Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page
Demo Data from SIGIR 2026 / reviewers in the wild / expert

Rujiphart Charatvaraphan

dblp:421/7031 · DBLP profile ↗
← Back
1ranked-venue papers
1as first author
1since 2021 · last 2025
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Empirical software engineering · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Empirical software engineering
developer studies		 0.912025
PyGress: Tool for Analyzing the Progression of Code Proficiency in Python OSS Projects · ASE 2025
Empirical software engineering
mining software repositories		 0.912025
PyGress: Tool for Analyzing the Progression of Code Proficiency in Python OSS Projects · ASE 2025

Methods — techniques the papers use, named apart from their topics

CEFR-aligned code analysis · 0.9
YearPublicationVenuePosition
2025 PyGress: Tool for Analyzing the Progression of Code Proficiency in Python OSS Projects
abstract
Assessing developer proficiency in open-source software (OSS) projects is essential for understanding project dynamics, especially for expertise. This paper presents "PyGress", a web-based tool designed to automatically evaluate and visualize Python code proficiency using pycefr, a Python code proficiency analyzer. By submitting a GitHub repository link, the system extracts commit histories, analyzes source code proficiency across CEFR-aligned levels (A1-C2), and generates visual summaries of individual and project-wide proficiency. The PyGress tool visualizes per-contributor proficiency distribution and tracks project code proficiency progression over time. PyGress offers an interactive way to explore contributor coding levels in Python OSS repositories. The video demonstration of the PyGress tool can be found at https://youtu.be/hxoeK-ggcWk, and the source code of the tool is publicly available at https://github.com/MUICT-SERU/PyGress.
Rujiphart Charatvaraphan, Bunradar Chatchaiyadech, Thitirat Sukijprasert, Chaiyong Ragkhitwetsagul, Morakot Choetkiertikul, Raula Gaikovina Kula, Thanwadee Sunetnanta, Ken-ichi Matsumoto
 ASE1