Software teams need change-risk scores that can guide continuous integration decisions such as review prioritization, test scheduling, and downstream validation before risky changes are merged or released. However, open-source teams often lack deployable tools for surfacing these risk signals in everyday CI workflows. We present DRS-OSS, an open-source diff-risk scoring tool for continuous integration workflows. DRS-OSS is designed as a deployable and customizable pipeline rather than as a standalone prediction model. It combines a REST API gateway, containerized model services, a developer dashboard, GitHub integration, and a replication package that lets users retrain or replace the backend with other transformer models. The bundled workflow combines commit messages, commit diffs, and change metrics in a single risk-prediction pipeline. The default packaged backend uses a Llama 3.1 8B sequence classifier configured for long diffs. Its training recipe uses parameter-efficient tuning, quantization, CPU offloading, and customization helper scripts so that it can be adapted on modest hardware. We compare DRS-OSS with similar tools and evaluate the bundled classifier on ApacheJIT, where it reaches an ROC-AUC of 0.895 and outperforms prior baselines. From a user-feedback perspective, DRS-OSS has received interest from Uber, Duolingo, and Microsoft in adapting the workflow to their own continuous integration settings. The full tool is released with source code, customization scripts, deployment artifacts, a public repository, a live demo at worldofcode.org/drs, and a demonstration video at youtube.com/watch?v=2FzeRRdNaco.

翻译：软件团队需要变更风险评分来指导持续集成决策，例如在风险变更合并或发布前进行审查优先级排序、测试调度和下游验证。然而，开源团队通常缺乏可在日常CI工作流中呈现这些风险信号的可部署工具。我们提出DRS-OSS，一种面向持续集成工作流的开源差异风险评分工具。DRS-OSS被设计为可部署且可定制的流水线，而非独立的预测模型。它结合REST API网关、容器化模型服务、开发者仪表板、GitHub集成以及一个可让用户用其他Transformer模型重新训练或替换后端的可复现包。其内置工作流将提交消息、提交差异和变更指标整合在单一风险预测流水线中。默认封装的后端使用针对长差异配置的Llama 3.1 8B序列分类器，其训练方案采用参数高效微调、量化、CPU卸载和定制化辅助脚本，以便在普通硬件上进行适配。我们将DRS-OSS与同类工具进行比较，并在ApacheJIT数据集上评估其封装分类器，该分类器的ROC-AUC达到0.895，优于以往基线。从用户反馈来看，Uber、Duolingo和微软已表示有兴趣将DRS-OSS的工作流适配到自身持续集成环境中。该工具的完整版本已发布，包含源代码、定制化脚本、部署工件、公开仓库、在线演示（worldofcode.org/drs）及演示视频（youtube.com/watch?v=2FzeRRdNaco）。