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 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.

Please see ESEIW website for venue, registration, and visa information

Topics of Interest

Application oriented:

  • 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.

Theory oriented:

  • 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:

  • 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:

  • 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.


Important Dates

  • Abstracts due: July 16, 2018
  • Submissions due: July 20, 2018
  • Author notification: August 21, 2018
  • Conference Date: October 10, 2018


Journal Special Issue

  • Following the conference, the authors of the best papers will be invited for consideration in a special issue of the Empirical Software Engineering journal by Springer.



  • TBA

Kinds of Papers

We invite theory and empirical studies on the topics of interest (e.g. case studies, meta-analysis, replications, experiments, simulations, surveys etc.), as well as industrial experience reports detailing the application of predictive modelling and data analytics in industrial settings. Both positive and negative results are welcome, though negative results should still be based on rigorous research and provide details on lessons learned. It is encouraged, but not mandatory, that conference attendees contribute the data used in their analysis on-line. Submissions can be of the following kinds:

  • Full papers (oral presentation): papers with novel and complete results.
  • Short papers (oral presentation): papers to disseminate on-going work and preliminary results for early feedback, or vision papers about the future of predictive modelling and data analytics in software engineering
Note about GitHub research: 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”. 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).



PROMISE 2018 submissions must meet the following criteria:
  • be original work, not published or under review elsewhere while being considered.
  • conform to the ACM SIG proceedings template
  • not exceed 10 (4) pages for full (short) papers including references.
  • follow a structured abstract with the headings: Background, Aims, Method, Results, and Conclusions.
  • written in English;
  • Papers should be submitted via EasyChair (please choose the paper category appropriately):
Submissions will be peer reviewed by at least three experts from the international program committee. 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.

Programme Committee

  • Gabriele Bavota, University of Lugano
  • Ricardo Britto, Blekinge Institute of Technology
  • Massimiliano (Max) Di Penta, University of Sannio
  • Carmine Gravino, University of Salerno
  • Rachel Harrison, Oxford Brooks University
  • Hoa Khan, University of Wollongong
  • Foutse Khomh, Polytechnique Montreal
  • Ekrem Kocaguneli, MIcrosoft
  • Gernot Liebchen, Bournemouth University
  • Lech Madeyski, Wroclaw University of Science and Technology
  • Tim Menzies, North Carolina State University
  • Leandro Minku, University of Leicester
  • Jaechang Nam, Handong Global University
  • Daniel Rodriguez, University of Alcalá
  • Martin Shepperd, Brunel University London
  • Chakkrit Tantithamthavorn, University of Adelaide
  • Hironori Washizaki, Waseda University
  • Xin Xia, Monash University
  • Yuming Zhou, Nanjing University

Steering Committee

General Chair

PC Co-Chairs

Publication Chair

Publicity and Social Media Chair

Local Organization Chair