[Opt-Net] IEEE Transactions on Evolutionary Computation : Special Issue on Search-Based Software Engineering

[Marouane Kessentini]

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

IEEE Transactions on Evolutionary Computation :
Special Issue on Search-Based Software Engineering

GUEST EDITORS:
• Marouane Kessentini, Department of Computer and Information Science,
University of Michigan, USA marouane at umich.edu
• Kalyanmoy Deb, Department of Electrical and Computer Engineering,
Michigan State University, USA   kdeb at egr.msu.edu
• Federica Sarro, Department of Computer Science, University College
London, UK f.sarro at ucl.ac.uk

I. AIM AND SCOPE
Software engineering involves a task for searching a solution that balances
a number of constraints to achieve optimal or near-optimal solutions [5].
The current procedures require time consuming human activities. The methods
do not usually scale to solve real-world software engineering problems. A
growing trend has begun in recent years to move software engineering
problems from human-based search to more machine-based search. As a result,
human effort is moving up the abstraction chain to focus on guiding the
automated search, rather than performing the search itself. This emerging
software engineering paradigm is known as Search- Based Software
Engineering (SBSE). It uses search based optimization techniques, mainly
those from the evolutionary computation literature to automate the search
for optimal or near-optimal solutions to software engineering problems.
While evolutionary computation has been successfully applied to the design
of engineering artefacts in civil, mechanical and electronic engineering,
the search process cannot directly optimize these materials; the search
ranges over a design space, guided by a simulation of a model of reality.
The search space and guidance are very different when we apply computation
search to software. SBSE find a new and potent possibility for search based
optimization: the Evolutionary Algorithms can directly optimize the
engineering material: the programs themselves [6].
The SBSE approach can and has been applied to many problems in software
engineering that span the spectrum of activities from requirements to
maintenance and reengineering [1][2][3][4][5]. Already, success has been
achieved in requirements, refactoring, project planning and management,
testing, maintenance and reverse engineering. However, several challenges
have to be addressed to mainly tackle the growing complexity of software
systems.

II. THEMES
In this special issue, we will invite papers that address problems in the
software engineering domain through the use of evolutionary computation
search techniques. We particularly encourage papers demonstrating novel
search strategies or the application of computational search techniques to
new problems in software engineering. Applications may be drawn from
throughout the software engineering lifecycle by investigating the
application of search based software engineering approaches for the
automation of all phases of the software development process, including the
analysis, design, implementation, testing, and maintenance of large
software systems. Specific topics can include the application of
evolutionary computation to the following areas:
• Component-based systems
• Data mining for software engineering
• Empirical software engineering
• Human-computer interaction
• Knowledge acquisition and management

• Maintenance and evolution
• Software testing, verification, and validation
• Product line development methods
• Refactoring and program understanding
• Requirements engineering and software development
• Software Analysis
• Software architecture and design

III. SUBMISSIONS
Manuscripts should be prepared according to the “Information for Authors”
section of the journal found at http://ieee-cis.org/pubs/tec/authors/ and
submissions should be done through the journal submission website:
http://mc.manuscriptcentral.com/tevc-ieee/, by selecting the Manuscript
Type of “SBSE Special Issue Papers” and clearly marking “SBSE Special Issue
Paper” as comments to the Editor-in-Chief. Submitted papers will be
reviewed by at least three different expert reviewers. Submission of a
manuscript implies that it is the authors’ original unpublished work and is
not being submitted for possible publication elsewhere.

IV. IMPORTANT DATES
Submission deadline: May 28, 2016
Author notification: September 15, 2016
Revision: November 15, 2016
Final version: December 15, 2016

REFERENCES
[1] Langdon, William B., and Mark Harman. "Optimising existing software
with genetic programming." IEEE Transactions on Evolutionary Computation,
19, no.1, (2015).
[2] Sahin, Dilan, Marouane Kessentini, Slim Bechikh, and Kalyanmoy Deb.
"Code-smell detection as a bilevel problem." ACM Transactions on Software
Engineering and Methodology (TOSEM) 24, no. 1 (2014): 6.
[3] Harman, Mark, S. Afshin Mansouri, and Yuanyuan Zhang. "Search-based
software engineering: Trends, techniques and applications." ACM Computing
Surveys (CSUR) 45, no. 1 (2012): 11.
[4] Mkaouer, Wiem, Marouane Kessentini, Shaout, Slim Bechikh, Kalyanmoy
Deb, and Ali Ouni. "Many-Objective Software Remodularization Using
NSGA-III." ACM Transactions on Software Engineering and Methodology (TOSEM)
24, no. 3 (2015): 17.
[5] Deb, Kalyanmoy, and Himanshu Jain. "An evolutionary many-objective
optimization algorithm using reference-point-based nondominated sorting
approach, part I: solving problems with box constraints." Evolutionary
Computation, IEEE Transactions on 18, no. 4 (2014): 577-601.
[6] Harman, Mark. “Why the Virtual Nature of Software Makes it Ideal for
Search Based Optimization”, 13th International Conference on Fundamental
Approaches to Software Engineering (FASE 2010), 1-12
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://listserv.zib.de/pipermail/opt-net/attachments/20160121/3ad01629/attachment.html>