Blog entry by HENDRO EKO PRABOWO 5116201006

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Language processing systems translate a natural or artificial language into another representation of that language and, for programming languages, may  also execute the resulting code. In software engineering, compilers translate an artificial programming language into machine code. Other language-processing systems may translate an XML data description into commands to query a database or to an alternative XML representation. Natural language processing systems may translate one natural language to another e.g., French to Norwegian.

A possible architecture for a language processing system for a programming language is illustrated in Picture 1. The source language instructions define the program to be executed and a translator converts these into instructions for an abstract machine. These instructions are then interpreted by another component that fetches the instructions for execution and executes them using (if necessary) data from the environment. The output of the process is the result of interpreting the instructions on the input data.

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Picture 1. The Architecture of a Language Processing System

Of course, for many compilers, the interpreter is a hardware unit that processes machine instructions and the abstract machine is a real processor. However, for dynamically typed languages, such as Python, the interpreter may be a software component.

Programming language compilers that are part of a more general programming environment have a generic architecture (Picture 2.) that includes the following components:

1. A lexical analyzer, which takes input language tokens and converts them to an internal form.
2. A symbol table, which holds information about the names of entities (variables, class names, object names, etc.) used in the text that is being translated.
3. A syntax analyzer, which checks the syntax of the language being translated. It uses a defined grammar of the language and builds a syntax tree.
4. A syntax tree, which is an internal structure representing the program being compiled.
5. A semantic analyzer that uses information from the syntax tree and the symbol table to check the semantic correctness of the input language text.
6. A code generator that ‘walks’ the syntax tree and generates abstract machine code.

Other components might also be included which analyze and transform the syntax tree to improve efficiency and remove redundancy from the generated machine code. In other types of language processing system, such as a natural language translator, there will be additional components such as a dictionary, and the generated code is actually the input text translated into another language.

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Picture 2. A Pipe and Filter Compiler Architecture


There are alternative architectural patterns that may be used in a language processing system (Garlan and Shaw, 1993). Compilers can be implemented using a composite of a repository and a pipe and filter model. In a compiler architecture, the symbol table is a repository for shared data. The phases of lexical, syntactic, and semantic analysis are organized sequentially, as shown in Picture 2., and communicate through the shared symbol table.

This pipe and filter model of language compilation is effective in batch environments where programs are compiled and executed without user interaction; for example, in the translation of one XML document to another. It is less effective when a compiler is integrated with other language processing tools such as a structured editing system, an interactive debugger or a program pretty printer. In this situation, changes from one component need to be reflected immediately in other components. It is better, therefore, to organize the system around a repository, as shown in Picture 3.

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Picture 3. A Repository Architecture for A Language Processing System

This figure illustrates how a language processing system can be part of an integrated set of programming support tools. In this example, the symbol table and syntax tree act as a central information repository. Tools or tool fragments communicate through it. Other information that is sometimes embedded in tools, such as the grammar definition and the definition of the output format 
for the program, have been taken out of the tools and put into the repository. Therefore, a syntax-directed editor can check that the syntax of a program is correct as it is being typed and a pretty printer can create listings of the program in a format that is easy to read.

Source : Sommerville, Ian. 2011. Software Engineering. 9th Ed. Boston: Pearson Education, Inc.

Associated Course: KI142303BKI142303B
[ Modified: Friday, 23 December 2016, 4:21 PM ]