Towards Automatically Extracting the Relational Model of an Operating System

Several recent projects have argued that users would benefit from having a relational interface to operating systems state. In this paper, we report on the progress of a tool to automate this data modeling process. While automating schema inference in the general case appears to be intractable, we argue that it is feasible in the limited domain of operating system. Our approach leverages static analysis on the tightly-controlled coding styles common in OS kernels and hybridized techniques from the programming languages and databases literature for inferring and propagating constraints. We use a simple static analysis to extract relation names, types, and arity from constrained operating system source code patterns. We then leverage LLMs and iterative refinement to identify constraints. Our prototype implementation automates the extraction of 10% of the operating system structure into the relational model.

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Publication Details

Published
2025-06-22
DOI
https://doi.org/10.1145/3735106.3736534
Primary Topic
Data Quality and Management
Type
article
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article

Towards Automatically Extracting the Relational Model of an Operating System

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Data Quality and Management
article

Towards Automatically Extracting the Relational Model of an Operating System

Robert Soulé, Brian Choi, Peter Alvaro, Alex Yuan, George V. Neville-Neil, Avi Silberschatz
article en

Abstract

Several recent projects have argued that users would benefit from having a relational interface to operating systems state. In this paper, we report on the progress of a tool to automate this data modeling process. While automating schema inference in the general case appears to be intractable, we argue that it is feasible in the limited domain of operating system. Our approach leverages static analysis on the tightly-controlled coding styles common in OS kernels and hybridized techniques from the programming languages and databases literature for inferring and propagating constraints. We use a simple static analysis to extract relation names, types, and arity from constrained operating system source code patterns. We then leverage LLMs and iterative refinement to identify constraints. Our prototype implementation automates the extraction of 10% of the operating system structure into the relational model.

University City Science Center (US), Yale University (US)
Openalex Percentile: Top 83%
Data Quality and Management
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