code execution, it is a method of avoiding the runtime cost of using an interpreter while maintaining some of the benefits that lead to the development of interpreters.

Variations

Control table interpreter

Logic is specified as data formatted as a table.

Bytecode interpreter

Some interpreters process bytecode which is an intermediate format of logic compiled from a high-level language. For example, Emacs Lisp is compiled to bytecode which is interpreted by an interpreter. One might say that this compiled code is machine code for a virtual machine – implemented by the interpreter. Such an interpreter is sometimes called a compreter.^[9][10]

Threaded code interpreter

A threaded code interpreter is similar to bytecode interpreter but instead of bytes, uses pointers. Each instruction is a word that points to a function or an instruction sequence, possibly followed by a parameter. The threaded code interpreter either loops fetching instructions and calling the functions they point to, or fetches the first instruction and jumps to it, and every instruction sequence ends with a fetch and jump to the next instruction. One example of threaded code is the Forth code used in Open Firmware systems. The source language is compiled into "F code" (a bytecode), which is then interpreted by a virtual machine.^{[citation needed]}

Abstract syntax tree interpreter

An abstract syntax tree interpreter transforms source code into an abstract syntax tree (AST), then interprets it directly, or uses it to generate native code via JIT compilation.^[11] In this approach, each sentence needs to be parsed just once. As an advantage over bytecode, AST keeps the global program structure and relations between statements (which is lost in a bytecode representation), and when compressed provides a more compact representation.^[12] Thus, using AST has been proposed as a better intermediate format than bytecode. However, for interpreters, AST results in more overhead than a bytecode interpreter, because of nodes related to syntax performing no useful work, of a less sequential representation (requiring traversal of more pointers) and of overhead visiting the tree.^[13]

Template interpreter

Rather than implement the execution of code by virtue of a large switch statement containing every possible bytecode, while operating on a software stack or a tree walk, a template interpreter maintains a large array of bytecode (or any efficient intermediate representation) mapped directly to corresponding native machine instructions that can be executed on the host hardware as key value pairs (or in more efficient designs, direct addresses to the native instructions),^[14][15] known as a "Template". When the particular code segment is executed the interpreter simply loads or jumps to the opcode mapping in the template and directly runs it on the hardware.^[16][17] Due to its design, the template interpreter very strongly resembles a JIT compiler rather than a traditional interpreter, however it is technically not a JIT due to the fact that it merely translates code from the language into native calls one opcode at a time rather than creating optimized sequences of CPU executable instructions from the entire code segment. Due to the interpreter's simple design of simply passing calls directly to the hardware rather than implementing them directly, it is much faster than every other type, even bytecode interpreters, and to an extent less prone to bugs, but as a tradeoff is more difficult to maintain due to the interpreter having to support translation to multiple different architectures instead of a platform independent virtual machine/stack. To date, the only template interpreter implementations of widely known languages to exist are the interpreter within Java's official reference implementation, the Sun HotSpot Java Virtual Machine,^[14] and the Ignition Interpreter in the Google V8 JavaScript execution engine.

Microcode

Microcode imposes an interpreter between the hardware and the architectural level of a computer.^[18] As such, the microcode is a layer of hardware-level instructions that implement higher-level machine code instructions or internal state machine sequencing in many digital processing elements. Microcode is used in general-purpose central processing units, as well as in more specialized processors such as microcontrollers, digital signal processors, channel controllers, disk controllers, network interface controllers, network processors, graphics processing units, and in other hardware. Microcode typically resides in special high-speed memory and translates machine instructions, state machine data or other input into sequences of detailed circuit-level operations. It separates the machine instructions from the underlying electronics so that instructions can be designed and altered more freely. It also facilitates the building of complex multi-step instructions, while reducing the complexity of computer circuits. Writing microcode is often called microprogramming and the microcode in a particular processor implementation is sometimes called a microprogram. More extensive microcoding allows small and simple microarchitectures to emulate more powerful architectures with wider word length, more execution units and so on, which is a relatively simple way to achieve software compatibility between different products in a processor family.

See also

• Dynamic compilation
• Homoiconicity – Characteristic of a programming language
• Meta-circular evaluator – Type of interpreter in computing
• Partial evaluation – Technique for program optimization
• Read–eval–print loop – Computer programming environment