[ecoop-info] CFP: The 14th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE'18)

[Mei Nagappan]

PROMISE 2018
The 14th International Conference on Predictive Models and Data
Analytics in Software Engineering (PROMISE'18) - in conjunction with
ESEM'18
Oct. 10, 2018. Oulu, Finland.

http://promisedata.org/2018
Twitter: @promise_conf
Facebook: https://www.facebook.com/promiseConf
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IMPORTANT DATES:

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

JOURNAL SPECIAL SECTION:

Following the conference, the authors of the best papers will be
invited for consideration in a special issue of the Empirical Software
Engineering journal:
http://www.springer.com/computer/swe/journal/10664/

——————PROMISE 2018: 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. 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.

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 datasets
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;

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.

SUBMISSIONS:

Submissions must conform to the ACM SIG proceedings templates
(https://www.acm.org/publications/proceedings-template), and within
10(4) pages for full(short) papers, including references. Papers
should be submitted via EasyChair:
http://www.easychair.org/conferences/?conf=promise2018. Submissions
should not be published or under review elsewhere while being
considered.

Accepted papers will be published in the ACM Digital Library within
its International Conference Proceedings Series and will be available
electronically via the ACM DL. Each accepted paper needs to have one
registration at the full conference rate and be presented in person at
the conference.


ORGANIZATION:

General Chair: Burak Turhan, Brunel University

PC Co-chairs: Ayse Tosun, Istanbul Technical University, Shane
McIntosh, McGill University

Proceedings Chair: David Bowes, University of Hertfordshire

Publicity and Social Media Chair: Meiyappan Nagappan, University of Waterloo

Local Organization Chair: Burak Turhan, Brunel University


Steering Committee:
David Bowes, University of Hertfordshire
Leandro Minku, Univ. of Leicester
Andriy Miranskyy, Ryerson University
Massimiliano Di Penta, Univ. of Sannio
Emad Shihab, Concordia University
Burak Turhan, Brunel University
Hongyu Zhang, University of Newcastle