Advanced Software Engineering in the Age of Artificial Intelligence: Best Practices, Challenges, and Opportunities

A special issue of Computers (ISSN 2073-431X). This special issue belongs to the section "AI-Driven Innovations".

Deadline for manuscript submissions: 30 April 2027 | Viewed by 188

Special Issue Editor


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Guest Editor
Gina Cody School of Engineering and Computer Science, Concordia University, Montreal, QC H3G 1M8, Canada
Interests: software engineering; distributed computing; cloud-native services and architecture; applied machine learning
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Special Issue Information

Dear Colleagues,

Software engineering is undergoing a period of transformation as Artificial Intelligence (AI) increasingly influences the software lifecycle, from requirements engineering to maintenance. This Special Issue explores the intersection of two distinct but mutually reinforcing domains: AI for Software Engineering (AI4SE), which investigates how AI models can automate and optimize engineering tasks, and Software Engineering for AI (SE4AI), which addresses the rigorous architectural and quality requirements of developing intelligent systems.

As software systems grow in complexity, the industry must address the implications of AI-driven development on technical debt, cost management, and long-term maintainability. This issue seeks to bridge the gap between emerging generative capabilities and established engineering principles such as modularity, observability, architectural principles, and robust testing frameworks. We invite researchers and practitioners to submit work that provides empirical evidence, methodological advancements, and critical analysis of how AI integration impacts the software engineering discipline. Topics are in three related categories, including

I. AI for Software Engineering (AI4SE)

This category focuses on the utilization of machine learning and autonomous systems to enhance traditional engineering processes.

  • Intelligent Requirement Engineering: Methods for automated requirement extraction, conflict detection, and specification refinement.
  • Automated Software Quality Assurance: Enhancing testing protocols, static analysis, and defect prediction for large-scale, distributed systems.
  • Repository Mining and Analysis: Utilizing AI to extract insights from software repositories to improve maintenance, evolution, and technical debt management.
  • AI-Assisted Development Processes: Methodologies for integrating generative models into the CI/CD pipeline while maintaining secure and reproducible build environments.

II. Software Engineering for AI (SE4AI)

This category focuses on the application of rigorous software engineering principles to the development of robust and trustworthy AI models.

  • Architectures for Intelligent Systems: Design patterns and architectural standards for deploying AI models within distributed and cloud-native environments.
  • Trustworthiness and Explainability (XAI): Methodologies for auditing AI systems to ensure transparency, accountability, and reliability in critical domains.
  • Life-Cycle Management for Machine Learning: Applying DevOps and MLOps principles to manage the deployment, monitoring, and versioning of machine learning components.
  • Validation of Autonomous Behavior: Engineering frameworks to assess the robustness, performance, and safety of autonomous agents or learning-based systems.

III. Ethics, Sustainability, and Governance

This category examines the broader societal and operational impacts of integrating AI into software development.

  • Ethical Software Engineering: Assessing the social impact of AI-driven systems and implementing frameworks for bias mitigation and algorithmic fairness.
  • Sustainability and Resource Efficiency: Metrics and measurement models to evaluate the environmental and computational costs of AI-intensive software development.
  • Governance and Compliance: Strategies for aligning AI-integrated software engineering practices with emerging regulatory standards for data privacy and security.

Prof. Dr. Yan Liu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Computers is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • software engineering
  • AI4SE
  • SE4AI
  • explainable AI (XAI)
  • distributed computing
  • cloud-native architecture
  • software quality
  • trustworthy systems
  • ethics in software development
  • lifecycle management

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