Science of Computer Programming - Elsevier - Impact Factor

Science of Computer Programming - Elsevier | 2024 Impact Factor:1.4 | Cite Score:4.0 | Q3

Impact Factor and Journal Rank of Science of Computer Programming

About: Science of Computer Programming aims to bridge the gap between theory and practice in computer programming and software engineering. It provides a platform for researchers, practitioners, and educators to exchange ideas, share insights, and contribute to the advancement of software development methodologies and technologies.
Objective:
The primary objective of Science of Computer Programming is to serve as a prominent forum for publishing high-quality research articles, reviews, and application papers that advance the understanding and practice of computer programming and software engineering. The journal covers a wide range of topics including programming languages, software development methodologies, formal methods, software testing, program analysis, software architecture, and empirical studies in software engineering. By addressing both theoretical foundations and practical applications, the journal aims to facilitate the development of innovative solutions that improve the reliability, efficiency, and maintainability of software systems.
Interdisciplinary Approach:
Science of Computer Programming adopts an interdisciplinary approach, encouraging contributions that integrate insights from computer science, software engineering, mathematics, and related disciplines. The journal covers diverse interdisciplinary topics such as formal verification of software systems, domain-specific languages, agile software development practices, software metrics and measurement, software evolution and maintenance, and software quality assurance. By promoting collaboration across disciplines, the journal facilitates the dissemination of cutting-edge research that addresses real-world challenges in software development and enhances the productivity and effectiveness of software engineering practices.
Impact:
The impact of Science of Computer Programming is significant in both academic research and practical applications. By publishing rigorous research articles and reviews, the journal contributes to the advancement of theoretical frameworks, methodologies, and technologies in computer programming and software engineering. The journals publications inform the development of new programming paradigms, software tools, and techniques that improve software reliability, scalability, and security. The emphasis on high-quality research and practical relevance ensures that the journals contributions support the continuous evolution and adoption of best practices in software development worldwide.
Significance:
Science of Computer Programming holds significant importance for researchers, educators, practitioners, and industry professionals involved in computer programming, software engineering, and related fields. The journals contributions include advancing theoretical foundations, exploring new applications of software development methodologies, and addressing practical challenges in software design, implementation, and maintenance. By providing insights into the latest developments, emerging trends, and best practices in computer programming and software engineering, the journal serves as a valuable resource for fostering innovation and improving software development practices globally. It supports the continuous advancement of knowledge and technological innovation in the field of computer programming and software engineering.

Journal Home: Journal Homepage

Editor-in-Chief: M.R. Mousavi

Scope: Science of Computer Programming is a peer-reviewed journal that focuses on the science and engineering of computer programming. It covers both theoretical and practical aspects of programming, software engineering, and related areas. The journal publishes high-quality research papers, surveys, and reviews that contribute to the advancement of knowledge in the following key areas:
Programming Methodology:
Methods, techniques, and tools for software design, development, testing, debugging, maintenance, and evolution.
Formal Methods in Software Engineering:
Formal approaches to software specification, verification, validation, and synthesis. This includes formal languages, formal semantics, formal modeling, model checking, and theorem proving.
Programming Languages:
Design, semantics, implementation, and optimization of programming languages. Topics include functional programming, object-oriented programming, logic programming, domain-specific languages, and concurrent/distributed programming.
Software Specification and Verification:
Methods for specifying software requirements, formal specification languages, correctness proofs, program verification techniques, and software testing methodologies.
Software Engineering Practices:
Best practices in software engineering, software architecture, design patterns, software metrics, software quality assurance, software reuse, and empirical studies in software development.
Software Tools and Environments:
Development and evaluation of software development tools, integrated development environments (IDEs), debugging tools, version control systems, and software configuration management.
Software Evolution and Maintenance:
Techniques and tools for software maintenance, software refactoring, software evolution, reverse engineering, software reuse, and legacy system migration.
Empirical Software Engineering:
Empirical studies, experiments, case studies, and evaluations of software engineering practices, methodologies, and tools in real-world settings.
Software Security and Privacy:
Techniques for ensuring software security, secure coding practices, vulnerability analysis, security testing, privacy-enhancing technologies, and cybersecurity.
Software Engineering for AI Systems:
Methods and practices for developing and deploying AI-based systems, including machine learning models, deep learning systems, natural language processing applications, and AI-driven software engineering tools.