Collaborative Identification of Code Smells: A Multi-Case Study
Roberto Oliveira, Leonardo Sousa, Rafael de Mello, Natasha Valentim, Adriana Lopes, Tayana Uchôa Conte, Alessandro Garcia, Edson Cesar Cunha de Oliveira, Carlos J. P. de Lucena · 2017
Code smells are anomalous program structures that may indicate software maintainability problems. God Classes and Feature Envies are examples of code smells that frequently become the target of software refactoring. However, smell identification might be harder than expected due to the subjectivity involved in the recognition of the apparently simple structure of each smell. Moreover, smell identification might require the knowledge of multiple program elements, which are better understood by different developers. Thus, the use of collaboration among developers may have the potential to improve effectiveness on smell identification. However, current knowledge, especially empirically developed and evaluated in the industry, is quite scarce. This paper reports an industrial case study aimed at observing how 13 developers individually and collaboratively performed smell identification in five software projects from two software development organizations. Our results suggest that collaboration contributes to improving effectiveness on the identification of a wide range of code smells. We also analyzed the factors contributing to such effectiveness improvement.