The EVerest Dataset for Secure Software Engineering
For researchers in secure software engineering, this dataset fills a gap by providing a comprehensive, multi-artifact resource with fine-grained security labels, enabling new research directions.
The paper introduces the EVerest dataset, a multi-artifact resource for end-to-end security verification in software engineering, containing 84 security requirements, 1,445 fine-grained security elements, and trace links. The dataset enabled the discovery and fix of a real security weakness (CWE-1295).
End-to-end security verification, from requirements through architecture to code, requires datasets that span all three artifact types with fine-grained security labels. No existing dataset provides this combination. We present the EVerest dataset, a multi-artifact resource based on EVerest, an industry-driven open-source software stack for electric vehicle charging stations. The dataset includes 84 manually elicited security requirements annotated with security objectives, 1,445 fine-grained security elements (components, entities, data, data flows, states, etc.), acceptance windows, coreferences, and architectural trace links, as well as the EVerest software architecture model, source code, and natural language documentation. It enables research on security requirements classification, named entity recognition, architectural trace linking, and design-time or code-level security verification. During dataset creation, a real security weakness (CWE-1295) was identified, disclosed to the project maintainers, and subsequently fixed. The dataset is publicly available. A short video is available at https://youtu.be/pnn1uqpomvQ.