Features¶
🔍 Features
ID |
Title |
SI |
Errors |
|---|---|---|---|
C Language Support |
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Analyze marked content via CLI interface |
FAULT_CLI_ANALYZE_1; FAULT_CLI_ANALYZE_2; FAULT_CLI_ANALYZE_3 |
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Discover the filepaths a specified root directory via CLI interface |
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Export marked content to other formats via CLI interface |
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Customized comment styles |
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C++ Language Support |
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Define new traceability objects in source code |
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Discover Source Code Files |
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Link code to existing need items |
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Python Language Support |
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Extract blocks of reStructuredText embedded within comments |
FAULT_RST_EXTRACTION_1; FAULT_RST_EXTRACTION_2; FAULT_RST_EXTRACTION_3 |
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Rust Language Support |
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YAML Language Support |
Create new Sphinx-Needs directly from a single comment line in your source code. This feature enables developers to maintain traceability information right at the point of implementation, ensuring that requirements, specifications, and code remain synchronized. By embedding traceability markers in comments, you can:
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Discover source code files in a specified root directory. The root directory shall be configurable. |
Support for defining traceability objects in C source code. The C language parser leverages tree-sitter to accurately identify and extract
comments from C source files, including both single-line ( Key capabilities:
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Support for defining traceability objects in C++ source code. Building upon C language support, the C++ parser handles the full complexity of modern C++ syntax including classes, namespaces, templates, and advanced features. The tree-sitter based parser ensures accurate comment extraction and scope detection across various C++ constructs. Enhanced features for C++:
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Support for defining traceability objects in Python source code. The Python language parser provides comprehensive support for Python’s unique comment
and docstring conventions. It can extract traceability markers from both standard
comments ( Python-specific capabilities:
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Support for defining traceability objects in YAML configuration files. The YAML language parser provides comprehensive support for YAML’s structure
and comment conventions. It can extract traceability markers from YAML comments
( YAML-specific capabilities:
|
Support for defining traceability objects in Rust source code. The Rust language parser leverages tree-sitter to accurately identify and extract
comments from Rust source files, including single-line ( Key capabilities:
|
Support for different customized comment styles in source code. The comment structure can be defined in the configuration file. This feature provides flexibility to adapt Sphinx-Codelinks to your project’s existing coding standards and conventions. Define custom markers, prefixes, and delimiters that match your team’s documentation practices without requiring code changes. Configuration options include:
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Link code to existing need items without creating new ones, perfect for tracing implementations to requirements. This feature enables you to establish connections between your source code and existing documentation or requirements defined elsewhere in your Sphinx-Needs documentation. Instead of creating duplicate need objects, you can simply reference existing ones, maintaining a clean and organized traceability structure. Linking capabilities:
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Extract blocks of reStructuredText embedded within comments, allowing you to include rich documentation with associated metadata right next to your code. This powerful feature enables you to write full reStructuredText content directly in your source code comments, which will be extracted and processed as part of your Sphinx documentation. This approach brings documentation closer to implementation, making it easier to keep both synchronized. reStructuredText extraction features:
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It shall be possible to analyze marked content via the CLI interface. The command-line interface provides powerful tools for analyzing and reporting on traceability markers in your codebase without requiring a full Sphinx build. This enables quick validation, continuous integration checks, and standalone reporting. CLI analysis capabilities:
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It shall be possible to specify a root directory for the CLI interface. All files in and below this directory shall be discovered. The discovery feature provides intelligent file system traversal to identify all relevant source files within a project structure. This enables bulk operations and ensures comprehensive coverage of your codebase. Discovery features:
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It shall be possible to export marked content to other formats via the CLI interface. The export functionality enables transformation of extracted traceability data into various output formats for use in external tools, reports, or downstream processing. This makes Sphinx-Codelinks a versatile component in your documentation toolchain. Export capabilities:
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