Main TrackAIware 2026

Call for Papers – AIware 2026 Main Track

“Software for all and by all” is the future of humanity. AIware, i.e., AI-powered software, has the potential to democratize software creation. We must reimagine software and software engineering (SE), enabling individuals of all backgrounds to participate in its creation with higher reliability and quality. Over the past decade, software has evolved from human-driven Codeware to the first generation of AIware, known as Neuralware, developed by AI experts. Foundation Models (FMs, including Large Language Models or LLMs), like GPT, ushered in software’s next generation, Promptware, led by domain and prompt experts. However, this merely scratches the surface of the future of software. We are already witnessing the emergence of the next generation of software, Agentware, in which humans and intelligent agents jointly lead the creation of software. With the advent of brain-like World Models and brain-computer interfaces, we anticipate the arrival of Mindware, representing another generation of software. Agentware and Mindware promise greater autonomy and widespread accessibility, with non-expert individuals, known as Software Makers, offering oversight to autonomous agents.

The software engineering community will need to develop fundamentally new approaches and evolve existing ones, so they are suitable for a world in which software creation is within the reach of Software Makers of all levels of SE expertise, as opposed to solely expert developers. We must recognize a shift in where expertise lies in software creation and start making the needed changes in the type of research that is being conducted, the ways that SE is being taught, and the support that is offered to software makers.

The 3rd ACM International Conference on AI-powered Software (AIware 2026, https://conf.researchr.org/home/aiware-2026) will be hosted on Mon 6 July and Tue 7 July, 2026, in Montreal, Canada, co-located with FSE’26. AIware 2026 aims to bring different communities together in anticipation of the upcoming changes driven by FMs and look at them from the perspective of AI-powered software and its evolution. AIware 2026 promotes cross-disciplinary discussions, identifies emerging research challenges, and establishes a new research agenda for the community in the Foundation Model era.

New this year

• Fully Open Public Review Process This year’s AIware Main Track adopts a fully open and public peer-review process to increase transparency and accountability in peer review, and promote broader engagement and feedback beyond the program committee. All submissions, reviews, author responses, and discussions will be publicly visible on the OpenReview platform.

• Author-Reviewer Interaction An author response period with multi-round interaction will be incorporated. Authors will have the opportunity to clarify technical details, correct misunderstandings and respond to reviewer concerns in an open forum. Reviewers can also raise further questions during this period.

• Another Opportunity for Rejected Submissions To further support open science and broader dissemination of ideas, all rejected submissions to the Main Track will be invited to participate in the AIware ArXiv Track and have the opportunity to present their work at the conference. Papers in the ArXiv Track will be clearly labeled as non-archival and will not be blocked for submission to other venues.

Topics of Interest

Topics of interest of the AIware conference include, but are not limited to the following:

• How would future software look like in the FM era?
• Agents & SE
• How to integrate legacy software in future AIware?
• Do existing programming models (e.g., object-oriented or functional programming) and SE practices (e.g., test-driven development and agile) remain suitable for developing and maintaining software in the FM era?
• What roles do autonomous agents play in the development and maintenance of software in the FM era?
• How will inner and open source collaboration evolve in the FM era?
• What kind of release engineering practices do we need for FM-powered software applications?
• Are LLMOps comprehensive enough to capture the release engineering needs of AIware in the FM era?
• How do we debug and monitor AIware in the FM era?
• How should we change SE curriculum, training and mentoring in the FM era?
• How to evolve FMs from the perspective of AIware and its makers in the FM era?
• How do human interactions and perceptions shape the development and implementation of AIware in the FM era?
• How do we measure and improve the trustworthiness of AIware in the FM era?
• What are the implications and effectiveness of foundation models in improving software engineering practices and outcomes?
• How does AIware impact developer productivity?

Types of Submissions

The AIware Main Track welcomes submissions from both academia and industry. At least one author of each accepted paper must attend the conference and present the work.

We welcome the following types of contributions:

• Full research papers

• Applied research papers

• Case studies

• Vision papers

• Position and new-idea papers

• Literature reviews and surveys

Page Limits

All submissions must follow the ACM format with strict page limits (excluding references):

• Full-length papers (i.e. case studies, theoretical, applied research papers): 8 pages

• Short papers (i.e., vision, new ideas, and position papers): 2–4 pages

• Literature reviews and surveys: 14–20 pages

Up to 1–2 additional pages are allowed for references only.

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Awards and Journal Invitations

• The best full-length papers will be recognized with the ACM SIGSOFT Distinguished Paper Awards.

• Selected accepted papers will be invited to be substantially revised and extended for a special issue of Empirical Software Engineering (published by Springer).

Submission Guidelines

All authors should use the official “ACM Primary Article Template” as can be obtained from the ACM Proceedings Template page. LaTeX users should use the following latex code at the start of the LaTeX document where the review option produces line numbers for easy reference by the reviewers and the anonymous optician omits author names:

\documentclass[sigconf,review,anonymous]{acmart}

Papers must be submitted electronically in OpenReview platform through the following submission site: https://openreview.net/group?id=ACM.org/AIWare/2026/Conference

Authors are required to sign up active OpenReview accounts for submission. (Institutional email is recommended for registration otherwise it might take a couple of days for OpenReview to manually activate the account.) Instructions for account signing-up. Please visit http://openreview.net/profile after logging in, complete your profile and import your publications. Publications can be automatically imported from DBLP. Instructions for importing publications.

All submissions must be in PDF. All papers must be written in English.

All submissions are subject to ACM policies including ACM Publications Policies, ACM’s new Publications Policy on Research Involving Human Participants and Subjects, ACM Policy and Procedures on Plagiarism, ACM Policy on Prior Publication and Simultaneous Submissions, and the ACM Policy on Authorship and its accompanying FAQ released April 20, 2023. In particular, authors should pay attention to the following points:

• Generative AI tools and technologies, such as ChatGPT, may not be listed as authors of an ACM-published Work. The use of generative AI tools and technologies to create content is permitted but must be fully disclosed in the Work. For example, the authors could include the following statement in the Acknowledgements section of the Work: ChatGPT was used to generate sections of this Work, including text, tables, graphs, code, data, citations, etc. If you are uncertain about the need to disclose the use of a particular tool, err on the side of caution, and include a disclosure in the acknowledgements section of the Work.
• If you are using generative AI software tools to edit and improve the quality of your existing text in much the same way you would use a typing assistant like Grammarly to improve spelling, grammar, punctuation, clarity, engagement or to use a basic word processing system to correct spelling or grammar, it is not necessary to disclose such usage of these tools in your Work.

Review and Publication Process

A double-anonymous review process will be employed for submissions to the main track. The submission must not reveal the identity of the authors in any way. Papers that violate the double-anonymous requirement will be desk-rejected. For more details on the double-anonymous process, please refer to FSE’s submission guidelines.

All submissions will be desk-checked to make sure that they are within the scope of the conference and have satisfied the submission requirements (e.g., page limits and anonymity).

Three members of the Program Committee will then be assigned to each submission for the review process. The Program Committee members can bid on submissions to review. The Program Committee will discuss the review results virtually and decide on the accepted submissions. The accepted submissions will be published in the ACM digital library.

AUTHORS TAKE NOTE: The official publication date is the date the proceedings are made available in the ACM Digital Library. This date may be up to two weeks prior to the first day of the conference. The official publication date affects the deadline for any patent filings related to published work.