Keywords: Computational intelligence, water wave optimization, disease diagnosis, diagnostic model, metaheuristic technique.
Refactoring is a critical task in software maintenance and is commonly applied to improve system design or to cope with design defects. There are 68 different types of refactoring techniques and each technique has a particular purpose and effect. However, most prior studies have selected refactoring techniques based on their common use in academic research without obtaining evidence from the software industry. This is a shortcoming that points to the existence of a clear gap between academic research and the corresponding industry practices. Therefore, to bridge this gap, this study identified the most frequently used refactoring techniques, the commonly used programming language, and methods of applying refactoring techniques in the current practices of software refactoring among software practitioners in the industry, by using an online survey. The findings from the survey revealed the most used refactoring techniques, programming language, and the methods of applying the refactoring techniques. This study contributes toward the improvement of software development practices by adding empirical evidence on software refactoring used by software developers. The findings would be beneficial for researchers to develop reference models and software tools to guide the practitioners in using these refactoring techniques based on their effect on software quality attributes to improve the quality of the software systems as a whole.
Keywords: Exploratory study, software refactoring, survey, refactoring techniques.
ABSTRACT
Emergency management systems (EMS) assist emergency managers to resolve emergencies on hand, through analyzing the emergency characteristics and consolidating data from different departments that are involved in resolving the emergency. Many countries have adopted various forms of EMS that are specialized in resolving one type of emergency, and studies demonstrate their effectiveness in producing better decisions. However, the COVID-19 pandemic uncovered the lack of a comprehensive framework that could deal with different emergencies. It also revealed the inability of the current systems to communicate with each other to retrieve the needed data. The aim of this study is to show the current state of EMS in emergency departments by constructing a framework for a knowledge-based decision support system for emergency management focusing on resolving pandemics. Qualitative approach was adopted in this research, where the authors reviewed emergency management in general and pandemics in specific. Existing EMS systems were investigated, and knowledge-based decision support systems were explored. Approaches for integration, communication, and collaboration were also studied. As a result of this study, a comprehensive framework, i.e., a knowledge-based decision support system for emergency departments, focusing on resolving pandemics was introduced. The framework was validated by a domain expert who provided insights and suggestions for future research. While the primary research focus is to assist emergency managers in resolving the COVID-19 pandemic, the proposed framework is unique by adopting different approaches and techniques that enable the system to deal with various emergencies not limited to the current pandemic.