SPECIALSESSIONSEVOLUTIONARY METHODS AND MACHINELEARNING IN SOFTWARE ENGINEERING,TESTING AND SOFTWARE ENGINEERINGREPOSITORIES
Daniel Rodriguez, Anna Esparcia-Alcázar, Inmaculada Medina,Tanja Vos, Francisco Palomo,Francisco Chicano, José-RaúlRomero, Javier Dolado

This special session aims to bring together both theoretical developments andapplications of Computational Intelligence to software engineering (SE), i.e.,themanagement, design, the development, operation, maintenance, and testing of software. All
bio-inspired computational paradigms and machine learning techniques are welcome, suchas Genetic and Evolutionary Computation, including Multi-Objective Approaches, FuzzyLogic, Intelligent Agent Systems, Neural Networks, Cellular Automata, Artificial Immune
Systems, Swarm Intelligence, and others, including machine learning techiques.
Currently, an increasing number of researchers from the SE discipline are focusing on
applying computational intelligence techniques such as meta-heuristics (known as Searchbased software engineering -SBSE-), data mining or statistics to their research. Problems
such as planning and decision making in software engineering, arrangements of modules,
finding patterns of defective modules, cost and effort estimation, testing and test casegeneration, debugging and fault localisation, knowledge extraction, etc. can be reformulated
or addressed using a set of techniques which includes searching and optimization
techniques, data mining and machine learning, simulation, process mining, etc. Thesetechniques, already used extensively in other areas, are incrementally being applied insoftware engineering.
There is a large number of decisions during the development and maintenance of any
software system. Evolutionary methods and data mining can help with the decision making
process based on the information available (e.g., estimation and planning of projects) or withthe generation of artifacts (e.g., test case generation). Furthermore, modern development
environments (IDEs, Issue Tracking Systems and Configuration Management Systems) allow
us to collect large amount of data during the executing of a project for real-time decisions as

Special Session Chair
Ke Tang · ketang@ustc.edu.chn

IEEE Conference on Evolutionary Computation
Donostia – San Sebastián, June 8-5
www.cec2017.org · info@cec2017.org

SPECIALSESSIONS

well as application repositories (AppStore, Google Play) containing huge amount of valuable
information that can be exploited.

Topics•Search-based Software Engineering•

Requirements engineering•

Automated design and development of software•

Genetic improvement of software•

Software maintenance and self-repair•

Software effort estimation and fault prediction•

Software reliability, testing and security with data-mining or meta-heuristic
techniques•

Project management, planning and scheduling•

Studies, applications and tools to extract information from software repositories•

Dealing with data problems in software repositories (noise, imbalance, outliers, etc.)
when applying ML or meta-heuristics•Process mining•

Mining mobile application repositories (AppStore and Google Play)•Tools based on evolutionary or ML methods in SE•

Real world applications of the above

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