iso3

isomorphic source code analyse and synthesis

.NET Roslyn Parser for Arango Graph Database

This project provides a .NET Roslyn-based parser that extracts Abstract Syntax Trees (AST) of every class in a solution. The parsed information is then stored in an Arango Graph Database, with inter-class edges representing method calls.

Table of Contents

1. Introduction
2. Features
3. Prerequisites
4. Installation
5. Usage
6. Configuration
7. Contributing
8. License

Introduction

This parser leverages the power of .NET Roslyn to analyze the source code of a given solution and extracts the AST for each class. The ASTs, along with inter-class relationships based on method calls, are then stored in an Arango Graph Database.

Features

• AST Extraction: Generates Abstract Syntax Trees for every class in a .NET solution using Roslyn.
• Graph Database Storage: Stores the parsed ASTs and inter-class method call relationships in an Arango Graph Database.
• Inter-Class Edges: Establishes edges between classes based on method calls, creating a comprehensive representation of the codebase.

Prerequisites

• .NET SDK: Ensure that you have the .NET SDK installed on your machine. If not, you can download it here.

• ArangoDB: Set up an instance of ArangoDB. You can download ArangoDB here.

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/roslyn-parser-arango.git

2. Navigate to the project directory:

   cd roslyn-parser-arango

3. Restore dependencies:

   dotnet restore

Usage

1. Configure the AppSettings:

   • Open the appsettings.json file and configure the ArangoDB connection settings.

2. Run the Parser:

   dotnet run -- --solutionPath YourSolution.sln

   • Replace YourSolution.sln with the path to your solution file.

3. View the Graph Database:

   Access the ArangoDB web interface to explore the stored ASTs and inter-class relationships.

Configuration

The appsettings.json file contains configuration settings for the ArangoDB connection. Update these settings to match your ArangoDB instance.

{
  "ArangoDB": {
    "Url": "http://localhost:8529",
    "Database": "YourDatabaseName",
    "Username": "YourUsername",
    "Password": "YourPassword"
  }
}


[SQL AST](http://ns.inria.fr/ast/sql/index.html)
[Static analysis of a code in a graph database ](https://greenspector.com/en/articles/2017-06-12-analyse-statique-code-bdd-orientee-graphe/)
[Getting Started C# Syntax Analysis](https://github.com/dotnet/roslyn/wiki/Getting-Started-C%23-Syntax-Analysis)
[ArangoDB Graphs](https://docs.arangodb.com/3.3/Manual/Graphs/)
[cudaHopfield](https://github.com/dariosharp/cudaHopfield)
[PlaidML](https://www.intel.ai/plaidml)
[Что такое логическое программирование и зачем оно нам нужно](https://habr.com/ru/post/322900/)
[Использование графов для решения разреженных систем линейных уравнений](https://habr.com/ru/post/438716/)

arangodb
127.0.0.1:8529

[!["Buy Me A Coffee"](https://www.buymeacoffee.com/assets/img/custom_images/orange_img.png)](https://www.buymeacoffee.com/epirogov)

[Computer Scientists Inch Closer to Major Algorithmic Goal]
(https://www.quantamagazine.org/computer-scientists-inch-closer-to-major-algorithmic-goal-20230623/)


Vector Database for LLM applications
There are many options out there:
- FAISS

- Pinecone

- Milvus

- Qdrant

- Weaviate

- Elasticsearch

- Vespa

- pgvector

- ScaNN

- Vald