Comparative Analysis Of Programming Approaches In Software Development. : An Empirical Study Of Solo, Pair, And Mob Programming

Abstract: This research study makes a comparison of solo programming, pair programming, and mob programming on collaboration, knowledge sharing, stress levels, productivity, and efficiency. The study draws insights from the analysis of data from other research papers and articles, and an experiment, which was conducted simulating a real life developing environment for each programming approach. The findings reveal that pair and mob programming are more effective in promoting collaboration and knowledge sharing than solo programming, with the latter having an edge over the former. Mob programming stands out in terms of teamwork, problem-solving, and celebrating team achievements. In contrast, solo programming is characterized by low levels of active participation and collaborative problem-solving. While solo programmers may also exchange knowledge, pair and mob programming are better suited for fostering knowledge sharing. Regarding stress, the experiment shows that solo programmers feel more stressed by accumulating difficulties. Mob programmers experience stress in task management, while pair programmers report lower stress levels. Productivity and efficiency vary across programming practices, with mob programming displaying high quality and efficiency and solo programming achieving higher scores but with lower efficiency. These findings underscore the significance of taking into account task nature, desired outcomes, and team dynamics in selecting programming practices. Additional research is imperative to explore the lasting implications, effectiveness in diverse environments, and impact on productivity and wellbeing in the technology domain.