This study presents a comprehensive bibliometric analysis of the Journal of Universal Computer Science (JUCS) covering the period 1994-2024, based on data retrieved from the Scopus database in April 2025. The analysis has been conducted following the scientific procedures and rationales for systematic literature reviews (SPAR-4-SLR) protocol and using mathematical and statistical methods, VOS viewer , and bibliometrix . The article investigates the journal’s publication trends, citation structures, collaboration networks, and thematic evolution over three decades. A comparative review with the study published in 2021 by Baloain and collaborators, shows improved journal metrics, enhanced global recognition, and alignment with emerging research trends. The co-citation and bibliographic coupling analyses highlight JUCS’s strong intellectual connectivity across key domains of computer science, particularly in interdisciplinary areas. Thematic mapping and keyword analysis show a clear transition from classical computing themes to modern topics like artificial intelligence, deep learning, big data, and blockchain, demonstrating the journal’s responsiveness to evolving scientific priorities. The study concludes with general findings, practical implications, and future research directions, emphasizing JUCS’s role as a durable, adaptive, and impactful platform for scholarly output in the global computer science research community.