Impact of Co-Occurrences of Code Smells and Design Patterns on Internal Code Quality Attributes

Abstract

The structural features of a code section that may indicate a more serious issue with the design of a system or code are known as code smells. Design patterns, on the other hand, are meant to describe the best reusable solution for creating object-oriented software systems. Even though design patterns and code smells are very different, they may co-occur. In fact, there may be a significant connection among the two, which requires further research. This study aims to (i) identify design patterns and code smells in web gaming code, (ii) investigate the co-occurrence of the two, and (iii) analyze the effects of these co-occurrences on internal quality aspects of code. An experiment is carried out on JavaScript (JS) web games utilizing machine learning classifiers to investigate the influence of co-occurrence on potential code smells and design patterns to evaluate games from a quality perspective. Moreover, statistical testing is performed to identify the impact of co-occurrences of code smells and design patterns on internal quality attributes. After examining the data, we determined that random forest is the most effective classifier, achieving an accuracy of 99.126% and 98.99% for both experimental situations, respectively. Moreover, on applying the Wilcoxon signed rank test, we found that co-occurrence has no impact on the coupling and complexity of web games codes, whereas there is a significant impact of co-occurrence on cohesion, size, and inheritance. Our results may guide developers in writing efficient games code to add to this swiftly growing market.