posted by user: timmenzies || 2350 views || tracked by 8 users: [display]

ACTION15 2015 : Actionable Analytics for SE


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

* 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
* 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 agenda for maturing and enriching software
planning decision models.


All accepted papers will appear in the IEEE Digital Library.


Easychair submission site:

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:

Authors should use US letter style.

LaTeX users should use this their document class:

% The compsoc option is not to be used.



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

ADAH 2017   Advanced Data Analytics in Health
ACML 2017   The 9th Asian Conference on Machine Learning
ETHE Blearning 2017   Blended learning in higher education: research findings
WWW 2018   World Wide Web (The Web Conference)
UMUAI SI 2018   UMUAI SI on Multimodal Learning Analytics & Personalized Support Across Spaces
ICCBDC - ACM 2017   International Conference on Cloud and Big Data Computing (ICCBDC 2017)--Ei Compendex and Scopus
DCTA 2017   Data Analytics: Concepts, Techniques and Applications
IEEE Big Data 2017   2017 IEEE International Conference on Big Data
SI Wiley SPE 2018   Call for Papers for Special Issue on Integration of Cloud, IoT and Big Data Analytics
ESEM 2017   Empirical Software Engineering and Measurement