Refactoring is a maintenance task that aims at enhancing the quality of a software’s source code by restructuring it without affecting the external behavior. Move method refactoring (MMR) involves reallocating a method by moving it from one class to the class in which the method is used most. Several studies have been performed to explore the impact of MMR on several quality attributes. However, these studies have several limitations related to the applied approaches, considered quality attributes, and size of the selected datasets. This paper reports an empirical study that applies statistical and machine learning (ML) approaches to explore the impact of MMR on code quality. The study overcame the limitations of the existing studies, and this improvement is expected to make the results of this study more reliable and trustworthy. We considered eight quality attributes and thirty quality measures, and a total of approximately 4 K classes from seven Java open-source systems were involved in the study. The results provide evidence that most of the quality attributes were significantly improved by MMR in most cases. In addition, the results show that a limited number of measures, when considered individually, have a significant ability to predict MMR, whereas most of the considered measures, when considered together, significantly contribute to the MMR prediction model. The constructed ML-based prediction model has an area under curve (AUC) value of 96.6%.

This study aims to discover how the daily usage of social media platforms affects the users’ second language learning. The study has been conducted in public high schools in Kuwait from different areas. A questionnaire has been distributed to the high school students to seek their opinions about social media usage and to test their language skills in English. The questionnaire was distributed on a random sample of 300 volunteering participants has been obtained through the online survey. An interview has been also conducted with high school English teachers to get sufficient information about the social media usage and its effect on their students. Four teachers were asked to provide random grades of their students to check how they are affected. Another questionnaire has been added to know whether the social media platforms usage during the Covid-19 Pandemic helps in the language skills. The approach that has been used to conclude our results is a mixed method of qualitative and quantitative approaches. The results have shown that the skills of the language can be improved by the usage of the social media platforms specially the listening, speaking, and reading skills. The writing skill, however have not shown any improvement after using the social media platforms. Therefore, social media applications can be a reliable tool for learning a second language but it has to be under the guidance and supervision of professional teachers.