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An automated software build turns declared source inputs and dependencies into outputs through repeatable tool steps, such as code generation, compilation, linking and packaging. A build description defines those steps and their dependencies; a build system decides their order and may reuse outputs whose relevant inputs have not changed.

For example, changing a header can require recompiling several source files before relinking a computer program. Omitting that dependency can produce a stale executable even when every individual compiler invocation succeeds. In continuous integration, the automated build provides a repeatable check of the integrated revision, often combined with tests.^[ref] Repeatability requires identifying tool versions, generated inputs and configuration as well as the main source files.

A compiler translates a program from one representation to another while aiming to preserve its programming language semantics. Its input might be source code or an intermediate representation; its output might be another programming language, bytecode, an intermediate representation, or machine code. Producing machine code is therefore one possible destination, rather than the definition of compilation. For example, the LLVM 20.1.0 tutorial translates an abstract syntax tree into an intermediate representation before introducing execution.^[ref]

Compilation can use an abstract syntax tree for checking and transformations such as constant folding before producing machine code. These are useful possibilities, not a compulsory sequence of separate stages for every compiler. The central distinction is between translating a program and executing its operations: a compiler can translate x*(2+3)-4 without knowing the input value of x, whereas an interpreter needs that value to produce this program expression's result.

Different representations expose different questions. Source code preserves what a programmer wrote; an abstract syntax tree exposes grouping; a type system checks permitted combinations; a stack machine makes operand movement explicit. Retaining abstract syntax tree source locations across compilation helps an error message identify the original construct even after constant folding has changed its shape. A malformed x*(2+)-4 is a programming language syntax error; an unavailable x in the valid example is instead a missing input. Locating the failing rule is more helpful than treating both as an unexplained execution failure.

A computer program specifies operations or constraints that an implementation can execute or interpret. Its representation can be source code, bytecode or machine code; the same intended computation can have several computer program representations. Its behavior depends on the language semantics, input and execution environment.

For example, a source expression adding two variables is not yet one fixed result. A compiler can translate it into lower-level operations, while an interpreter or CPU performs those operations for particular values. Calling a library or reading a file makes additional parts of the environment relevant. A computer program is consequently distinct from its one observed execution trace and from the abstract algorithm it implements: two programs can implement the same algorithm with different representations, error behavior or resource costs.

An interpreter executes a program's operations according to its programming language semantics. It can recursively evaluate an abstract syntax tree, or follow an instruction sequence using an execution state such as a stack and an instruction pointer. It need not repeatedly read source code characters, and it need not use an abstract syntax tree at all.

Compilation and interpretation can coexist. In CPython, Python source code is compiled into bytecode for execution by an interpreter; its bytecode is not promised to remain stable between releases.^[ref] The Python 3.14 compile function accepts text or an abstract syntax tree and can produce a code object, which eval or exec can execute.^[ref] These operations make translation and execution separately accessible without requiring them to live in different applications.

Just-in-time compilation gives another combination: an interactive implementation can translate a submitted program expression into machine code and then execute it immediately. The LLVM 20.1.0 tutorial demonstrates this by adding an intermediate representation module to its just-in-time compilation facility, looking up the generated function, and calling it.^[ref] Thus calling a programming language permanently "compiled" or "interpreted" hides an implementation choice: ask which representation is translated, which is executed, and when.