Used LRSTAR Parser & Lexer Generator for Windows?


Editors’ Review

Download.com staff
LRSTAR is a powerful LALR(k) parser generator that uses compressed-matrix tables to create exceptionally fast compiler front-ends and language processors. It generates code primarily for C and C++ environments.
  • Pros

    • Builds fast compilers using compressed-matrix parser tables.
    • Compiler front-ends achieve 1,000,000 lines per second throughput.
    • Solves the specific "typedef" problem in complex C grammars.
    • Supports TBNF grammar notation for automatic Abstract Syntax Tree generation.
    • DFA lexical analyzers process 30,000,000 tokens per second.
  • Cons

    • Compiler front-end source code requires manual rewriting for Java or C# output.
    • Primarily designed around Microsoft Visual Studio C/C++ work spaces.

Used LRSTAR Parser & Lexer Generator for Windows?


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Full Specifications

GENERAL
Release
Latest update
Version
3.0.210
OPERATING SYSTEMS
Platform
Windows
Operating System
  • Windows Vista
  • Windows 7
  • Windows 10
  • Windows XP
Additional Requirements
None
POPULARITY
Total Downloads
552
Downloads Last Week
0

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Developer’s Description

Generate swift compilers and language processors via compressed-matrix parser tables in C/C++.
LRSTAR is a fast LALR(k) parser generator for C/C++ programmers, that builds very fast compilers and language processors by using compressed-matrix parser tables. Creates compiler front-ends that read source code at 1,000,000 lines per second. LRSTAR reads the powerful TBNF grammar notation which facilitates building an AST automatically and other advanced functionality. Solves the "typedef" problem in C grammars. The compiler front-end source code is in C++, however, a user may re-write the skeleton file in another language, such as C, C#, Java, and then generate code in that language. Contains Microsoft Visual Studio C/C++ work spaces. DFASTAR and DFAC lexer generators are included in the downloads. These generate very fast DFA lexical analyzers which read 30,000,000 tokens per second -- twice the speed of Flex.

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