microsoft/OpenRCA
[ICLR'25] OpenRCA: Can Large Language Models Locate the Root Cause of Software Failures?
Latest metrics (snapshot 2026-10-15)
| stars | 434 |
|---|---|
| forks | 51 |
| issues | 14 |
| pushed_at | 2026-10-14T09:59:53Z |
History
History chart: 1 daily snapshot so far (archive started 2026-10-14). The line fills in as the daily archive grows; full series via the API.
| Date | GitHub stars |
|---|---|
| 2026-10-15 | 434 |
ADC Momentum: 35/100
| Growth velocity | 26 |
|---|---|
| Consistency | 21 |
| Recency | 96 |
| Agent demand | 0 |
| Basis | bootstrap |
ADC Momentum (0-100) = 45% growth velocity (stars/likes gained per day in our daily archive, relative and absolute, percentile-ranked within the category) + 20% consistency (share of recent days with growth) + 20% recency (latest push/update/release, decaying) + 15% agent demand (how often AI agents looked it up via our API/MCP this week). MCP servers use release cadence; LLMs use price cuts, context and recency. Recomputed daily; scores marked "bootstrap" use lifetime rates until the archive has enough days. Method
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[](https://agentdataco.com/repo/microsoft/OpenRCA)<a href="https://agentdataco.com/repo/microsoft/OpenRCA"><img src="https://agentdataco.com/badge/repo/microsoft/OpenRCA.svg" alt="ADC Momentum"></a>Details
| description | [ICLR'25] OpenRCA: Can Large Language Models Locate the Root Cause of Software Failures? |
|---|---|
| url | https://github.com/microsoft/OpenRCA |
| language | Python |
| license | MIT |
| topics | benchmark large-language-models llm llm-agent rca root-cause-analysis software-engineering |
| created_at | 2024-10-30T08:21:05Z |
| homepage | https://aka.ms/openrca |
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