PhD Defense: 'Improving design smell detection for adoption in industry'

The primary objective of our study is to improve the useful of design smell detection to increase the software quality for adoption in industry domain. Therefore, to reach this objective there are some other secondary objectives must be achieved due to the difference in some smell detection techniques characteristics:

1. Study in deep the similarities and differences for the different set of smell detection techniques to identify the efficient factors in determining the problems in software projects.
2. To identify the reliability agreement between software smell detection tools (automatic experts) in determining the expected problems in industrial software projects
3. To identify the reliability agreement between human experts in determining the expected design smells in industrial software projects.
4. To identify the relationship between human experts and automatic experts in the reliability agreement for determining the expected problems in industrial software projects.
5. Improve the JSmellSensor tool in different aspects such as gray scale or fuzzy to classify a class that having a smell in a certain percentage (Feature envy 50%) or classify the smells based on priority and its impact on the maintainability cost.
6. Proposed a novel experimental based approach for improving industry adoption based on clustering technique.

Directores da tese: José Ángel Taboada González e Yania Crespo González-Carvajal