softwareRisk

Description

It leverages the network-like architecture of scientific models together with software quality metrics to identify chains of function calls that are more prone to generating and propagating errors. It operates on tbl_graph objects representing call dependencies between functions (callers and callees) and computes risk scores for individual functions and for paths (sequences of function calls) based on cyclomatic complexity, in-degree and betweenness centrality. The package supports variance-based uncertainty and sensitivity analyses after Puy et al. (2022) <doi:10.18637/jss.v102.i05> to assess how risk scores change under alternative risk definitions.

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Maintainer: ‘Arnald Puy <arnald.puy@pm.me>’

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R Observatory began tracking this package on Mar 10, 2026; it first appeared on CRAN Jan 21, 2026. Releases before tracking aren’t shown.