Journal Information
Automated Software Engineering (ASE)
https://link.springer.com/journal/10515Impact Factor: |
3.1 |
Publisher: |
Springer |
ISSN: |
0928-8910 |
Viewed: |
26272 |
Tracked: |
37 |
Call For Papers
Aims and scope Automated Software Engineering is an archival, peer-reviewed journal publishing research, tutorial papers, survey and accounts of significant industrial experience in the foundations, techniques, tools and applications of automated software engineering technology. This includes the study of techniques for constructing, understanding, adapting, and modelling software artifacts and processes. Both automatic systems and collaborative systems are within the scope of the journal, as are computational models of human software engineering activities. Knowledge representations and artificial intelligence techniques applicable to automated software engineering are of interest, as are formal techniques that support or provide theoretical foundations. Topics of interest include, but are not restricted to: specification and design representation schemes, both formal and informal; descriptions and models of the development process; tools and environments to support software development; cognition in software development, including studies of specifiers, designers and implementors, and cognitive properties of representation schemes, programming and programming languages; software development methods, analysis and validation; requirements elicitation, acquisition and formalization; system rationale; software quality and metrics; software reuse and adaptation; animation and execution of specifications and designs; domain modelling and analysis; software visualization; software object management; development of user interfaces; group and team work in software engineering; development of distributed, real-time, embedded and composite systems; systems integration; software evolution and maintenance; system testing; reverse engineering and program understanding; documentation and program explanation. Automated Software Engineering is published bi-yearly by Springer, with worldwide distribution to individuals, industry and institutions. It includes reviews of books, software, conferences, and workshops.
Last updated by Dou Sun in 2026-01-10
Special Issues
Special Issue on Flaky Tests and Beyond: Confronting Non-Determinism in Automated TestingSubmission Date: 2026-01-22Flaky tests erode trust in test suites, inflate maintenance costs, and are prevalent across languages and domains. This special issue of Automated Software Engineering seeks original research papers addressing the challenges of flaky tests as well as non-determinism in testing more generally. We invite novel contributions that advance the understanding, detection, prevention, and mitigation of these challenges across diverse systems and contexts. Building on the momentum of the ICSE Flaky Tests Workshops (FTW 2024-2025), we particularly encourage submissions extending workshop findings with substantial new contributions. However, all high-quality research is welcome, including new studies, tools, empirical evaluations, and industrial experience reports that address the topics of interest. Topics of interest: - Causes of flaky tests. - Costs and consequences of flaky tests. - Debugging of flaky tests. - Detection of flaky tests. - Flakiness in emerging contexts and specialized systems. - Mitigation of flaky tests. - Non-determinism in testing generally. - Repair of flaky tests.
Last updated by Dou Sun in 2026-01-10
Special Issue on Virtual and augmented reality software engineeringSubmission Date: 2026-01-31VR (Virtual Reality) and AR (Augmented Reality) are emerging techniques with promising applications. Major IT companies such as Microsoft, Google, and Apple all have essential investments in the area, and Facebook has even changed its name to Meta to focus on the metaverse, a concept that technically largely depends on virtual reality.
As VR/AR platforms such as Unity, Google ARCore, Apple ARKit, and Meta for Developers are getting more and more popular, thousands of apps have been developed to explore various VR/AR applications such as gaming, education, remote communication, computer-aided operation, etc.
VR/AR software development has a lot of special concerns, such as graphics design and performance optimization, management of 3D assets, testing constraints in the physical world (for AR apps), and additional privacy protection (e.g., tackling the leak of head and body movement information from VR/AR devices).
Meanwhile, VR/AR can be adopted as an important technique to support software engineering practices that are not possible in traditional 2D interfaces. For example, 3D visualization of code and project workspace may largely enhance software productivity.
In this special issue of the Automated Software Engineering Journal, we call for papers from both industry and academia to mutually advance the state of the art and practice in this area, and we expect the special issue to serve as a platform for readers to understand the current research progress in VR/AR software engineering.
Areas of interest include, but are not restricted to:
Requirement analysis and specification of VR/AR software
Modeling and abstraction of VR/AR software
Testing and maintenance of VR/AR software
Performance measurement and optimization of VR/AR software
Program analysis and verification of VR/AR software
Security and privacy concerns in VR/AR software
Mining VR/AR software and software repositories, and creation of a dataset
Empirical studies on VR/AR software development process and products
VR/AR-based IDEs and coding tools
User studies of VR/AR-based software development techniques
VR/AR-based software visualization
The papers will undergo the standard, rigorous journal review process and be accepted only if well-suited to the topic of this special issue and meeting the scientific level of the journal. Final decisions on all papers are made by the Editor in Chief.Last updated by Dou Sun in 2026-01-10
Special Issue on NIER@ASE Track 2025Submission Date: 2026-02-28The Special Issue for the NIER@ASE Track in the Automated Software Engineering Journal aims to provide a platform for showcasing forward-looking, innovative research in software engineering. This special issue invites selected papers from the NIER track at the ASE conference to submit extended versions for publication. Authors are encouraged to submit papers that present significant, original, and unpublished results within these areas. Submissions will undergo a rigorous peer-review process to maintain the journal’s high standards. We invite researchers and practitioners from academia and industry to contribute their cutting-edge research and insights to this special issue. For the list of welcomed topics, please see the following link: https://ause-journal.github.io/26ase-nier.html
Last updated by Dou Sun in 2026-01-10
Special Issue on Advances and Applications in Search-Based Software EngineeringSubmission Date: 2026-03-31Search-Based Software Engineering (SBSE) is a dynamic research field that reformulates software engineering problems as search problems, leveraging optimization techniques to address challenges across the software development lifecycle. By applying computational intelligence methods—ranging from metaheuristics like evolutionary algorithms and simulated annealing to exact optimization techniques—SBSE enables effective and efficient solutions to complex software engineering tasks. This special issue aims to showcase recent advances in SBSE, highlighting innovative applications, theoretical contributions, empirical evaluations, and industrial experiences. The issue will explore how SBSE intersects with emerging trends in AI, machine learning, and automation, pushing the boundaries of software engineering research and practice. We invite submissions of high-quality original research papers addressing topics including (but not limited to): - Innovative Applications of SBSE: Applying SBSE techniques to novel or underexplored areas of software engineering, such as security, sustainability, or AI-driven systems. - Theoretical Analyses: Advancing the understanding of search algorithms tailored for software engineering problems, including multi-objective optimization and robustness analysis. - Empirical Evaluations: Rigorous experimental studies demonstrating the effectiveness and scalability of SBSE methods, with reproducible datasets and benchmarks. - Industrial Experiences: Reports detailing real-world applications of SBSE in industry, including lessons learned and challenges encountered Special Invitation for SSBSE 2025 Papers Authors of well-reviewed papers from the 17th Symposium on Search-Based Software Engineering (SSBSE 2025), held in Seoul in November 2025, are especially encouraged to submit extended versions of their work. To ensure substantial contributions beyond the conference version, submissions must meet the following criteria: - Revised Title: A distinct title differentiating the journal submission from the conference paper. - New Content: At least 30% novel material (e.g., expanded experiments, additional theoretical insights, or new applications). - Clear Discussion: A detailed explanation of how the journal version builds upon the original conference paper. How to Submit Submissions should conform to the journal’s formatting requirements and will undergo rigorous peer review. Authors are encouraged to include supplementary materials (e.g., datasets or experimental results) to enhance reproducibility.
Last updated by Dou Sun in 2026-01-10
Special Issue on Automated, Verifiable, and Generative Approaches to Software EngineeringSubmission Date: 2026-04-30The increasing complexity, dynamism, and scale of modern software systems have intensified the demand for advanced forms of automation throughout the software development lifecycle. The emergence of Generative Artificial Intelligence, particularly Large Language Models (LLMs), combined with architectural and methodological advances such as multi-agent systems, has introduced transformative opportunities for automated analysis, synthesis, verification, and maintenance of software. Simultaneously, the growing importance of correctness, adaptability, and trustworthiness in software-intensive systems underscores the need for rigorous verification and validation frameworks that can seamlessly integrate with automated engineering workflows.
This Special Issue invites high-quality submissions that explore the foundations, methods, and tools required to advance automated, verifiable, and generative approaches to software engineering. We seek contributions offering novel scientific insights, innovative engineering solutions, extensive empirical studies, and significant technological advancements that foster deeper integration between automation, AI-driven engineering, and formal verification. Interdisciplinary works that connect software engineering with artificial intelligence, distributed systems, human–AI collaboration, and cyber-physical systems are also welcome.
By bringing together perspectives on automated synthesis, rigorous verification, agent-based collaboration, and generative modeling, this Special Issue aims to showcase emerging research that can shape the future of trustworthy, adaptive, and scalable software systems.
Scope and Topics of Interest
Submissions are invited on (but not limited to) the following topics:
Automated and Generative Software Engineering
Automated synthesis of software artifacts
Generative AI and LLM-enabled approaches for requirements, modeling, design, code generation, evolution, and maintenance
Integration of LLMs into automated engineering workflows
Tool support for generative modeling, refactoring, design space exploration, and automated testing
Multi-Agent and Distributed Approaches
Architectures and coordination frameworks for multi-agent systems in software engineering
Distributed and collaborative problem-solving for development, verification, and adaptation
Engineering agents for reasoning, negotiation, planning, and decision-making
Practical issues in agent-based engineering frameworks
Verification, Validation, and Correctness
Formal verification of automated or AI-generated artifacts
Compositional theories, correctness proofs, and dynamic verification
Hybrid verification combining formal methods with ML or generative models
Validation of performance, energy, reliability, and security
Runtime verification, monitoring, and self-adaptive assurance
Model-Driven and Architecture-Centric Approaches
Model-driven engineering, transformations, co-simulation, and multi-model integration
Formal specifications of architectures and system behaviors
Automated migration to microservice- or component-based architectures
Domain-specific modeling languages and model synthesis
AI-Driven and Learning-Based Methods
ML and AI for comprehension, traceability, debugging, optimization, and anomaly detection
Automated planning, reasoning, and decision-making for generative or adaptive design
Intelligent agents and learning mechanisms for automation
Predictive models integrated with verification workflows
Applications, Empirical Studies, and Emerging Domains
Industrial case studies on automated, verifiable, or generative engineering
Empirical evaluations, benchmarks, and experimental frameworks
Automated development and formal verification of smart contracts
Managing large-scale ecosystems through automation and AI
Human–AI interaction and collaboration in automated environments
Please note that surveys, systematic literature reviews, and mapping studies fall outside the scope of this Special Issue.
Authors should prepare their manuscript according to the Instructions for Authors available from the Journal’s submission guidelines https://link.springer.com/journal/10515/submission-guidelines. Submitted papers should present original, unpublished work, relevant to one of the topics of the special issue. All submitted papers will be evaluated on the basis of relevance, significance of contribution, technical quality, scholarship, and quality of presentation by at least two independent reviewers. It is the policy of the journal that no submission, or substantially overlapping submission, be published or be under review at another journal or conference at any time during the review process.
Please note that the authors of selected papers presented at AYSDE '25 and MAS-GAIN '25 are invited to submit an extended version of their contributions by taking into consideration both the reviewers’ comments on their conference paper, and the feedback received during presentation at the conference. It is worth clarifying that the extended version is expected to contain a substantial scientific contribution, e.g., in the form of new algorithms, experiments or qualitative/quantitative comparisons, and that neither verbatim transfer of large parts of the conference paper nor reproduction of already published figures will be tolerated.
The extended versions of AYSDE '25 and MAS-GAIN '25 papers will undergo the standard, rigorous journal review process and be accepted only if well-suited to the topic of this special issue and meeting the scientific level of the journal. Final decisions on all papers are made by the Editor in Chief.Last updated by Dou Sun in 2026-01-10
Special Issue on Genetic Improvement, 2026Submission Date: 2026-07-31Genetic Improvement is the application of evolutionary and search-based optimisation methods to the improvement of existing software. It has been used to improve both software functional properties, such as fixing bug or performing automated code transplantation, and software non-functional properties, such as minimising execution time, memory usage, or energy consumption. We invite submissions that discuss recent developments in all areas of research on, and applications of, Genetic Improvement. Topics of interest include both the theory and practice of Genetic Improvement. Applications of GI include, but are not limited to: - Improve runtime efficiency - Decrease memory consumption - Decrease energy consumption - Transplant new functionality - Specialise software - Generate multiple versions of software - Improve low level or binary code - GI techniques in industrial settings - Use of AI/large language models in combination with GI - Use of AI/large language models to improve GI or vice versa
Last updated by Dou Sun in 2026-01-10
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