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 AI and Software Engineering: Are We Ready?
Submission Date: 2021-07-30

The use of artificial intelligence (AI) is becoming ubiquitous in every walk of life, from transportation to digital assistants. Software engineering is also benefiting from this rise of AI; however, the full potential has not been exploited so far. While testing is already a beneficiary of this rise, planning, modeling, design, and analysis phases are also catching up quickly. The current maturity of AI is ready to take software engineering to the next level. However, with great potential also come new challenges. Some of the important questions to be asked are:
- How will AI improve, accelerate, or disrupt the current practices of software engineering and vice versa?
- How will AI enable developers to write software that learn like humans?
- Will AI enable engineers to develop smart and intelligent applications or will it threaten their eventual existence because of the AI-created automatic software?
- How do we build explainable software models, how do we generate explanations from them, and how might we evaluate explainability of those models?
- What could be the associated social, societal, legal, ethical, and environmental challenges for the technology spawned by the rise of AI?

This theme issue invites papers covering any aspect related to applications of AI in software engineering, including, but not limited to:
- Explainable AI for software engineering
- AI for better requirements reasoning and refinement
- Software specification, verification, validation, testing, and traceability
- Automated test case generation and prioritization
- Automated (or semi-automated) program repair
- Monitoring running systems (e.g., using anomaly detectors) or optimizing those systems (e.g., using search-based software engineering)
- Mining software repositories to learn predictive and quality models
- Automatic (or human-supported) configuration tools
- Planning, modeling, and analysis
- Software architecture designs and decisions
- Man-machine interaction and machine-to-machine communication
- Human, social, societal, ethical, legal, and environmental aspects
- Regulation and certification
- Case studies, experience reports, benchmarking, best practices, and worst practices (e.g., war stories illustrating important anti-patterns)
- New ideas, emerging results, vision papers, and roadmaps
- Robotics, autonomous driving, NLP, digital assistants, and recommendation systems 

Special Issue on Technology Predictions
Submission Date: 2021-12-01

Publication issue: July 2022

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. 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 both 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, machine learning, and deep learning
    Novel computer technologies such as CPUs, accelerators, memories (including non-volatile), storage, and interconnects
    Communication technologies such as the Internet, wireless, and 5G
    Deployment of cloud and edge technologies
    Predictions from the standards perspective
    Predictions from the road-mapping perspective
    Novel technology applications and use cases, including in manufacturing, biotech, healthcare, oil and gas, transportation, finance, smart cities, and education
    Personal and pervasive computing technologies
    Societal, legal, and ethical aspects
    Security and reliability aspects
    Impact on supply chains
    Future workforce support

Important Dates

    Paper submissions due: 1 December 2021
    First-round review due: 22 January 2022
    Revision due: 5 March 2022
    Final decision notification: 9 April 2022
    Camera-ready submission due: 23 April 2022
    Publication: July 2022

Submission Guidelines

Computer is looking for succinct, practical, readable articles that will appeal to experts and nonexperts alike. Feature articles shouldn’t exceed 6,000 words (minimum 4,500 words), including text, bibliography, and author biographies. Columns shouldn’t exceed 2,500 words (minimum 1,500 words), including text, author biographies, and table text. Each figure and table is counted, on average, as 300 words. Any article that exceeds these word counts may be rejected automatically without going through the review process. Article titles shouldn’t exceed nine words. All manuscripts are subject to peer review on both technical merit and relevance to Computer’s international readership–primarily practicing engineers and academics who are looking for material that introduces new technology and broadens familiarity with current topics. We do not accept white papers, and papers that are primarily theoretical or mathematical must clearly relate the mathematical content to a real-life or engineering application. Manuscripts should not be published or currently submitted for publication elsewhere.

Please read Computer‘s submission guidelines. When you are ready to submit, visit https://mc.manuscriptcentral.com/com-cs.

Guest Editors

Contact the guest editors at co7-22@computer.org.

    Phillip A. Laplante, Penn State
    Dejan Milojicic, Hewlett Packard Labs