slope_fun

Computes the slope of a simple linear regression of a numeric vector
against its index (<code>seq_along(x)</code>). Non-finite (<code>NA</code>, <code>NaN</code>, <code>Inf</code>) values
are removed prior to computation. If fewer than two finite values remain,
the function returns <code>0</code>.

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

slope_fun function

<dl><dt>x</dt>
<dd>Numeric vector.</dd></dl>

Arguments

Compute the linear slope of a numeric sequence — slope_fun

<dl>

<dt>x</dt>
<dd>Numeric vector.</dd>

</dl>

slope_fun: Compute the linear slope of a numeric sequence

Description

Usage

Value

Arguments

Details

Examples