AI-based PHP vulnerability detection: a PRISMA 2020 systematic review — supplementary materials
Year: 2026
Type: preprint
Study design: Systematic Review
Abstract: Supplementary materials for a PRISMA 2020 systematic review of empirical studies (2018–2026) on PHP vulnerability detection using machine learning, deep learning, and large language models. Searches covered Scopus and OpenAlex; 58 studies (60 reports) met the eligibility criteria. This deposit includes the frozen protocol, search logs, screening and eligibility registers, the extraction/coding matrix, quality appraisal (five exploratory domains), the blind second-rater audit and its adjudication, VOSviewer bibliometric inputs, analysis scripts that reproduce every reported count, and a SHA-256 manifest. Anonymised for double-blind review; the non-anonymised version will replace it after review.
Source: OSF Preprints (OSF Preprints)
Author: Iwan Setiawan
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7225405019