posted by user: timmenzies || 2726 views || tracked by 8 users: [display]

ACTION15 2015 : Actionable Analytics for SE

FacebookTwitterLinkedInGoogle

Link: http://action15.github.io/
 
When Nov 9, 2015 - Nov 9, 2015
Where Lincoln, Nebraska
Submission Deadline Jul 3, 2015
Notification Due Jul 24, 2015
Final Version Due Aug 31, 2015
Categories    computer science   software engineering   data mining   empirical
 

Call For Papers

ACTION15: Actionable Analytics for SE

An ASE'15 workshop
Lincoln, Nebraska, USA
Nov 9-13

http://action15.github.io
@actionable15

* Submission: July 3
* Notification: July 24
* Camera ready: Aug 31

-----------------------------------------------------

A repeated complaint in software analytics is that
industrial practitioners find it hard to apply the
results generated from data science. This is a
pressing issue: actionable analytics are required to
enable time- ensitive, environmental-aware decision
making. How can we bridge the gap between the
predictions we can generate to actions that users
can apply?

The workshop goal is to:

* Exchange research work on exploring new ideas,
metrics, and algorithms in software prediction;
* Discuss emergent challenges in software
prediction;
* Propose and ideally converge on a research road
map for the next 5-10 year.

Accordingly, we ask for papers on related topics
that include (but are not limited to) the following:

* Experiences and lessons learned on the strengths
and limitations of current software predictive
models; (i.e. how reliable are existing methods?)
* Challenges and barriers to adopt current models
and methodologies in the context of new software
technologies, such as crowdsourcing, architecture
migration, cloud service composition, etc.
* Roles of automation in improving predictive power
in software estimation.
* New metrics and models to better measure, search
and recommend the underlying causal relationships
of cost, schedule, and quality, etc.
* Trends and needs of emergent software planning
practices and impact on software estimation
research;
* Research agenda for maturing and enriching software
planning decision models.

Publication
===========

All accepted papers will appear in the IEEE Digital Library.

Submission
==========

Easychair submission site:
https://easychair.org/conferences/?conf=action15

Full papers: max 10 pages (+2 pages refs).
Vision statements: max 4 pages (including refs)

All submissions must come in PDF format and
conform to the [6]these guidelines: http://goo.gl/XxBwt

Authors should use US letter style.

LaTeX users should use this their document class:

\documentclass[conference]{IEEEtran}
% The compsoc option is not to be used.

Organization
============

Co-chairs:

Tim Menzies :: NcState, USA
Ye Yang :: Stevens Institute, USA

Program committee:

Hoa Khanh Dam :: U. Wollongong, Aust.
Gregory Gay :: U. Sth Carolina, USA
Ho In :: Korea, U., Korea
Jacky Keung :: HK Poly U, HK
Sung Kim :: HK Poly U, HK
Gunes Koru :: UMBC, USA
Kenichi Matsumoto :: NAIST, Japan
Ray Madachy :: NPS, USA
Leandro Minku :: U. Birmingham,UK
Guenther Ruhe :: U.Calgary, Canada
Martin Shepperd :: Brunel U. UK
Ricardo Valerdi :: U.Arizona, USA
Liming Zhu :: NICTA, Aust.

Related Resources

JLA 2019   Journal of Learning Analytics Special Section Call for Papers - Beyond Cognitive Ability
ICDMML 2019   【ACM ICPS EI SCOPUS】2019 International Conference on Data Mining and Machine Learning
SI SocInf+MAISoN 2018   Special Issue on Mining Social Influence and Actionable Insights from Social Networks
ICDM 2019   19th Industrial Conference on Data Mining ICDM 2019
SE 2019   7th International Conference on Software Engineering & Trends
MLDM 2019   15th International Conference on Machine Learning and Data Mining MLDM 2019
IJIBM 2019   Call For Papers - International Journal of Information, Business and Management
CCSEIT 2019   9th International Conference on Computer Science, Engineering and Information Technology
Data SI Semantic Analytics for Big Data 2018   Data Journal Special Issue on Semantics in the Deep: Semantic Analytics for Big Data
Special Issue A&DC IoT 2019   SENSORS (Q1) Special Issue: Algorithm and Distributed Computing for the Internet of Things