MLASE 2013 - Special Session on Machine Learning Applications in Software Engineering

The field of Software Engineering is constantly evolving with new methodologies, technologies, applications, and processes. Machine Learning involves computer program solutions that use experience-based learning to improve performance at some task. The overlap between Machine Learning and Software Engineering has seen the development of Machine Learning applications to address various problems in Software Engineering. Some example applications include software measurement selection, defect prediction models, software reuse qualification, software requirements gathering, project management, etc. The field of Machine Learning involves a variety of techniques, from simple regression models to more advanced computational intelligence-based models, such as fuzzy logic, neural networks, evolutionary computation, and case-based reasoning. The aim of this special session is to obtain a good perspective into the current state of practice of Machine Learning applications to address important Software Engineering problems.