Computer, the flagship publication of the IEEE Computer Society, publishes peer-reviewed articles written for and by computer researchers and practitioners representing the full spectrum of computing and information technology, from hardware to software and from emerging research to new applications. The aim is to provide more technical substance than trade magazines and more practical ideas than research journals. Computer seeks to deliver useful information for all computing professionals and students, including computer scientists, engineers, and practitioners of all levels.

Special Issue on Generative AI in the Software Development Lifecycle (SDLC)
Submission Date: 2024-11-20

Generative AI is rapidly reshaping the software development landscape, promising significant improvements across various phases of the Software Development Lifecycle (SDLC), from design and coding to testing, deployment, and beyond. However, as organizations explore the integration of Generative AI tools, they face new challenges and opportunities. This special issue invites submissions that explore the transformative potential of Generative AI in the SDLC, the barriers to adoption, and the long-term implications for software engineering teams and practices.

Scope of Interest:

We invite original research articles, case studies, and thought pieces addressing the role of Generative AI in software development. Potential topics of interest include, but are not limited to:

    How is Generative AI transforming the SDLC?
    Explore how AI-powered tools are changing software design, development, and maintenance processes, with a focus on new workflows and methodologies.
    Applications of Generative AI in SDLC phases:
    Identify the most promising applications of Generative AI across specific SDLC phases such as design, coding, testing, deployment, and post-release monitoring.
    Challenges of integrating Generative AI into existing workflows:
    Discuss the organizational, technical, and cultural barriers to adoption, including concerns around compatibility, cost, and change management.
    Team dynamics and human roles in AI-augmented software teams:
    Analyze the evolving role of human engineers within AI-augmented teams, including the implications of AI on collaboration, communication, and team structures.
    Security challenges unique to Generative AI in SDLC:
    Investigate security vulnerabilities introduced by AI-generated code, models, and processes, and explore potential mitigation strategies.
    Generative AI’s impact on software quality assurance and testing processes:
    Examine how AI-driven tools are enhancing or complicating the processes of testing and validating software, and how organizations can measure improvements in quality and performance.
    Long-term implications of relying on Generative AI for critical development tasks:
    Forecast how organizations can prepare for the strategic, ethical, and operational impacts of relying on AI for critical development functions.
    Measuring success and impact of Generative AI in SDLC:
    Propose methodologies for quantifying the effectiveness and success of Generative AI tools within different SDLC phases.
    Future developments in Generative AI and their potential to revolutionize the SDLC:
    Speculate on upcoming trends and breakthroughs that could further transform the SDLC and software engineering practices.
    Other thoughts, ideas, or concerns related to Generative AI in the SDLC.
    We welcome unique perspectives that address emerging concerns, innovations, or potential risks that have yet to be fully explored.

Special Issue on Game, Film & Interactive Experience Technologies
Submission Date: 2024-12-18

Computer seeks submissions for this upcoming special issue to feature topics relevant to game, film, and interactive experience technology professionals and chief scientists. Submissions should be relevant to near-term and far-term deployment in the development of games, films, and interactive experiences.

We seek papers that explore the following:

    Machine learning for games & interactive experiences
    Generative AI & large language models for game, film, & interactive experience authoring
    Architectures for the networking of games & film production
    Sensor-based games & interactive experiences
    Computational human perception for games & interactive experiences
    Novel architectures for the metaverse
    Large language models that can generate complete feature-length films
    Technologies for building a human-intelligent metaverse
    Game & interactive experience architectures for use in education

Special Issue on Tech Predictions 2025
Submission Date: 2025-01-31

Technology predictions have always been hard to make, yet they attract wide audiences because of their speculative nature and potential impact. Accurate predictions could have substantial impact on business. Degree of speculation as well as potential impact is dramatically amplified with radical changes introduced by pandemics and wars. The ability to correctly predict may differentiate countries that will sustain tragic losses from those that will evade impact. Similarly, technology trends may make a difference in whether industries will entirely go away, undergo complete transformation, or suddenly start blooming.

Technology prediction is hard because it entails technical and business components, as well as a time dimension. Superior technologies have not always won. And those that did win sometimes took much more time to mature and ultimately reach adoption. Technology success depends on technical, production, market, social, and many other aspects.

Successful technology predictions will provide a basis and justification for the prediction, including research and development results that can quantify and qualify prediction. Ideally, the prediction will have been motivated by novel technological aspects or the use thereof.

Over the past ten years, the IEEE Computer Society has conducted technology predictions at the end of each year. Many other organizations around the world do the same. For examples of papers on technology predictions, see the December 2019 issue of Computer, including a rebuttal by Jeff Voas, at that time the incoming EiC of Computer. For examples of technology predictions, see the IEEE Computer Society Press Room, including scorecards from the past 10 years.

Scope of Interest

All submitted papers to this special issue are to focus on state-of-the-art technology predictions from various academic and industry viewpoints. The topics of interests in this special issue include, but are not limited to:

    AI, AGI (Artificial General Intelligence), Large Language Models
    Novel architectures, accelerators, quantum, memory, storage, interconnects
    Sustainability, new energy sources, energy sector digital transformation
    Digital Twins across industries: data centers, aerospace, bridges, dams, etc.
    High Performance computing and data analytics
    Communication technologies 
    Reliability, availability, and serviceability; security
    Continuum of deployment in cloud and edge
    Megatrends, standards and road-mapping
    Predictions in space tech, manufacturing, bio, health, oil/gas, transport, finance
    Personal and pervasive computing technologies
    Societal, legal, and ethical aspects, impact on supply chains, future workforce

Special Issue on Resilient and Sustainable Smart Communities
Submission Date: 2025-03-31

Smart ecosystems are emerging worldwide, addressing the need for both resilient and sustainable development, meeting key performance indicators that consider social and economic factors as well as technological ones. The growth of such smart ecosystems is no longer constrained to urban scenarios but encompasses others including rural and peri-urban environments that have their own challenges, such as the drastic population reduction in the former and the extremely fast increase in the later. 

This special issue will explore how previous research in smart cities can serve as a cornerstone to support the scalable expansion of smart ecosystems, fostering novel business and societal activities, and developing models with the citizens at their epicenter. It will also provide a forum for new approaches and metrics needed when we conceive of technical solutions to reach sustainability and resilience, especially in the context of the complexities of population growth, climate change, and the astonishing increase of the number of cities around the world. The issue will help highlight the role of a data-driven ecosystem, as it may be an agnostic approach for consolidating both resilient and sustainable paradigms, which include computational concepts such Internet of Things and Services, Data Spaces, Distributed Ledger Technologies, Cloud Edge Computing Continuum, and Artificial Intelligence.

The goal of this special issue is to address the domain of smart communities from a computational point of view, to improve the state of the art, and to present recent technological advances and experiences that are employed in these settings and that take into account a circular economy, climate impact, and the like. 

Authors are encouraged to submit original contributions related to resilient and sustainable smart communities. Topics of interest for this special issue include (but are not limited to):

    Smart communities as systems of systems
    Smart city and smart community applications and services
    Smart city and/or smart community pilot projects
    Smart community embedded and cyberphysical systems
    Smart city and smart community management platforms
    Computing for smart communities (IoT, edge/cloud, Industry 4.0, Society 5.0, etc.)
    Communication technologies, including 6G
    Data management and knowledge extraction
    Distributed ledger technologies supporting smart community ecosystems
    Robust smart and circular communities
    Open data initiatives, cases, and applications
    Data spaces for smart ecosystems
    Digital twins and their application to smart communities
    Artificial intelligence (AI) and machine learning (ML) in the smart community domain
    People-centric systems and crowd-based computing in smart communities
    Grassroots movements for resilient and sustainable smart ecosystems
    Tools and techniques for urban co-creation
    Studies on behavioral change aspects for sustainability
    Policy for smart communities and their development
    Business models for resilient and sustainable smart communities