Usability Smells and Machine Learning in Web Applications: A Systematic Literature Review

Machine learning (ML) is being implemented to automate the detection of usability errors, which involves defining and establishing metrics or independent variables to detect them, applying ML techniques and algorithms for their identification, and validating the accu-racy of the results in different application contexts. Therefore, this research aims to deter-mine the current state of the literature regarding the use of ML techniques in detecting us-ability smells or signs of usability problems.