Journal of the ACM - Impact Factor

Journal of the ACM | 2025 Impact Factor:3.0 | Cite Score:6.7 | SCOPUS Q1

Impact Factor and Journal Rank of Journal of the ACM

About: The Journal of the ACM (JACM) is a highly prestigious, peer-reviewed scientific journal that publishes original research articles in the field of computer science. Established in 1954, JACM is one of the oldest and most respected journals in the computing community. It serves as a platform for disseminating significant and innovative contributions to all areas of computer science, including theoretical foundations, algorithm design, computational complexity, and practical applications.
Publication Frequency:
The Journal of the ACM publishes articles on a quarterly basis, ensuring the regular dissemination of high-quality research findings.
Peer Review:
All submissions undergo a rigorous peer-review process conducted by experts in the respective fields to ensure the highest standards of quality, originality, and relevance.
Impact:
JACM is renowned for its influential contributions to the advancement of computer science. The journal aims to foster the exchange of ideas, promote innovative research, and address emerging challenges in the field.

Journal Home: Journal Homepage

Editor-in-Chief: Venkatesan Guruswami

Scope: The Journal of the ACM (JACM) is a prestigious peer-reviewed scientific journal published by the Association for Computing Machinery (ACM). It covers a wide range of topics in computer science, including theoretical and practical aspects of computing. Here is an overview of its key focus areas and scope:
1. Algorithms and Data Structures:
Research on the design, analysis, and complexity of algorithms, including data structures, optimization algorithms, and algorithmic game theory.
Studies on algorithmic techniques for problems in computer science, mathematics, and related disciplines.
2. Computational Complexity:
Topics covering the study of complexity classes, hardness of approximation, parameterized complexity, and complexity-theoretic foundations of cryptography.
Research on lower bounds, circuit complexity, and complexity of counting problems.
3. Formal Methods and Verification:
Advancements in formal methods for verifying correctness and reliability of software and hardware systems, including model checking, theorem proving, and static analysis.
Research on program semantics, type theory, and formal specification languages.
4. Machine Learning and Artificial Intelligence:
Topics covering theoretical foundations and applications of machine learning algorithms, including statistical learning theory, reinforcement learning, and neural networks.
Research on AI ethics, fairness, interpretability, and robustness of AI systems.
5. Cryptography and Security:
Advancements in cryptographic protocols, cryptanalysis, and secure multiparty computation.
Research on privacy-preserving technologies, blockchain, and cybersecurity.
6. Databases and Information Retrieval:
Topics covering database management systems, data mining, information retrieval, and knowledge discovery.
Research on query optimization, indexing techniques, and big data analytics.
7. Computer Architecture and Systems:
Advancements in computer architecture, parallel and distributed systems, operating systems, and cloud computing.
Research on memory systems, processor design, fault tolerance, and performance evaluation.
8. Theoretical Computer Science:
Topics covering foundational aspects of computer science, including automata theory, formal languages, computability theory, and complexity hierarchies.
Research on structural graph theory, algorithmic graph theory, and computational geometry.