We have designed the tool in two different approaches: (i) by using a dictionary of English natural language; and (ii) by using the query language of a text database. We describe the technical features of the tool, and demonstrate the applications of its use as well as an alternative approach that does not involve dictionary search. Furthermore, we demonstrate different applications for query text or for text database.
7.2. Syntax Checking of Compiled Web Browsers.
This section is non-normative.
Languages that allow the user to inspect and modify the language syntax that are used on-the-fly (e.g., for JavaScript or XML parsing and transformation) are often more efficient than languages that do not support this capability, because such languages require few extra steps and do not frequently run the risk of being changed (e.g., with manual language configuration). Languages that parse syntax by using the underlying computer language are called “compiler-compilers.” Some of these languages are available with a static analysis engine (e.g., in Microsoft Visual Basic.) However, with static analysis such programs can have a greater performance penalty, due to the extra time needed to detect syntax errors.
This section gives a good account of the syntax checking that is available for a well-known scripting language like Perl.
7.3. Syntax Checking of Compiled Web Applications.
This section is normative.
Many web applications contain code that is written to be executed by other parts of the same application. The execution of the application does not require a full, general type-checking. For example, one may write some HTML to represent a request to submit some data to a web service. The application may then run an external program to submit the data to the service. The data may be represented differently in the external program and in the application executing the application, or it may be presented differently. Although the application executes the external program with no type checking, the execution of the application may still be statically analyzed to detect some syntax errors, such as invalid parameter names.
The following sections describe two techniques for statically analyzing code using a type-checking engine:
Compiling the code and writing a type-checking module which uses the compiled code for the type-checking, as follows:
This technique was first applied in the context of Python.
The syntax of a code fragment could be determined by using type inference to define the necessary functions and structures used in the code.
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Design Tool Combining Keyword Analyzer and Case-based Parser for Developing Natural Language Database Interfaces Video Shimizu Sago Anita Yoke Takashi C&C Information Technology Research Laboratories
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