RACK (Rapid Assurance Curation Kit)
Overview
RACK (Rapid Assurance Curation Kit) is a semantic triplestore backed by an ontology. The ontology (or what we also call the data model) is tailored for curating evidence from certification artifacts of software systems. Evidence to show that a software package is fit-for-purpose can come from multiple subsystem providers, each generating data using different tools, in different formats, captured in different levels of granularity. As a curation platform, RACK uses its data model to normalize and organize the data. It also verifies that the ingested data is compliant with constraints specified by the data model, such as data types and cardinalities. RACK also takes as input the provenance of the data, as well as its relationship to the structure of the relevant system. Specifically, RACK provides a data ingestion interface for use by data providers whose primary focus is to generate evidence from which assurance arguments can be crafted. RACK also provides a query interface for use by data consumers whose primary focus is the construction of compelling assurance arguments. RACK queries allow users to find evidence related to diverse parts of the target system, understand where that evidence came from, and what the evidence infers about that system. RACK is a vendor agnostic data curation system. Requirements can be maintained in a third-party tool such as DOORS; source code in Git; models in Cameo Teamwork Cloud; and build processes in Jenkins. RACK pulls evidential data from all these sources into a knowledge graph from which it can be queried and the returned results can be used to show whether a system meets its goals of safe and secure operation. We also provide an Eclipse-based IDE called RITE (RACK Integrated CerTification Environment) that seamlessly connects with RACK. RITE allows for easy ingestion of data into RACK, development of data model using SADL (Semantic Application Design Language), creation of ingestion packages, and more. Besides these basic data modeling and curation features, RITE also provides functionalities and GUI-support for easy generation of assurance cases and compliance reports to aid in system certification.
Playlist
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RACK (Rapid Assurance Curation Kit) Tutorial
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RITE Tutorial
Links
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Joint work by GE Aerospace Research and Galois
Contacts
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Kit Siu, GE Aerospace Research, siu at geaerospace dot com
Contributors
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Abha Moitra, Paul Cuddihy, Daniel Russell, David Archer, Eric Mertens, Paul (Baoluo) Meng, Mike Durling, Craig McMillan, Jenny Williams, Saswata Paul, Sarat Varanasi, Kevin Quick, John Interrante, Valentin Robert, Chris Alexander
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Moitra, A. (2023). RACK: A Semantic Model and Triplestore for Curation of Assurance Case Evidence. In P. Cuddihy, K. Siu, D. Archer, E. Mertens, D. Russell, K. Quick, … F. Bitsch (Eds.), "Computer Safety, Reliability, and Security. SAFECOMP 2023 Workshops" (pp. 149–160). "Cham": "Springer Nature Switzerland". http://doi.org/10.1007/978-3-031-40953-0_13
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Cuddihy, P., Russell, D., Mertens, E., Siu, K., Archer, D., & Williams, J. (2023). Aviation Certification Powered by the Semantic Web Stack. In International Sematic Web Conference ISWC 2023 (pp. 345–361). "Cham": "Springer Nature Switzerland". http://doi.org/10.1007/978-3-031-47243-5_19
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Moitra, A., Cuddihy, P., Siu, K., Meng, B., Interrante, J., Archer, D., … Russell, D. (2022). A Semantic Reference Model for Capturing System Development and Evaluation. 2022 IEEE 16th International Conference on Semantic Computing (ICSC), 173–174. http://doi.org/10.1109/ICSC52841.2022.00035
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Moitra, A., Siu, K., Cuddihy, P., Russell, D., Mertens, E., Archer, D., & Quick, K. (2024). Enabling Development of an Extensible, Multi-Perspective Ontology. In 2024 IEEE 18th International Conference on Semantic Computing (ICSC) (pp. 77–80). http://doi.org/10.1109/ICSC59802.2024.00018
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McMillan, C., Lee, L., Russell, D., Prince, D., Hasanovic, N., Durling, M., … Kleven, E. (2024). Verification and Validation of Model-Based Systems Requirements and Design Leveraging Formal Methods to Increase Development Assurance. In 2024 SAE AeroTech. Charlotte, NC.
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Paul, S., Alexander, C., Durling, M., Siu, K., Prince, D., Meng, B., … Stuart, D. (2023). Automated DO-178C Compliance Summary through Evidence Curation. 2023 IEEE AIAA 42nd Digital Avionics Systems Conference (DASC), 1–10. http://doi.org/10.1109/DASC58513.2023.10311159
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Paul, S., Siu, K., Meng, B., Durling, M., Prince, D., McMillan, C., & Shackleton, J. (2024). A Semantic Tri Plestore- Based ARP 4 754A Compliance Summary Dashboard. In 2024 AIAA DATC/IEEE 43rd Digital Avionics Systems Conference (DASC) (pp. 1–10). http://doi.org/10.1109/DASC62030.2024.10749136
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Paul, S. (2024). Assurance Case Synthesis from a Curated Semantic Triplestore. In Computer Safety, Reliability, and Security. Springer Nature Switzerland. (Original work published September 2024)
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Russell, D., Moitra, A., Siu, K., & McMillan, C. (2022). Modeling a DO-178C Plan and Analyzing in a Semantic Model. In 2022 Annual Reliability and Maintainability Symposium (RAMS) (pp. 1–8). IEEE Press. http://doi.org/10.1109/RAMS51457.2022.9893967
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Herencia-Zapana, H., Russell, D., Prince, D., Siu, K., & Cuddihy, P. (2023). Towards Compliance to Safety Objectives Using Data Curation. 2023 Annual Reliability and Maintainability Symposium (RAMS), 1–8. http://doi.org/10.1109/RAMS51473.2023.10088181