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OpenGrok is a Java-based source code search engine and indexer designed to process large source trees and binaries into a searchable index. It functions as a version control browser, allowing for the exploration and searching of revision histories integrated with version control systems.
The main features of oracle/opengrok are: Code Search Tools, Full-Text Search Engines, Full-Text Inverted Indexes, Source Code Indexing, Code Navigation Tools, Codebase Indexing, Version Control Browsers, Automatic Index Synchronization.
Projects with overlapping indexed features include: universal-ctags/ctags — Universal Ctags is a multi-language symbol indexer and regex-based parsing engine used to extract and catalog… bloopai/bloop — Bloop is an AI code analysis tool and semantic search engine designed for understanding and querying large-scale… etsy/hound — Hound is a self-hosted source code search engine designed to index multiple repositories for high-performance regular… apache/lucene-solr — This project is a full text search engine and enterprise search infrastructure designed for indexing and retrieving… elasticsearch/elasticsearch — Elasticsearch is a distributed search engine and NoSQL document store designed for full-text search and real-time data… huichen/wukong — Wukong is a distributed full-text search engine designed for indexing and retrieving text documents. It functions as a…
Universal Ctags is a multi-language symbol indexer and regex-based parsing engine used to extract and catalog functions, classes, and variables from source code. It functions as a source code indexer that scans files across diverse programming languages to create searchable catalogs of definitions and declarations. The project is distinguished by its extensible parser framework, which allows users to define new language rules using regular expressions and configuration files. It supports complex parsing scenarios through state-based parsing, stack-oriented scope tracking, and guest-parser del
Bloop is an AI code analysis tool and semantic search engine designed for understanding and querying large-scale codebases. It utilizes a high-performance indexing system written in Rust to enable fast symbol and text retrieval across multiple programming languages. The project differentiates itself by using on-device embeddings for semantic code search, allowing users to locate logic based on meaning and intent rather than exact keywords. It combines a language model with a retrieval-augmented generation approach to provide a natural language interface for conversational querying and the gen
Hound is a self-hosted source code search engine designed to index multiple repositories for high-performance regular expression queries. It serves as a multi-repository code indexer that provides a centralized interface for searching across large-scale, private, and versioned codebases. The system utilizes trigram-based indexing to enable fast pattern matching and regular expression lookups without scanning every file. To maintain current search results, it employs automatic synchronization through a combination of periodic polling of remote version control systems and monitoring of local di
This project is a full text search engine and enterprise search infrastructure designed for indexing and retrieving large sets of documents. It provides a comprehensive framework for information discovery using ranked results and linguistic analysis. The system integrates high-dimensional vector similarity search for semantic retrieval alongside traditional full-text capabilities. It distinguishes itself through support for geospatial data retrieval, multilingual text processing, and a search suggestion workflow that includes typo-tolerant query completion and spellchecking. The platform cov