Bulletin of Computer and Data Sciences

The Bulletin of Computer and Data Sciences (e-ISSN 3072-2926) published by MEDINLIN SOFT is dedicated to providing scholars, researchers, and practitioners a premier platform to advance the fields of computer and data sciences through the dissemination of original research, insightful articles, comprehensive reviews, and case studies. Our unwavering commitment to an open-access model ensures rapid, affordable, and high-quality publishing, making vital research accessible to a global audience.

Bulletin of Computer and Data Science published by MEDINLIN SOFT is an English-language, diamond open access journal published under the CC BY 4.0 license (e-ISSN: 3072-2926). The journal publishes one volume per year, consisting of four issues released in March, June, September, and December. To support timely dissemination of research, accepted papers are published online in the current running issue immediately after completion of the production process. The journal operates a single-blind peer review system and maintains an average time of 75 days from submission to final editorial decision. The current acceptance rate is 17%. In addition, all submitted manuscripts undergo plagiarism screening as part of the journal’s editorial and publication quality-control procedures prior to publication.

Recent Publications

Demystifying security in the software lifecycle: From threats to best practices

Qasem Abu Al-Haija1
1Departmnet of Cybersecurity, Jordan University of Science and Technology, Jordan

The path toward ethical science is paved with diamonds

Nate Breznau1
1German Institute for Adult Education–Leibniz Centre for Lifelong Learning, 53175 Bonn, Germany

Differentially Private Universal Coresets for \((\alpha,\beta)\)-Fair \(k\)-Median and \(k\)-Means Clustering

Iftikhar Ahmad1, Wang Zu2
1University of Agriculture Faisalabad (UAF), Pakistan
2Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China

Modular QBF Compilations for Implication, Abduction, and Repair in Team Semantics

Fei Yu1
1College of Information and Intelligent, Hunan Agricultural University, Changsha, China, 410128

Cost-Sensitive Sparse Random Machines for Imbalanced High-Dimensional Data

Fei Yu1, Liu Wenbing1
1College of Information and Intelligent, Hunan Agricultural University, Changsha, China, 410128

News & Announcements

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Author Guidelines

Helping authors turn robust computer and data science into trusted, citable research.

Reviewer Guidelines

Review with confidence: evaluate validity, strengthen science, support the community.

Publication Ethics

Strong science, clean ethics: the foundation of every BCDS article.

Open Access Policy

Free to read, free to publish—science without barriers.

Meet Our Editorial Members

Prof. Sayan Mukherjee (Late)
Founder and Editor-in-Chief (2020-2025)
Duke University
Statistical Science, Mathematics, and Biostatistics & Bioinformatics
Seifedine Kadry
Lebanese American University, Lebanon
Professor of Data Science
D. P. Kothari
Institute of Technology Management and Research Nagpur India
Engineering and Technology
Diego Alberto Oliva
Universidad de Guadalajara, Mexico
Ingeniería Electro-Fotónica
Mazin Abed Mohammed
University of Anbar, Iraq
Artificial Intelligence and Biomedical Computing
Sondipon Adhikari
The University of Glasgow, Scotland
Engineering Mechanics
Bimal K. Bose
The University of Tennessee, Knoxville, United States
Electrical Engineering and Computer Science
Changjin Xu
Guizhou University of Finance and Economics, China
Neural networks
Nate Breznau
Leibniz Centre for Lifelong Learning, Bonn, Germany
Adult Education
Sanjaya Kumar Panda
National Institute of Technology Warangal, India
Computer Science and Engineering
Orville Vernon Burton
Clemson University College of Arts, United States
Director of the Clemson Cyberinstitute
Paolo Di Giamberardino
Sapienza University of Rome, Italy
Computer, Control, and Management Engineering Antonio
Shonak Bansal
Chandigarh University, India
Nature-Inspired Algorithms
Qasem Abu Al-Haija
Jordan University of Science and Technology, Jordan
Computer & Information Technology

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