ProfOlaf: Semi-Automated Tool for Systematic Literature Reviews

TL;DR

ProfOlaf is a semi-automated tool that combines automation and manual effort to improve the efficiency, quality, and reproducibility of systematic literature reviews using large language models and iterative filtering.

Contribution

The paper introduces ProfOlaf, a novel semi-automated tool that supports systematic reviews with human-in-the-loop filtering and LLM-based article analysis, enhancing existing manual processes.

Findings

Increases review efficiency and reproducibility.

Supports iterative snowballing with human oversight.

Utilizes large language models for article analysis.

Abstract

Systematic reviews and mapping studies are critical to synthesize research, identify gaps, and guide future work, but are often labor-intensive and time-consuming. Existing tools provide partial support for specific steps, leaving much of the process manual and error-prone. We present ProfOlaf, a semi-automated tool designed to streamline systematic reviews while maintaining methodological rigor. ProfOlaf supports iterative snowballing for article collection with human-in-the-loop filtering and uses large language models to help select articles, extract key topics, and answer queries about the content of articles. By combining automation with guided manual effort, ProfOlaf enhances the efficiency, quality, and reproducibility of systematic reviews across research fields. ProfOlaf can be used both as a CLI tool and in web application format. A video demonstrating ProfOlaf is available at: https://youtu.be/R-gY4dJlN3s