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SBSE Track at GECCO 2017 : SBSE Track at Genetic and Evolutionary Computation Computation Conference


When Jul 15, 2017 - Jul 19, 2017
Where Berlin, Germany
Abstract Registration Due Jan 30, 2017
Submission Deadline Feb 6, 2017
Categories    evolutionary computation   software engineering

Call For Papers

Search-Based Software Engineering (SBSE) Track @ Genetic and Evolutionary Computation Conference (GECCO) 2017

Dear Colleague,

We invite you to contribute high quality papers to the Search-Based Software Engineering (SBSE) track of the Genetic and Evolutionary Computation Conference (GECCO 2017). After a few years as part of a combined track, SBSE is once again the subject of its own dedicated track at GECCO and thus we welcome your support for the track in this new form. Note also this year GECCO invites shorter “poster-only” papers in addition to full-length technical papers; see: for details.


Paper Submission: 6 February 2017 (non-extensible; abstracts by 30 January)
Conference: 15-19 July 2017, Berlin, Germany
Track Details:
Paper Submission Details:


Search-Based Software Engineering (SBSE) is the application of search algorithms to the solution of software engineering tasks. Evolutionary computation is a foundation of SBSE, and since 2002 the SBSE track at GECCO has provided an opportunity to present SBSE research to the evolutionary computation community, and for SBSE to be informed by advances in evolutionary computation.

We invite papers that address problems in the software engineering domain through the use of heuristic search techniques. We particularly encourage papers demonstrating novel search strategies or the application of SBSE techniques to new problems in software engineering. Papers may also address the use of methods and techniques for improving the applicability and efficacy of search-based techniques when applied to software engineering problems. While empirical results are important, papers that do not contain results - but instead present new approaches, concepts, or theory - are also very welcome.


As an indication of the wide scope of the field, search techniques include, but are not limited to:
Ant Colony Optimization, Automatic Algorithm configuration and Parameter Tuning, Estimation of Distribution Algorithms,
Evolutionary Computation, Hybrid and Memetic Algorithms, Hyper-heuristics, Iterated Local Search,
Particle Swarm Optimization, Simulated Annealing, Tabu Search, Variable Neighbourhood Search.

The software engineering tasks to which they are applied are drawn from throughout the engineering lifecycle and include, but are not limited to:
Automated Software Design and Hyper-Heuristics
Automatic Algorithm Selection and Configuration
Configuring Cloud-Based Architectures
Creating Recommendation Systems to Support Software Development
Developing Dynamic Service-Oriented Systems
Enabling Self-Configuring/Self-Healing/Self-Optimizing Systems
Network Design and Monitoring
Optimizing Functional and Non-Functional Software Properties (Genetic Improvement)
Predictive Modelling for Software Engineering Tasks
Project Management and Organization
Regression Test Optimization
Requirements Engineering
Software Maintenance, Program Repair, Refactoring and Transformation
Software Security
System and Software Integration
Test Data Generation


Each paper submitted to the track will be rigorously evaluated in a double-blind review process. Paper evaluation at GECCO occurs on a per-track basis, ensuring high interest and expertise of the reviewers. Review criteria include significance of the work, technical soundness, novelty, clarity, writing quality, and sufficiency of information to permit replication, if applicable. All accepted papers will be published in the ACM Digital Library.


Federica Sarro (, Senior Research Associate, CREST, University College London, United Kingdom
Simon Poulding (, Assistant Professor, SERL, Blekinge Institute of Technology, Sweden

GECCO is sponsored by the Association for Computing Machinery Special Interest Group for Genetic and Evolutionary Computation (ACM SIGEVO).

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