Journal Information

IEEE Software

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Impact Factor:
3.3
Publisher:
IEEE
ISSN:
0740-7459
Viewed:
29370
Tracked:
10

Call For Papers

IEEE Software is an academic journal published by IEEE. (ISSN 0740-7459, impact factor 3.3).

IEEE Software’s mission is to be the best source of reliable, useful, peer-reviewed information for leading software practitioners—the developers and managers who want to keep up with rapid technology change. The authority on translating software theory into practice, this bimonthly magazine positions itself between pure research and pure practice, transferring ideas, methods, and experiences among researchers and engineers. Peer-reviewed articles and columns by real-world experts illuminate all aspects of the industry, including process improvement, project management, development tools, software maintenance, web applications and opportunities, testing, and usability. Technical articles are peer-reviewed carefully to ensure they offer practical and reliable ideas and techniques to readers. The departments cover key concerns of software development: requirements, design, architecture, tools, technologies, empirical evidence, and quality. We also publish insightful lessons-learned articles by people with stories to tell. Software engineering experts in architecture and design, quality, project management, education, requirements, and many other areas of expertise help guide the selection of what we publish. Our Letters to the Editor, Point-Counterpoint debates, and Sounding Board contributions from thought leaders challenge the status quo and stimulate debate. The magazine has been helping train newcomers to software engineering since 1984, as professors, project managers, and developers pass on articles for their colleagues and students to read.
Last updated by Dou Sun on

Special Issues

Special Issue on Human-Centric AI for Software Engineering Submission Date: 2026-09-07 Artificial Intelligence (AI) is reshaping nearly every facet of software systems — from how we design, test, and deploy them, to how they are maintained and evolved. While AI-driven capabilities promise to dramatically improve software quality and developer productivity, they also raise fundamental challenges: explainability, trust, fairness, human oversight, control, and accountability. These challenges are inherently human-centric: software engineers, users, and stakeholders interact with AI systems, make decisions based on them, and must understand their behavior. In the context of software engineering, a human-centric perspective on AI is essential. When we embed AI components inside software development pipelines or products, we are not merely building smart code — we are co-creating socio-technical systems. The human actors (developers, testers, operators, end users) shape, adapt to, and are affected by these systems. Ignoring human aspects can lead to misaligned goals, a lack of user trust, unintended behaviors, or systemic failures. This special issue of IEEE Software invites high-quality contributions exploring the intersection of AI, software engineering, and human-centric design. We welcome papers from two complementary angles: (1) Human-centered AI, focusing on how humans understand, collaborate with, and shape AI within software engineering workflows; and (2) AI for humans, highlighting how AI can support, augment, and empower developers, testers, operators, and end users. Submissions should emphasize how software engineering methods, tools, and processes can be designed or adapted to preserve human agency, understanding, oversight, and participation when building or using AI-enabled systems —keeping human needs and roles central, rather than addressing trustworthiness or technical properties in isolation. Contributions addressing both developer-focused human-AI topics and end-user-focused interaction and co-creation are encouraged. We seek practical, experience-based, and research-grounded articles that address the integration of human-centric principles into AI for software engineering. Submissions should offer value to practitioners while being grounded in evidence, case studies, frameworks, tools, or reflections on real-world practice. Topics of interest include, but are not limited to: Explainable, interpretable, and transparent AI for developers, operators, and end users Human-in-the-loop and human-AI collaborative development tools Governance, safety, trust, accountability, and ethical alignment in AI-augmented systems Human factors, mental models, and developer experience with AI tools Fairness, bias mitigation, and inclusive AI system design AI-assisted requirements, design, testing, maintenance, and evolution Participatory design, co-creation, and multi-stakeholder collaboration in AI-enabled software Socio-technical ecosystems and organizational practices for human-centered AI DevOps/MLOps pipelines that embed human oversight and feedback End-User interaction with AI-augmented software features Human-AI co-creation for end-user development Empirical and longitudinal studies of AI in software engineering practice Education and workforce development for human-centric AI engineering https://www.computer.org/digital-library/magazines/so/cfp-human-centric-ai
Last updated by Dou Sun on

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