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Journal of Automated Reasoning - Springer | 2024 Impact Factor:0.8 | Cite Score:3.1 | Q2

Journal of Automated Reasoning

Impact Factor and Journal Rank of Automated Reasoning

  • About: The Journal of Automated Reasoning (JAR) is a peer-reviewed journal dedicated to the advancement of research in automated reasoning. This field encompasses the development of computer systems that simulate, emulate, or extend human reasoning capabilities. JAR covers a broad range of topics including theorem proving, logical reasoning, formal verification, decision procedures, constraint programming, and artificial intelligence. The journal aims to publish high-quality research articles that present new theories, methodologies, tools, and applications in automated reasoning.
  • Objective:
    The primary objective of the Journal of Automated Reasoning is to provide a platform for researchers, practitioners, and scholars to disseminate innovative research findings and developments in the field of automated reasoning. The journal seeks to foster the exchange of ideas and collaboration among experts in computer science, artificial intelligence, mathematics, and related disciplines. JAR aims to advance the understanding and implementation of automated reasoning systems, promoting the development of more efficient and robust reasoning techniques and applications.
  • Interdisciplinary Approach:
    JAR adopts an interdisciplinary approach, integrating research from various fields such as computer science, artificial intelligence, mathematics, logic, and engineering. The journal covers diverse topics including automated deduction, model checking, formal methods, knowledge representation, and reasoning under uncertainty. By embracing contributions from multiple disciplines, JAR facilitates cross-fertilization of ideas and methodologies, addressing complex challenges in automated reasoning and enhancing the development of sophisticated reasoning systems. This interdisciplinary focus helps bridge gaps between theoretical research and practical applications, promoting comprehensive advancements in the field.
  • Impact:
    The impact of the Journal of Automated Reasoning is significant in both academic research and practical applications. By publishing groundbreaking research articles, reviews, and case studies, the journal contributes to the advancement of automated reasoning techniques and their applications in various domains such as software engineering, cybersecurity, robotics, and knowledge management. JARs publications inform the development of new algorithms, tools, and systems for automated reasoning, influencing best practices and technological innovations. The journals emphasis on rigorous research and practical relevance ensures that its contributions have a lasting impact on the field and its related areas.
  • Significance:
    The Journal of Automated Reasoning holds significant importance for researchers, educators, practitioners, and policymakers interested in the development and application of automated reasoning systems. The journals contributions include advancing the theoretical foundations of automated reasoning, improving formal verification techniques, and developing tools for automated theorem proving and decision-making. By promoting high-quality research and fostering interdisciplinary collaborations, JAR supports the creation of reliable, efficient, and scalable automated reasoning systems that address complex problems in various fields. It serves as a vital resource for staying informed about the latest developments, trends, and challenges in automated reasoning.

  • Editor-in-Chief:  Jasmin Blanchette

  • Scope: The Journal of Automated Reasoning is a peer-reviewed journal that focuses on all aspects of automated reasoning, including the theory, implementation, and application of automated reasoning techniques. It covers a wide range of topics, including:
  • Theoretical Foundations:
    Research on the theoretical aspects of automated reasoning, including logic, proof theory, model theory, and formal methods.
  • Automated Theorem Proving:
    Techniques and systems for automated theorem proving in various logics, including first-order logic, higher-order logic, modal logics, and non-classical logics.
  • Model Checking:
    Methods and tools for model checking, including temporal logic model checking, symbolic model checking, and bounded model checking.
  • Formal Verification:
    Applications of automated reasoning in formal verification of hardware and software systems, including verification of safety-critical systems and security protocols.
  • Decision Procedures:
    Development and analysis of decision procedures for various logical theories, including satisfiability (SAT) solvers, satisfiability modulo theories (SMT) solvers, and constraint solvers.
  • Reasoning about Programs:
    Techniques for reasoning about programs, including program analysis, program verification, and program synthesis.
  • Interactive Proof Systems:
    Development and use of interactive proof systems, including proof assistants and tools for formalizing mathematics.
  • Knowledge Representation and Reasoning:
    Methods for knowledge representation and reasoning, including description logics, ontologies, and reasoning about actions and change.
  • Nonmonotonic Reasoning:
    Research on nonmonotonic reasoning, including default reasoning, belief revision, and reasoning under uncertainty.
  • Applications of Automated Reasoning:
    Practical applications of automated reasoning techniques in various domains, including artificial intelligence, mathematics, computer science, biology, and engineering.
  • Logical Frameworks:
    Development and use of logical frameworks for specifying and implementing reasoning systems.
  • Constraint Programming:
    Research on constraint programming and constraint satisfaction problems, including techniques for solving combinatorial problems.
  • Latest Research Topics for PhD in Computer Science
  • Latest Research Topics for PhD in Machine Learning
  • Latest Research Topics for PhD in Artificial Intelligence

  • Print ISSN:  0168-7433

    Electronic ISSN:   1573-0670

  • Abstracting and Indexing:  Science Citation Index Expanded, Scopus.

  • Imapct Factor 2024:  0.8

  • Subject Area and Category:  Computer Sciences, Mathematics

  • Publication Frequency:  Bimonthly

  • H Index:  64

  • Best Quartile:

    Q1:  

    Q2:  Artificial Intelligence

    Q3:  

    Q4:  

  • Cite Score:  3.1

  • SNIP:  1.149

  • Journal Rank(SJR):  0.616