[ecoop-info] CFP: PROMISE 2016

Raise Software raise.workshop at gmail.com
Sat Apr 16 10:22:45 CEST 2016


PROMISE’16: The 12th International Conference on Predictive Models and Data
Analytics in Software Engineering
September 7th, 2016 - Ciudad Real, Spain
(Co-located with ESEM 2016)


http://promisedata.org/2016/
https://twitter.com/promise_conf
https://www.facebook.com/promiseConf


Important dates


Abstract submission deadline: June 10th, 2016
Paper submission deadline: June 17th, 2016
Notification date: July 20th, 2016
Camera-ready copy: July 27th, 2016
Conference date: September 7th, 2016


Keynote


Keynote by Prof. Natalia Juristo from the Computing School at the Technical
University of Madrid (UPM)


Journal Special Section

Following the conference, the authors of two of the best  manuscripts will
be invited to extend their papers into full journal papers, for a Special
Section of the Information and Software Technology.




CALL FOR PAPERS


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. Such models and analyses could be targeted at:
planning, design, implementation, testing, maintenance, quality assurance,
evaluation, process improvement, management, decision making, and risk
assessment in software and systems development. PROMISE is distinguished
from similar forums with its public data repository and focus on
methodological details, providing a unique interdisciplinary venue for
software engineering and data mining communities, and seeking for
verifiable and repeatable experiments that are useful in practice.


Topics of Interest


Topics of interest include, but are not limited to:


Application oriented:
* predicting for 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:
* contributions to the repository;
* data quality, sharing, and privacy;
* ethical issues related to data collection;
* metrics;
* tools and frameworks to support researchers and practitioners to collect
data and construct models to share/repeat experiments and results.


*** Poster Competition ***

We will also have a poster competition. The poster is not mandatory, but is
strongly encouraged. Posters will be judged by a panel during the
conference.


Kinds of Papers


We invite all kinds of 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.


Following the tradition, PROMISE 2016 will give the highest priority to
studies based on publicly available datasets. It is therefore encouraged,
but not mandatory, that conference attendees contribute the data used in
their analysis to the on-line PROMISE data repository (
http://openscience.us/). We also encourage authors to submit their source
codes to the repository.


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.
* Short paper (poster competition): papers to disseminate on-going work and
preliminary results for early feedback.


Submissions


PROMISE 2016 submissions must meet the following criteria:
* be original work, not published or under review elsewhere;
* conform to the ACM SIG proceedings templates from http://goo.gl/wE1k
* not exceed 10 (4) pages for full (short) papers including references;
* papers should be submitted via EasyChair (please choose the paper
category appropriately): https://easychair.org/conferences/?conf=promise2016



Accepted papers will be published in the ACM digital library.


Organisation


Steering Committee:


Ayse Bener, Ryerson University, Canada
Leandro Minku, University of Leicester, UK
Andriy Miranskyy, Ryerson University, Canada
Massimiliano Di Penta, University of Sannio, Italy
Burak Turhan, University of Oulu, Finland
Hongyu Zhang, Microsoft Research, China


General Chair:
Ayse Bener, Ryerson University, Canada


PC Co-chairs:
Andriy Miranskyy, Ryerson University, Canada and Hongyu Zhang, Microsoft
Research, China


Publicity Chair:
Leandro Minku, University of Leicester, UK


Publication Chair:
Massimiliano Di Penta, University of Sannio, Italy


Local Organization Co-Chairs:
Burak Turhan, University of Oulu, Finland
Daniel Rodriguez, University of Alcalá, Spain


Program Committee:


Lefteris Angelis, Aristotle University of Thessaloniki, Greece
Gabriele Bavota, Free University of Bozen-Bolzano, Italy
Bora Caglayan, Ryerson University, Canada
Tracy Hall, Brunel University, UK
Rachel Harrison, Oxford Brookes University, UK
Jacky Keung, City University of Hong Kong, China
Foutse Khomh, DGIGL École Polytechnique de Montréal, Canada
Ekrem Kocaguneli, Microsoft, USA
Chris Lokan, University of New South Wales, Australia
Lech Madeyski, Wroclaw University of Technology, Poland
Tim Menzies, North Carolina State University, USA
Rudolf Ramler, Software Competence Center Hagenberg, Austria
Daniel Rodriguez, The University of Alcalá, Spain
Federica Sarro, University College London, UK
Martin Shepperd, Brunel University, UK
Ayse Tosun Misirli, Istanbul Technical University, Turkey
Stefan Wagner, University of Stuttgart, Germany
Hironori Washizaki, Waseda University, Japan
Dietmar Winkler, Vienna University of Technology, Austria
Yang Ye, Stevens Institute of Technology, USA
Yuming Zhou, Nanjing University, China

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