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Syntax (programming languages)

Form of source code, without regard to meaning

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The most commonly used languages are text-based with syntax based on strings. Alternatively, the syntax of a visual programming language is based on relationships between graphical elements.

When designing syntax, a designer of any language might start by writing down examples of both legal and illegal strings, before trying to figure out the general rules from those examples in use. Such that its general structure of syntax can be determined through its form of composition, so to yield semantically valid ranges everytime for each possible alteration. Or else, it returns errors, and warnings, for each invalid input.

Levels of syntax

Computer language syntax is generally distinguished into three levels:

  • Words – the lexical level, determining how characters form tokens;
  • Phrases – the grammar level, narrowly speaking, determining how tokens form phrases;
  • Context – determining what objects or variables names refer to, if types are valid, etc.

Distinguishing in this way yields modularity, allowing each level to be described and processed separately and often independently.

First, a lexer turns the linear sequence of characters into a linear sequence of tokens; this is known as "lexical analysis" or "lexing".

Second, the parser turns the linear sequence of tokens into a hierarchical syntax tree; this is known as "parsing" narrowly speaking. This ensures that the line of tokens conform to the formal grammars of the programming language. The parsing stage itself can be divided into two parts: the parse tree, or "concrete syntax tree", which is determined by the grammar, but is generally far too detailed for practical use, and the abstract syntax tree (AST), which simplifies this into a usable form. The AST and contextual analysis steps can be considered a form of semantic analysis, as they are adding meaning and interpretation to the syntax, or alternatively as informal, manual implementations of syntactical rules that would be difficult or awkward to describe or implement formally.

Thirdly, the contextual analysis resolves names and checks types. This modularity is sometimes possible, but in many real-world languages an earlier step depends on a later step – for example, the lexer hack in C is because tokenization depends on context. Even in these cases, syntactical analysis is often seen as approximating this ideal model.

The levels generally correspond to levels in the Chomsky hierarchy. Words are in a regular language, specified in the lexical grammar, which is a Type-3 grammar, generally given as regular expressions. Phrases are in a context-free language (CFL), generally a deterministic context-free language (DCFL), specified in a phrase structure grammar, which is a Type-2 grammar, generally given as production rules in Backus–Naur form (BNF). Phrase grammars are often specified in much more constrained grammars than full context-free grammars, in order to make them easier to parse; while the LR parser can parse any DCFL in linear time, the simple LALR parser and even simpler LL parser are more efficient, but can only parse grammars which production rules are constrained. In principle, contextual structure can be described by a context-sensitive grammar, and automatically analyzed by means such as attribute grammars, though, in general, this step is done manually, via name resolution rules and type checking, and implemented via a symbol table which stores names and types for each scope.

Tools have been written that automatically generate a lexer from a lexical specification written in regular expressions and a parser from the phrase grammar written in BNF: this allows one to use declarative programming, rather than need to have procedural or functional programming. A notable example is the lex-yacc pair. These automatically produce a concrete syntax tree; the parser writer must then manually write code describing how this is converted to an abstract syntax tree. Contextual analysis is also generally implemented manually. Despite the existence of these automatic tools, parsing is often implemented manually, for various reasons – perhaps the phrase structure is not context-free, or an alternative implementation improves performance or error-reporting, or allows the grammar to be changed more easily. Parsers are often written in functional programming languages, such as Haskell, or in scripting languages, such as Python or Perl, or in imperative programming languages such as C or C++.

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