The parser – is the heart of the language service. The Managed Package Framework (MPF) language classes require a language parser to select information about the code being displayed. A parser separates the text into lexical tokens and then identifies those tokens by type and functionality. A parser is a software component that takes input data (frequently text) and builds a data structure – often some kind of parse tree, abstract syntax tree or other hierarchical structure – giving a structural representation of the input, checking for correct syntax in the process.

The parsing ay be preceded or followed by other steps, or these may be combined into a single step. The parser is often preceded by a separate lexical analyser, which creates tokens from the sequence of input characters; alternatively, these can be combined in scannerless parsing. Parsers may be programmed by hand or may be automatically or semi-automatically generated by a parser generator. Parsing is complementary to templating, which produces formatted output.

These may be applied to different domains, but often appear together, such as the scanf/printf pair, or the input (front end parsing) and output (back end code generation) stages of a ompiler. The input to a parser is often text in some computer language, but may also be text in a natural language or less structured textual data, in which case generally only certain parts of the text are extracted, rather than a parse tree being constructed.

Parsers range from very simple functions such as scanf, to complex programs such as the frontend of a C++ compiler or the HTML parser of a web browser. An important class of simple parsing is done using regular expressions, where a regular expression defines a regular language, and then the regular expression engine automatically generates a parser for that language, allowing attern matching and extraction of text. In other contexts regular expressions are instead used prior to parsing, as the lexing step whose output is then used by the parser.

The use of parsers varies by input. In the case of data languages, a parser is often found as the file reading facility of a program, such as reading in HTML or XML text; these examples are markup languages. In the case of programming languages, a parser is a component of a compiler or interpreter, which parses the source code of a computer programming language to create some form of internal representation; the parser is a key step in the compiler frontend.

Programming languages tend to be specified in terms of a deterministic context-free grammar because fast and efficient parsers can be written for them. For compilers, the parsing itself can be done in one pass or multiple passes – see one-pass compiler and multi-pass compiler. Context- free grammars are limited in the extent to which they can express all of the requirements of a language. Informally, the reason is that the memory of such a language is limited.

The grammar cannot remember the presence of a construct over an arbitrarily long input; this is necessary for a language in which, for example, a ame must be declared before it may be referenced. More powerful grammars that can express this constraint, however, cannot be parsed efficiently. Thus, it is a common strategy to create a relaxed parser for a context-free grammar which accepts a superset of the desired language constructs (that is, it accepts some invalid constructs); later, the unwanted constructs can be filtered out at the semantic analysis (contextual analysis) step.

Parsing or syntactic analysis is the process of analysing a string of symbols, either in natural language or in computer languages, according to the rules of a formal rammar. The term parsing comes from Latin pars (orationis), meaning part (of speech). [1][2] The term has slightly different meanings in different branches of linguistics and computer science. Traditional sentence parsing is often performed as a method of understanding the exact meaning of a sentence, sometimes with the aid of devices such as sentence diagrams.

It usually emphasizes the importance of grammatical divisions such as subject and predicate. Within computational linguistics the term is used to refer to the formal analysis by computer of a sentence r other string of words into its constituents, resulting in a parse tree showing their syntactic relation to each other, which may also contain semantic and other information. The term is also used in psycholinguistics when describing language comprehension.

In this context, parsing refers to the way that human beings analyze a sentence or phrase (in spoken language or text) “in terms of grammatical constituents, identifying the parts of speech, syntactic relations, etc. ” [2] This term is especially common when discussing what linguistic cues help speakers to interpret garden-path sentences. Within computer science, the term is used in the analysis of computer languages, referring to the syntactic analysis of the input code into its component parts in order to facilitate the writing of compilers and interpreters.

Types of parser The task of the parser is essentially to determine if and how the input can be derived from the start symbol of the grammar. This can be done in essentially two ways: Top- down parsing- Top-down parsing can be viewed as an attempt to find left-most derivations of an input-stream by searching for parse trees using a top-down expansion of the given formal grammar rules. Tokens are consumed from left to right.

Inclusive choice is used to accommodate ambiguity by expanding all alternative right-hand-sides of grammar rules Bottom-up parsing – A parser can start with the input and attempt to rewrite it to the start symbol. Intuitively, the parser attempts to locate the most basic elements, then the elements containing these, and so on. LR parsers are examples of bottom-up parsers. Another term used for this type of parser is Shift-Reduce parsing. LL parsers and recursive-descent parser are examples of top-down parsers which cannot accommodate left recursive production rules.

Although it has been believed that simple implementations of top-down parsing cannot accommodate direct and indirect left-recursion and may require exponential time and space complexity while parsing ambiguous context-free grammars, more sophisticated algorithms for top-down parsing have been created by Frost, Hafiz, and Callaghan[5][6] which accommodate ambiguity and left recursion in polynomial time and which generate polynomial-size representations of the potentially exponential number of parse trees.

Their algorithm is able to produce both left-most and right-most derivations of an input with regard to a given CFG (context-free grammar). An important distinction with regard to parsers is whether a parser generates a leftmost derivation or a rightmost derivation (see context-free grammar). LL parsers will generate a leftmost derivation and LR parsers will generate a rightmost derivation (although usually in reverse). [4] Overview of process The following example demonstrates the common case of parsing a computer language with two levels of grammar: lexical and syntactic.

The first stage is the token generation, or lexical analysis, by which the input character stream is split into meaningful symbols defined by a grammar of regular expressions. For example, a alculator program would look at an input such as and split it into the tokens 12, *, (, 3, +, A, 2, each of which is a meaningful symbol in the context of an arithmetic expression. The lexer would contain rules to tell it that the characters *, +, A, ( and ) mark the start of a new token, so meaningless tokens like “12*” or “(3” will not be generated.

The next stage is parsing or syntactic analysis, which is checking that the tokens form an allowable expression. This is usually done with reference to a context-free grammar which recursively defines components that can make up an expression and the order in which they must appear. However, not all rules defining programming languages can be expressed by context-free grammars alone, for example type validity and proper declaration of identifiers.

These rules can be formally expressed with attribute grammars. The final phase is semantic parsing or analysis, which is working out the implications of the expression Just validated and taking the appropriate action. In the case of a calculator or interpreter, the action is to evaluate the expression or program, a compiler, on the other hand, would generate some kind of code. Attribute grammars can also be used to define these actions.