Automated Software Engineering - Springer - Impact Factor

Automated Software Engineering - Springer | 2025 Impact Factor:3.9 | Cite Score:7.6 | SCOPUS Q2

Impact Factor and Journal Rank of Automated Software Engineering

About: The Automated Software Engineering journal publishes high-quality, peer-reviewed research articles, case studies, and survey papers that contribute to the theory, design, implementation, and evaluation of automated software engineering technologies. The journal serves as a key resource for researchers, practitioners, and educators interested in automating various aspects of software engineering.
Objectives
The primary objectives of the journal are:
Advancing Automation: To publish research that advances the automation of software engineering tasks.
Theoretical Foundations: To provide a platform for the dissemination of foundational theories in automated software engineering.
Practical Applications: To highlight practical applications and case studies demonstrating the impact of automation in software engineering.
Interdisciplinary Research: To encourage interdisciplinary research that integrates automated software engineering with other fields such as artificial intelligence, machine learning, and human-computer interaction.
Knowledge Dissemination: To facilitate the exchange of knowledge among researchers, practitioners, and educators in the field of automated software engineering.
Key Topics Covered
Software Design Automation: Techniques for automating the design of software systems.
Code Generation and Synthesis: Methods for automatically generating and synthesizing code from high-level specifications.
Software Testing and Verification: Automated approaches for testing and verifying software systems to ensure correctness and reliability.
Model-Driven Engineering: Research on model-driven approaches to software development, including model transformation and code generation.
Program Analysis: Techniques for automated analysis of software programs to detect errors, security vulnerabilities, and performance issues.
Software Maintenance and Evolution: Automated tools and techniques for maintaining and evolving software systems over time.
Software Metrics and Quality Assurance: Automated measurement and assessment of software quality attributes.
AI and Machine Learning in Software Engineering: Application of artificial intelligence and machine learning techniques to automate software engineering tasks.
Human-Computer Interaction: Research on how automation affects human-computer interaction in software engineering tools and environments.
Tool Support and Development Environments: Development and evaluation of automated tools and integrated development environments (IDEs) that support software engineering activities.
Impact and Significance
Automated Software Engineering contributes significantly to:
Technological Innovation: By publishing research that drives advancements in the automation of software engineering processes.
Improved Productivity: By providing insights and technologies that enhance the productivity and efficiency of software engineering teams.
Enhanced Quality: By promoting automated techniques that improve the quality and reliability of software systems.
Interdisciplinary Collaboration: By fostering collaboration between software engineers and researchers from related fields such as AI and HCI.
Educational Value: By serving as an educational resource for students, educators, and professionals interested in automated software engineering.

Journal Home: Journal Homepage

Editor-in-Chief: Tim Menzies

Scope: Automated Software Engineering is a prominent journal that focuses on the automation of software engineering processes. It provides a platform for high-quality research on techniques, methodologies, and tools that support the automation of software development, maintenance, and evolution. Automated Software Engineering publishes innovative research contributions in the following areas:
Software Development Automation: Techniques and tools for automating various stages of the software development lifecycle, including requirements engineering, design, coding, and testing.
Software Maintenance and Evolution: Methods and tools for automating the maintenance and evolution of software systems, including refactoring, reengineering, and migration.
Model-Driven Engineering: Research on model-driven approaches to software development, including model transformation, code generation, and model-based testing.
Program Synthesis and Generation: Techniques for the automatic synthesis and generation of software programs from high-level specifications or example inputs.
Formal Methods and Verification: Application of formal methods to automate the verification and validation of software systems, including static analysis, model checking, and theorem proving.
Software Quality Assurance: Automation of software quality assurance processes, including automated testing, fault detection, and performance evaluation.
Empirical Studies and Evaluation: Empirical studies on the effectiveness and efficiency of automated software engineering techniques and tools, including case studies, experiments, and surveys.
Tool Support and Integration: Development and evaluation of integrated tool environments that support the automation of software engineering tasks.