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21st International Conference on Predictive Models and Data
Analytics in Software Engineering (PROMISE 2025)
https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fconf.researchr.org%2Fhome%2Fpromise-2025&data=05%7C02%7Ctimo.kehrer%40unibe.ch%7C4731d778532f456b1cca08dd3387190a%7Cd400387a212f43eaac7f77aa12d7977e%7C1%7C0%7C638723505581138696%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C40000%7C%7C%7C&sdata=6ON7OAMZobQv%2FvWZfPtURC2Yvuxo3cwn1vVFjK7b8Ds%3D&reserved=0
June, 2025, Trondheim, Norway
Co-located with the International Conference on the Foundations of
Software Engineering (FSE 2025)
Submit your papers by February 25th, 2025
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The International Conference on Predictive Models and Data
Analytics in Software Engineering (PROMISE) is an annual forum for
researchers and practitioners to present, discuss and exchange
ideas, results, expertise and experiences in construction and/or
application of predictive models, artificial intelligence, and
data analytics in software engineering. PROMISE encourages
researchers to publicly share their data in order to provide
interdisciplinary research between the software engineering and
data mining communities, and seek for verifiable and repeatable
experiments that are useful in practice.
=== Important Dates ===
- Abstract submission: Feb 18th, 2025 AoE
- Paper submission: Feb 25th, 2025 AoE
- Author notification: Mar 24th, 2025 AoE
- Camera-ready: Apr 24th, 2025 AoE
- Conference Date: June, 2025
=== Types of Submissions ===
Technical papers (10 pages)
* PROMISE accepts a wide range of papers where AI tools have been
applied to SE such as predictive modeling and other AI methods.
Both positive and negative results are welcome, though negative
results should still be based on rigorous research and provide
details on lessons learned.
Industrial papers (2-4 pages)
* Results, challenges, lessons learned from industrial
applications of software analytics.
New idea papers (2-4 pages)
* Novel insights or ideas that may yet to be fully tested.
Journal First
* Selected papers will be invited for journal first presentations
at PROMISE. Details to follow.
=== Topics of Interest ===
PROMISE papers can explore any of the following topics (or more).
Application-oriented papers:
* prediction of cost, effort, quality, defects, business value;
* quantification and prediction of other intermediate or final
properties of interest in software development regarding people,
process or product aspects;
* using predictive models and data analytics in different
settings, e.g. lean/agile, waterfall, distributed, community-based
software development;
* dealing with changing environments in software engineering
tasks;
* dealing with multiple-objectives in software engineering tasks;
* using predictive models and software data analytics in policy
and decision-making.
Ethically-aligned papers:
* Can we apply and adjust our AI-for-SE tools (including
predictive models) to handle ethical non-functional requirements
such as inclusiveness, transparency, oversight and accountability,
privacy, security, reliability, safety, diversity and fairness?
Theory-oriented papers:
* model construction, evaluation, sharing and reusability;
* interdisciplinary and novel approaches to predictive modelling
and data analytics that contribute to the theoretical body of
knowledge in software engineering;
* verifying/refuting/challenging previous theory and results;
* combinations of predictive models and search-based software
engineering;
* the effectiveness of human experts vs. automated models in
predictions.
Data-oriented papers:
* data quality, sharing, and privacy;
* curated data sets made available for the community to use;
ethical issues related to data collection and sharing;
* metrics;
* tools and frameworks to support researchers and practitioners to
collect data and construct models to share/repeat experiments and
results.
Validity-oriented papers:
* replication and repeatability of previous work using predictive
modelling and data analytics in software engineering;
* assessment of measurement metrics for reporting the performance
of predictive models;
* evaluation of predictive models with industrial collaborators.
=== Submissions ===
PROMISE 2025 submissions must meet the following criteria:
* be original work, not published or under review elsewhere while
being considered;
*
conform to the submission format requirements of the FSE 2025
Companion
proceedings;
<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fconf.researchr.org%2Ftrack%2Ffse-2025%2Ffse-2025-how-to-submit%23submission-format&data=05%7C02%7Ctimo.kehrer%40unibe.ch%7C4731d778532f456b1cca08dd3387190a%7Cd400387a212f43eaac7f77aa12d7977e%7C1%7C0%7C638723505581176711%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C40000%7C%7C%7C&sdata=v3AwcA%2BTlpGGI%2B3K2p0vkEUeFxXeCkE%2FGJU%2FB%2FrP3so%3D&reserved=0>
* not exceed 10 (4) pages for technical (industrial, new-ideas)
papers including references;
* be written in English;
* be prepared for double blind review
* Exception: for data-oriented papers, authors may elect not to
use double blind by placing a footnote on page 1 saying “Offered
for single-blind review”.
*
be submitted via HotPRC and the submission link will be posted
shortly.
* on submission, please choose the paper category appropriately,
i.e., technical (main track, 10 pages max); industrial (4 pages
max); and new idea papers (4 pages max).
To satisfy the double blind requirement submissions must meet the
following criteria:
* no author names and affiliations in the body and metadata of the
submitted paper;
* self-citations are written in the third person;
* no references to the authors personal, lab, or university
website;
* no references to personal accounts on GitHub, bitbucket, Google
Drive, etc.
=== Publication and Attendance ===
Accepted papers will be published in the ACM Digital Library
within its International Conference Proceedings Series and will be
available electronically via ACM Digital Library.
Each accepted paper needs to have one registration at the full
conference rate and be presented in person at the conference.
=== Evaluation ===
Submissions will be peer reviewed by at least three experts from
the international program committee. Submissions will be evaluated
on the basis of their originality, importance of contribution,
soundness, evaluation, quality, and consistency of presentation,
and appropriate comparison to related work.
=== Green Open Access ===
Similar to other leading SE conferences, PROMISE supports and
encourages Green Open Access, i.e., self-archiving. Authors can
archive their papers on their personal home page, an institutional
repository of their employer, or at an e-print server such as
arXiv (preferred). Also, given that PROMISE papers heavily rely on
software data, we would like to draw authors that leverage data
scraped from GitHub of GitHub’s Terms of Service, which require
that “publications resulting from that research are open access”.
We also strongly encourage authors to submit their tools and data
to Zenodo, which adheres to FAIR (findable, accessible,
interoperable and re-usable) principles and provides DOI
versioning.
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