[alife] GI at CEC-2016 Genetic Improvement of Software submit by 15 January 2016

w langdon w.langdon at cs.ucl.ac.uk
Tue Nov 24 10:52:53 PST 2015


We are very pleased to announce that there will be a special session
at next year's CEC conference dedicated to Genetic Improvement of
Software and Search Based Software Engineering (SBSE).

CEC 2016 will be held in Vancouver (Canada) 25-29 July as part of the
IEEE World Congress on Computational Intelligence, WCCI 2016.
Although the Congress on Evolutionary Computation has been run
every year since 1999, this will be the first session dedicated to
genetic improvement (GI) of software.
Many more details can be found on the GI at CEC-2016 web page
http://www.cs.ucl.ac.uk/staff/W.Langdon/cec2016/
and the main http://www.wcci2016.org/ pages.

The submission deadline (8 pages double column) is 15 January 2016.
Submissions must in PDF and be made electronically via
http://ieee-cis.org/conferences/cec2016/upload.php


=== Aim and Scope ===



There has been a dramatic increase in work on Search-Based Software
Engineering (SBSE), the approach to software engineering in which
search-based optimisation algorithms are used to solve software
engineering problems. Evolutionary Computation (genetic algorithms,
GAs, genetic programming, GP, ES, DE, GE, etc.) and other stochastic
techniques are often used (SA, tabu, MCTS). One of the brightest
areas is the use of stochastic search to automatically improve
existing human written code. Recent successes have included automatic
bug repair, porting, automatic parallelisation, and performance
improvements. With increasing interest in software transplanting,
growing and grafting new code, genetic improvement, loop perforation,
and constraint based program synthesis And also multi-objective Pareto
trade-offs between functional and non-functional properties, such as
speed, accuracy, solution quality, memory and improved efficiency.

SBSE is attractive because it offers a suite of adaptive automated and
semi-automated solutions in situations typified by large complex
problem spaces with multiple competing and conflicting
objectives. SBSE has been applied to a number of software engineering
activities, right across the life-cycle from requirements engineering,
project planning and cost estimation through testing, to automated
maintenance, service-oriented software engineering, compiler
optimisation and quality assessment.

With this special session, we are providing an opportunity to showcase
recent breakthroughs in this field.

We invite submissions on any aspect of SBSE, including, but not
limited to, genetic improvement, theoretical results and interesting
new applications. The suggested topics cover the entire range of
functional and non-functional properties:
* bandwidth minimisation
* latency minimisation
* fitness optimisation
* energy optimisation
* software specialisation
* memory optimisation
* software transplantation
* bug fixing
* multi-objective SE optimisation

Markus Wagner  markus.wagner at adelaide.edu.au
Bill Langdon   w.langdon at cs.ucl.ac.uk
Brad Alexander brad at cs.adelaide.edu.au


        Dr. W. B. Langdon,
        Department of Computer Science,
        University College London
        Gower Street, London WC1E 6BT, UK
        http://www.cs.ucl.ac.uk/staff/W.Langdon/

barracuda_0.7.107b     http://seqbarracuda.sourceforge.net/
Genetic Improvement    http://www.springer.com/?SGWID=0-102-2-1487059-preview
EuroGP 2016            http://www.evostar.org/2016/cfp_eurogp.php
GECCO 2016	       http://www.sigevo.org/gecco-2016/
GI at CEC 2016            http://www.cs.ucl.ac.uk/staff/W.Langdon/cec2016/
choose your background
http://web4.cs.ucl.ac.uk/staff/W.Langdon/colour_telephone/bgcolor.html
A Field Guide to Genetic Programming
                       http://www.gp-field-guide.org.uk/
GP EM                  http://www.springer.com/10710
GP Bibliography        http://www.cs.bham.ac.uk/~wbl/biblio/



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