The RE’26 Research Track is the main track of the conference. It welcomes original research papers focusing on traditional areas of requirements engineering, as well as new ideas that challenge the boundaries of the field.

This is the right track, if you have developed a novel solution and evaluated it on public or industrial data. This is also the right track, if you have evaluated an existing problem through sound, empirical methods, e.g., controlled experiments, experimental simulations, case studies, surveys, or systematic literature reviews. The main goal of this track is to extend the scientific literature with ground-breaking solutions and solid evaluations.

Our Program Committee includes prominent researchers in requirements engineering and beyond and will ensure fair treatment of your submissions using high-review standards and well-defined criteria. Their role is not just to select papers for the conference, but also to provide constructive and actionable feedback on your research.

This year’s theme is “Sustainability and workforce transformation in the era of generative AI: How to prepare for a future in collaboration with advanced AI tools and assistants”. The theme focuses on innovating requirements engineering by embracing AI, DevOps, sustainability, security, personalization, and agile practices. It aims to equip professionals with the tools and methodologies needed to address the evolving challenges and opportunities in software development, ensuring robust, user-centric, and adaptable systems. As we navigate an increasingly diverse world, we also encourage reflections on how requirements engineering can recognize and respond to the varying needs of a global and heterogeneous user base. While your contribution does not necessarily need to address this specific theme, we highly encourage you to reflect on how you can provide the technical means and knowledge to confront these challenges.

Accepted Papers

Call for Papers

The RE 2026 Research Track welcomes original papers focusing on traditional RE topics, such as requirements elicitation, analysis, prioritization, documentation, validation, evolution, maintenance, and management. It also highly encourages papers covering novel areas at the boundary of RE and other disciplines, including but not limited to software engineering/computer science at large, mechanical/electronic/civil and other engineering, business, social science, psychology, anthropology, and the humanities.

In addition, this year, we particularly encourage submissions addressing the theme “Sustainability and workforce transformation in the era of generative AI: How to prepare for a future in collaboration with advanced AI tools and assistants”. This theme focuses on innovating requirements engineering by embracing AI, DevOps, sustainability, security, personalization, and agile practices. As we navigate an increasingly diverse world, we also encourage reflections on how requirements engineering can recognize and respond to the varying needs of a global and heterogeneous user base. It aims to equip professionals with the tools and methodologies needed to address the evolving challenges and opportunities in software development, ensuring robust, user-centric, and adaptable systems.

Categories of Research Papers

The RE 2026 Research Track invites original submissions of research papers in two categories: Solution-focused papers and Evaluation-focused papers.

Solution-focused Papers present novel or significantly improved solutions for requirements-related problems. This includes new approaches or theories, novel tools, modelling languages, infrastructures, or other technologies. All requirements-related activities, such as elicitation, prioritization, or analysis, are in scope. These papers are mainly evaluated based on the significance of the problem addressed, the novelty of the solution in comparison with existing work, clarity of presentation, technical soundness, and evidence of its benefits. A solution-focused paper does not require a thorough validation; however, a preliminary evaluation is expected to demonstrate the effectiveness, ease of use, or other relevant quality attributes of the proposed solution.

Evaluation-focused Papers empirically assess phenomena, theories, or real-world artifacts (e.g., methods, techniques, or tools) relevant to requirements engineering. These papers apply empirical software engineering approaches, such as experiments, experimental simulations, case studies, surveys, systematic literature reviews, and others, to report on qualitative and/or quantitative data, findings, and results. The discussion of lessons learned can complement the empirical results. The evaluation criteria for these papers focus on the soundness of the research questions, the appropriateness and correctness of the study design and data analysis, and considerations of threats to validity. Replication studies are welcome.

Submit your paper here.

Make sure you select the option “Research Papers (Main Track)”

Review Criteria

Each category of paper has its own review criteria, which reviewers will use for evaluation. Authors are encouraged to study these criteria as well. We also encourage them to read the paper “The ABC of Software Engineering Research” by Klaas-Jan Stol and Brian Fitzgerald, available in Open Access (https://dl.acm.org/doi/10.1145/3241743), which highlights the inherent limitations of each study type. This is to guide the authors in their study design, and to help reviewers determine which aspects of the study design are open to criticism and which are not.

Review Criteria: Solution-focused Papers

• Novelty: to what extent is the proposed solution novel with respect to the state-of-the-art? To what extent is the related work considered? To what extent did the authors clarify their contribution?

• Potential Impact: is the potential impact on research and practice clearly stated? Is the potential impact convincing? Has the proposed solution been preliminarily evaluated to show its potential impact (effectiveness, ease of use, or other relevant quality attributes of the proposed solution)?

• Soundness: has the novel solution been developed following a well-motivated approach? Are the design or methodological choices of the proposed solution justified? Did the authors clearly state the research questions? Is the preliminary evaluation of the solution using rigorous and appropriate research methods? Are the conclusions of the preliminary evaluation logically derived from the data? Did the authors discuss the limitations of the proposed solution? Did the authors discuss the threats to validity of the preliminary evaluation?

• Verifiability: did the authors provide guidelines on how to reuse their artifacts and replicate their results? Did the authors share their software, if any? Did the authors share their data?

• Presentation: is the paper clearly presented and well-structured? To what extent can the content of the paper be understood by the general RE public? If highly technical content is presented, did the authors make an effort to also summarise their proposal intuitively?

Review Criteria: Evaluation-focused Papers

• Novelty: to what extent is the study novel with respect to the related literature? To what extent is the related literature considered? To what extent did the authors clarify their contribution? To what extent does the study contribute to extending the body of knowledge in RE?

• Potential Impact: is the potential impact on research and practice clearly stated? Is the potential impact convincing? Was the study carried out in a representative setting?

• Soundness: Are the research methods justified? Are the research methods adequate for the problem at hand? Did the authors clearly state the research questions, data collection, and analysis? Are the conclusions of the evaluation logically derived from the data? Did the authors discuss the threats to validity?

• Verifiability: did the authors provide guidelines on how to reuse their artifacts and replicate their results? Did the authors share their software? Did the authors share their data?

• Presentation: is the paper clearly presented and well-structured? To what extent can the content of the paper be understood by the general RE public? If highly technical content is presented, did the authors make an effort to also summarise their study intuitively?

Open Science Policy and Open Science Competition

The RE conference has an Open Science Policy with the steering principle that all research results should be accessible to the public and, if possible, empirical studies should be reproducible. In particular, we actively support the adoption of open data and open source principles and encourage all contributing authors to disclose anonymized and curated data to increase reproducibility and replicability.

Please note that the open science policy is optional and therefore not mandatory for submission or acceptance.

However, compliance with the open science policy is expected, and non-compliance must be justified. Therefore, we expect authors to include an explicit Data Availability Statement at the end of their paper (similar to acknowledgments). Specifically, authors should provide details about any artifact disclosed alongside their submission, such as any dataset, tool, script, experimental protocol, codebook, or other executable or non-executable object produced by or used in the research. Otherwise, the authors should justify the reasons why disclosure is not possible, e.g., due to intellectual property or confidentiality agreements.

Moreover, RE’26 supports the Open Science Competition with two challenges to further promote open science in requirements engineering. All authors are invited to take up these challenges. Fame, honor, Open Science Awards, and prize money await you – don’t miss this chance!

Artifacts

The authors of accepted papers will have the opportunity to increase the visibility of their artifacts (such as any dataset, tool, script, experimental protocol, codebook, or other executable or non-executable object produced by or used in the research) and to obtain an artifact badge. Upon acceptance, the authors can submit their artifacts, which will be evaluated by a committee that determines their sustained availability and reusability. All accepted artifacts will compete for the Best Artifact Award.

For further details, please see the Call for Artifacts.

AI-generated Content

Concerning AI-generated content, authors must comply with the IEEE Policy.

“The use of content generated by artificial intelligence (AI) in an article (including but not limited to text, figures, images, and code) shall be disclosed in the acknowledgements section of any article submitted to an IEEE publication. The AI system used shall be identified, and specific sections of the article that use AI-generated content shall be identified and accompanied by a brief explanation regarding the level at which the AI system was used to generate the content.”

“The use of AI systems for editing and grammar enhancement is common practice and, as such, is generally outside the intent of the above policy. In this case, disclosure as noted above is recommended.”

The format of your paper must strictly adhere to the IEEEtran Proceedings Format. LaTeX users: please use the LaTeX class file IEEEtran v1.8 and the following configuration (without option ‘compsoc’ or ‘compsocconf’): \documentclass[conference]{IEEEtran}

Word users: please use this Word template. See the official IEEE Templates page for more information.

Please make sure that your submission:

• does not exceed the respective page limit specified in the track call
• is in PDF format,
• is in letter page size,
• does not have page numbers,
• has all fonts embedded in the PDF file,
• uses only scalable font types (like Type 1, TrueType) — bit-mapped font types (like Type 3) are not acceptable,
• has all figures embedded in vector graphics (if not possible, use a high-resolution bitmap format of at least 300 dpi; do not use JPG, but a lossless format like PNG or GIF),
• has all text in figures and tables large enough and readable when printed,
• has a caption for every figure or table,
• has the title and all headings properly capitalized
• has no orphans and widows (cf. Section Help), and
• does not use footnote references in the abstract.

Papers must be submitted electronically in PDF format via the RE’26 EasyChair system. Select the RE’26 Research Track for your submission.

To guide the reviewing process, all authors who intend to submit a paper must first submit the title and abstract. Abstracts should describe explicit coverage of context, objectives, methods, and results and conclusions, and should not exceed 200 words.

Papers must not exceed 10 pages for the main body and up to 2 additional pages for the references. Submissions must be written in English and formatted according to the IEEE formatting instructions. Submissions must be double-blinded in conformance with the instructions below.

Please note: Papers that exceed the length specification, are not formatted correctly, or are not properly double-blinded will be desk-rejected without review. Only full paper submissions will be peer-reviewed. Abstract-only submissions will be discarded without further notice after the submission deadline. Accepted papers may require editing for clarity before publication and presentation. They will appear in the IEEE Digital Library.

Instructions for the Double-Blind Review Process

The RE’26 Research track will use a double-blind reviewing process. The goal of double-blind reviewing is to ensure that the reviewers can read and review your paper without having to know who any of the authors are, and hence avoid related bias. Of course, authors are allowed and encouraged to submit papers that build on their previously published work.

To prepare your submission for double-blind reviewing, please follow the instructions given below.

1. Omit all names and affiliations of authors from the title page, but keep sufficient space to re-introduce them in the final version should the paper be accepted.
2. Do not include any acknowledgements that might disclose your identity. Leave space in your submission to add such acknowledgements when the paper has been accepted.
3. Refer to your own work in the third person, as you would normally do with the work of others. You should not change the names of your own tools, approaches, or systems, since this would clearly compromise the review process; it would also violate the constraint that “no change is made to any technical details of the work”. Instead, refer to the authorship or provenance of tools, approaches, or systems in the third person, so that it is credible that another author could have written your paper. In particular, never blind references.
4. When providing supplementary material (e.g., tools, data repositories, source code, study protocols), do this via a website that does not disclose your identity. Please refer to the Open Science Policy in the Call for Papers with guidelines on how to anonymize such content.
5. Adhere to instruction 3 when citing previously published own work.
6. Remove identification metadata from the PDF file before submission (in Adobe Acrobat Reader, you can check its presence with File Properties, or Ctrl-D).

Important Policy Announcements

Papers submitted to RE’26 must be original. They will be reviewed under the assumption that they do not contain plagiarized material and have not been published or submitted for review elsewhere while under consideration for RE’26.

RE’26 follows the IEEE policies for cases of double submission and plagiarism

Empirical Studies and Sharing of Data

• I am doing research with industry. What if I cannot share data from my research? We absolutely welcome research with industry, as it often conveys important lessons about requirements engineering in practice – and we perfectly understand that industry data may be subject to confidentiality issues or legal requirements. If you cannot share data, please state the reason in the submission form and the paper; a typical wording would be “The raw data obtained in this study cannot be shared because of confidentiality agreements”. Having said that, even sharing a subset of your data (for instance, the data used for figures and tables in the paper, an anonymized subset, or one that aggregates over the entire dataset), analysis procedures, or scripts, would be useful.

• I am doing user studies. What if I cannot share data from my empirical study? We absolutely welcome user studies! However, we also perfectly understand that sharing raw data can be subject to constraints such as privacy issues. If you cannot share data, please state the reason in the submission form and the paper; a typical wording would be “The raw data obtained in this study cannot be shared because of privacy issues”. Having said that, even sharing a subset of your data (for instance, the data used for figures and tables in the paper, an anonymized subset, or one that aggregates over the entire dataset), analysis procedures, or scripts, would be useful.

• I am doing qualitative research. What information should I include to help reviewers assess my research results and the readers use my results? Best practices for addressing the reliability and credibility of qualitative research suggest providing detailed arguments and rationale for qualitative approaches, procedures, and analyses. Therefore, authors are advised to provide as much transparency as possible into these details of their study. For example, clearly explain details and decisions such as 1) context of study, 2) the participant-selection process and the theoretical basis for selecting those participants, 3) collection of data or evidence from participants, and 4) data analysis methods, e.g., justify their choice theoretically and how they relate to the original research questions, and make explicit how the themes and concepts were identified from the data. Further, provide sufficient detail to bridge the gap between the interpretation of findings presented and the collected evidence by, for example, numbering quotations and labeling sources, and providing the codebook with associated examples for each code and category. Similar to replicability in quantitative research, transparency aims to ensure a study’s methods are available for inspection and interpretation. However, replicability or repeatability is not the goal, as qualitative methods are inherently interpretive and emphasize context. As a consequence, reporting qualitative research might require more space in the paper; authors should consider providing enough evidence for their claims while being mindful with the use of space. Finally, when qualitative data is counted and used for quantitative methods, authors should report the technique and results in assessing rigour in data analysis procedures, such as inter-reliability tests or triangulation over different data sources or methods, and justify how they achieved rigour if no such methods were used.

• I can make my data set / my tool available, but it may reveal my identity. What should I do? See this question under “double-anonymous submissions”, below.

Double-Blind Submissions

• I previously published an earlier version of this work in a venue that doesn’t have double-anonymous. What should I do about acknowledging that previous work? If the work you are submitting for review has previously been published in a peer-reviewed venue or in a non-peer-reviewed venue (e.g., arXiv.org, or a departmental technical report), then it should be cited but in the third person so that it is not revealed that the cited work and the submitted paper share one or more authors.

• Our submission makes use of work from a PhD or master’s thesis, dissertation, or report which has been published. Citing the dissertation might compromise anonymity. What should we do? It is perfectly OK to publish work arising from a PhD or master’s degree, and there is no need to cite it in a submission to the RE Research Track because prior dissertation publication does not compromise novelty. In the final post-review, camera-ready version of the paper, please do cite the dissertation to acknowledge its contribution, but in any submission to the RE Research Track, please refrain from citing the dissertation to increase anonymity. You need not worry whether or not the dissertation has appeared. Your job is to ensure that your submission is readable and reviewable, without the reviewers needing to know the identities of the submission’s authors. You do not need to make it impossible for the reviewers to discover the authors’ identities. The referees will be trying hard not to discover the authors’ identity, so they will likely not be searching the web to check whether there is a dissertation related to this work.

• What if we want to cite some unpublished work of our own (as motivation for example)? If the unpublished paper is an earlier version of the paper you want to submit to the RE Research Track and is currently under review, then you have to wait until your earlier version is through its review process before you can build on it with further submissions (this would be considered double-submission and violates plagiarism policies and procedures). Otherwise, if the unpublished work is not an earlier version of the proposed submission, then you should simply make it available on a website, for example, and cite it in the third person to preserve anonymity, as you are doing with other work.

• Can I disseminate a non-anonymized version of my submitted work by discussing it with colleagues, giving talks, publishing it at ArXiV, etc.? You can discuss and present your work that is under submission at small meetings (e.g., job talks, visits to research labs, a Dagstuhl or Shonan meeting), but you should avoid broadly advertising it in a way that reaches the reviewers even if they are not searching for it. Therefore, the title of your submission must be different from preprints on ArXiV or similar sites. During review, you must not publicly use the submission title. Under these conditions, you are allowed to put your submission on your home page and present your work at small professional meetings.

• What if we want to make available a tool, a data set, or some other resource, but it may reveal my identity? Please refer to the Open Science Policy in the Call for Papers with guidelines on how to anonymize such content. If that is impossible, place a warning next to the link that this may reveal your identity.