Call for papers for the SBSE track @ GECCO
Search-Based Software Engineering (SBSE) is the application of search algorithms and strategies to the solution of software engineering problems. Evolutionary computation is a foundation of SBSE, and since 2002 the SBSE track at GECCO has provided the unique
opportunity to present SBSE research in the widest context of the evolutionary computation community. Last but not least, participating to the SBSE track and, more generally, to GECCO allow to be informed by advances in evolutionary computation, new cutting
edge meta-heuristic ideas, novel search strategies, approaches and findings.
We invite papers that address problems in the software engineering domain through the use of heuristic search techniques. We would also thus like to invite papers from the genetic improvement area where evolutionary computation has been used for the purpose
of software improvement.
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 strong empirical results - but instead present new sound approaches, concepts, or theory in the search-based software engineering area
- are also very welcome.
Submission Information
We encourage the submission of both full papers and poster-only papers describing negative results as well as industrial reports on the practical use of search-based approaches. Moreover poster-only papers presenting frameworks/tools for search-based software
engineering are also welcome.
Deadline: January 30, 2019 (abstracts), February 6 (full papers)
Paper format information: https://gecco-2019.sigevo.org/index.html/tiki-index.php?page=Call%20for%20Papers
Scope
As an indication of the wide scope of the field, search techniques include, but are not limited to:
- Ant Colony Optimisation
- Automatic Algorithm configuration and Parameter Tuning
- Estimation of Distribution Algorithms
- Evolutionary Computation
- Genetic Programming
- Hybrid and Memetic Algorithms
- Hyper-heuristics
- Iterated Local Search
- Particle Swarm Optimisation
- 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:
- Bug fixing
- Creating Recommendation Systems to Support Life Cycle (Software
- Requirement, Design, Development, Evolution and Maintenance, etc.)
- Developing Dynamic Service-Oriented Systems
- Enabling Self-Configuring/Self-Healing/Self-Optimising Software Systems
- Improving Software's properties, such as runtime or energy consumption, and other
- Network Design and Monitoring
- Optimising Functional and Non-Functional Software Properties (Genetic Improvement)
- Predictive Modelling for Software Engineering Tasks
- Project Management and Organisation
- Testing including test data generation, regression test optimisation, test suite evolution
- Requirements Engineering
- Software Evolution and Maintenance
- Program Repair
- Refactoring and Transformation
- Software Security
- Software Transplantation
- System and Software Integration
- System and Software Verification
