From Code Reviews to Culture: Scaling Quality without Bottlenecks
DOI:
https://doi.org/10.63282/3117-5481/AIJCST-V7I3P104Keywords:
Code Review, Software Quality, Continuous Integration, Scalability, Tooling, Team Norms, MentorshipAbstract
In Continuous integration and Delivery is a constant movement, which reflects on the main issue of supporting quality of code at scale without introducing bottlenecks. The paper discusses the way in which the acceleration of the delivery speed can occur with the help of the increase of the code reviewing activities combined with the introduction of an engineering culture centered on quality. In particular we are taking into consideration the impact of tooling, team norms and mentoring structures to develop a balance between a short development time and the software integrity and maintainability. The issue with the old fashioned code review strategies is that when subjected to an environment of scale, they will either have time to finish them out or create less than satisfactory code. By discussing the existing bottlenecks and implementing a more specialized tooling (e.g. automated review tools, static analyzers), and the development of a specific team behaviour and mentorship program, we would propose a highly focused strategy that would not only enable us to create more reliable codebase faster but would not slow it down either. The step-by-step methodology of the study includes requirement analysis, integration of tools and culture of the team development, and empirical evaluation in form of the simulation case study. It is implemented with a tiered enforcement design that implements immediate feedback frameworks such as Gerrit, GitHub actions, SonarQube and ESLint. The measurement tools include; defect density, review turnaround time measures and scores of team satisfaction. According to the case study, the reduction in the number of defects during the post-deployment to the highest possible 45 per cent and the shortening of the review cycles to 30 per cent are attainable. The doubled implications of the research are as follows: Scale Software development can increase and not reduce its quality, and cultural investment in peer reviews and mentoring will pay in the long-term benefits of technical excellence. Finally, we can make recommendations on the implementation of a balanced quality-delivery model and pinpoint directions to pursue in the future, such as review assistant with the help of AI and domain-specific review patterns
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