Saturday, February 17, 2007 Beta 1.0

-Design a programming language that joins in single paradigm features of logic programming and algorithmic programming.
-Benefit from both the power of .net classes and the power of the logic programming.
-Reducing the Complexity of Existing (Logic) Programming Languages. Extend IS applications to logic concepts

1-Introduction to LogicC#.Net language is not a traditional or logic based language but it combines the power of both so the programmer can benefit from logic concepts like matching and backtracking and the power of procedural in computations and resources access.
LogicC#.Net is what is known as a declarative language. This means that given the necessary facts and rules, LogicC#.Net will use deductive reasoning to solve your programming problems. Also Support procedural coding for working with i\o,databases ,complex calculations and resources accessing .
This is in contrast to logic computer languages such as prolog that used in AI application and difficult to use in complex business applications, resources accessing.
Also this is contrast to traditional computer languages, such as C, C++ and C#, which are procedural languages.
In a procedural language, the programmer must provide step by step instructions that tell the computer exactly how to solve a given problem.
In other words, the programmer must know how to solve the problem before the computer can do it.
The LogicC#.Net programmer, on the other hand, only needs to supply a description of the problem and the ground rules for solving it.
From there, the LogicC#.Net system is left to determine how to find a solution.
Because of this declarative (rather than procedural) approach, well-known sources of errors such as loops that carry out one too many or one too few operations are eliminated right from the start.
Because of supporting procedural approach, easy to access resources and doing complex calculations.
LogicC#.Net can support both procedural code and logic code.
2-What Can LogicC#.Net be Used For?
-AI applications
It is very well suited for expert systems and similar AI applications. Frame or rule-based systems, pattern-matching systems.
-Business applications
Benefit from the high level of abstraction, automatic backtracking, enviroment management and the ease and simplicity with which complex data structures are represented, also database and other resources access.

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