synthetic_graph

A synthetic directed graph with cyclomatic complexity values to
illustrate the functions of the package.

datasets

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.

Arnald Puy

softwareRisk

Computation of Node and Path-Level Risk Scores in Scientific
Models

synthetic_graph function

A <code>tbl_graph</code> with:<dl>
<dt>nodes</dt>
<dd>55 nodes</dd><dt>edges</dt>
<dd>122 directed edges</dd>
</dl>

Format

Synthetic citation graph for software risk examples — synthetic_graph

A <code>tbl_graph</code> with:<dl>
<dt>nodes</dt>
<dd>55 nodes</dd>

<dt>edges</dt>
<dd>122 directed edges</dd>


</dl>

synthetic_graph: Synthetic citation graph for software risk examples

Description

Usage

Arguments

Format

Details