Open Issues Need Help
View All on GitHubAI Summary: This GitHub issue aims to achieve complete English/Japanese bilingual support for all Req2Run benchmark documentation. While four key files are already translated, over 56 additional documentation files, including main reports, specifications, and detailed guides, currently exist only in English and need to be translated into Japanese.
Requirements-to-Running-Code benchmark for AI/LLM systems and frameworks—builds, runs, and auto-scores apps across functional and non-functional metrics.
Requirements-to-Running-Code benchmark for AI/LLM systems and frameworks—builds, runs, and auto-scores apps across functional and non-functional metrics.
Requirements-to-Running-Code benchmark for AI/LLM systems and frameworks—builds, runs, and auto-scores apps across functional and non-functional metrics.
AI Summary: This issue describes the implementation of a real-time log aggregation pipeline. The system needs to ingest logs from various sources and formats, perform real-time processing including filtering, parsing, and advanced aggregations, store the data efficiently for time-series queries and full-text search, and provide rule-based and anomaly detection alerting capabilities.
Requirements-to-Running-Code benchmark for AI/LLM systems and frameworks—builds, runs, and auto-scores apps across functional and non-functional metrics.
AI Summary: This issue requests the creation of a baseline implementation for NET-001, a custom binary message protocol server over TCP. The server needs to handle message framing, multiple message types, connection management, and concurrent clients, with a specified file structure for the implementation.
Requirements-to-Running-Code benchmark for AI/LLM systems and frameworks—builds, runs, and auto-scores apps across functional and non-functional metrics.
AI Summary: This issue requests the creation of a baseline implementation for CRYPTO-001, an AES-256-GCM file encryption tool. It requires implementing features like PBKDF2 key derivation, secure key generation, and metadata preservation, along with a CLI and comprehensive testing, following a detailed project structure.
Requirements-to-Running-Code benchmark for AI/LLM systems and frameworks—builds, runs, and auto-scores apps across functional and non-functional metrics.