Table 2_Formal methods for safety-critical machine learning: a systematic literature revie

Alexandra Newcomb's systematic literature review, published on figshare in March 2026, synthesizes 46 peer-reviewed studies from 2020 to mid-2025. The work classifies research into eight formal method categories and analyzes application domains, methodological advances, and persistent challenges in the field.

Use Cases

• Mapping the research landscape based on the eight formal method categories identified in the review
• Identifying gaps and future research opportunities based on the compiled challenges and limitations
• Conducting bibliometric analysis based on the trends and classifications presented in the results
• Comparing the strengths of formal methods over traditional verification techniques as synthesized in the review

Strengths

• Follows a structured protocol for a systematic literature review, as described in the methods.
• Identifies and classifies 46 studies from four major digital libraries.
• Provides a temporal scope covering research from 2020 to mid-2025.

Limitations

• The dataset is a 691.7 KB document, which is a small-scale text summary rather than a primary data collection.
• Row count and column-level documentation are absent; the content structure must be inferred from the document.
• The description is detailed but does not provide access to the underlying data or code from the reviewed studies.

Provenance

Source

Alexandra Newcomb via figshare

Collection Method

Systematic Literature Review of peer-reviewed research from four major digital libraries.

Time Range

2020 to mid-2025

Freshness

Last updated 2026-03-17 13:07:09