CHI-ANNOUNCEMENTS Archives

ACM SIGCHI General Interest Announcements (Mailing List)

CHI-ANNOUNCEMENTS@LISTSERV.ACM.ORG

Options: Use Forum View

Use Monospaced Font
Show Text Part by Default
Condense Mail Headers

Message: [<< First] [< Prev] [Next >] [Last >>]
Topic: [<< First] [< Prev] [Next >] [Last >>]
Author: [<< First] [< Prev] [Next >] [Last >>]

Print Reply
Content-Type:
text/plain; charset="iso-8859-1"
Date:
Wed, 6 Feb 2013 12:52:48 +0800
Reply-To:
Ye Yang/ISCAS <[log in to unmask]>
Subject:
MIME-Version:
1.0
Message-ID:
Content-Transfer-Encoding:
quoted-printable
Sender:
"ACM SIGCHI General Interest Announcements (Mailing List)" <[log in to unmask]>
From:
Ye Yang/ISCAS <[log in to unmask]>
Parts/Attachments:
text/plain (254 lines)
========================== First Call for Papers ==========================

PROMISE'13

The 9th International Conference on Predictive Models in Software
Engineering

Oct 9, 2013, Baltimore, Maryland, USA

 <http://promisedata.org/2013/> http://promisedata.org/2013/

(Co-located with ESEM 2013)

===================================================================

 

IMPORTANT DATES:

Abstracts due: April 05, 2013 

Submissions due: April 12, 2013

Author notification: June 10, 2013 

Camera-ready copy due: June 28, 2013 

 

KEYNOTE SPEAKER:

Tom Zimmermann, Microsoft Research

 

PROMISE conference is an annual forum for researchers and practitioners to
present, discuss and exchange ideas, results, expertise and experiences in
construction and/or application of prediction models in software
engineering. Such models 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 machine learning communities, and seeking
for verifiable and repeatable prediction models that are useful in practice.


 

SPECIAL THEME: 

The special theme of PROMISE’13 is predictions across projects, contexts and
organizations, where the predictions employ approaches (e.g. transfer
learning, instance selection, data filtering) with an impact that is useful
in practice, in order to solve the problem of learning under concept drift
(across time and space). 

 

TOPICS OF INTEREST:

* (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 in policy and decision making;
using predictive models in different settings, e.g. lean/agile, waterfall,
distributed, community-based software development.

 

* (Theory oriented): Interdisciplinary and novel approaches to predictive
modeling that contribute to the theoretical body of knowledge in software
engineering; verifying/refuting/challenging previous theory and results; the
effectiveness of human experts vs. automated models in predictions.

 

* (Data and model oriented): Data quality, sharing, and privacy; ethical
issues related to data collection; metrics; contributions to the repository;
model construction, evaluation, sharing and reusability; tools and
frameworks to support researchers and practitioners to collect data and
construct models to share/repeat experiments and results. 

 

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
prediction technologies and their effectiveness 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'13 will give the highest priority to
empirical studies based on publicly available datasets. It is therefore
encouraged, but it is not mandatory, that conference attendees contribute
the data used in their analysis to the on-line PROMISE data repository. 

 

We solicit both full and short papers. Short papers are intended to
disseminate new ideas, on-going work and preliminary results for early
feedback, and do not necessarily require complete results as in full papers.
The deadline for short papers is the same as full papers.

 

SUBMISSIONS:

* Submissions must be original work, not published or under review
elsewhere.

* Submissions must conform to the ACM SIG proceedings templates from
http://goo.gl/wE1k.

* Submissions must not exceed 10 (4) pages for full (short) papers including
references.

* Papers should be submitted via Easychair (please choose either “full” or
“short” papers): http://www.easychair.org/conferences/?conf=promise2013.

* Accepted papers will be published in the ACM digital library. 

 

SPECIAL ISSUE:

The venue for the special issue is TBA. Previous PROMISE special issues have
appeared in IEEE Software, Empirical Software Engineering Journal,
Information and Software Technology Journal, and Automated Software
Engineering Journal.

 

 

ORGANIZATION:

Steering Committee:

 

Stefan Wagner, University of Stuttgart (General Chair)

Burak Turhan, University of Oulu (PC Chair)

Ye Yang, Chinese Academy of Science (Publicity Chair)

Ayse Bener, Ryerson University (Local Org. Chair)

 

Programme Committee:

 

Lefteris Angelis, Aristotle University of Thessaloniki

Ayse Bener, Ryerson University

Christian Bird, Microsoft Research

David Bowes, University of Hertfordshire

Daniela Da Cruz, University of Minho

Massimiliano Di Penta, RCOST - University of Sannio

Harald Gall, University of Zurich

Vahid Garousi, University of Calgary

Tracy Hall, Brunel University

Mark Harman, University College London

Rachel Harrison, University of Oxford

Jacky Keung, The Hong Kong Polytechnic University

Sunghun Kim, The Univ. of Hong Kong Science and Tech.

Ekrem Kocaguneli, West Virginia University

Lech Madeyski, Wroclaw University of Technology

Kenichi Matsumoto, Nara Inst. of Science and Tech.

Emilia Mendes, Blekinge Institute of Technology

Tim Menzies, West Virginia University

Leandro Minku, The University of Birmingham

Thomas Ostrand, AT&T Labs - Research

Daryl Posnett, UC Davis

Rudolf Ramler, Software Competence Center Hagenberg GmbH

Daniel Rodriguez, The University of Alcalá

Guenther Ruhe, University of Calgary

Federica Sarro, University College London

Carolyn Seaman, UMBC

Martin Shepperd, Brunel University

Qinbao Song, Xi'an Jiaotong University

Ayse Tosun Misirli, University of Oulu

Burak Turhan, University of Oulu

Stefan Wagner, University of Stuttgart

Dietmar Winkler, Vienna University of Technology

Ye Yang, Chinese Academy of Sciences

Hongyu Zhang, Tsinghua University

Yuming Zhou, Nanjing University

 

 

 

 

 


    ---------------------------------------------------------------
    For news of CHI books, courses & software, join CHI-RESOURCES
     mailto: [log in to unmask]

    To unsubscribe from CHI-ANNOUNCEMENTS send an email to
     mailto:[log in to unmask]

    For further details of CHI lists see http://listserv.acm.org
    ---------------------------------------------------------------

ATOM RSS1 RSS2