Systematic Literature Review on Software Quality using Agile Approach

Abstract

This study presents a Systematic Literature Review (SLR) of 30 peer-reviewed articles published between 2018 and 2025 to examine how software quality is measured and managed within Agile development environments. Guided by the PRISMA and PICO frameworks, the review analyzes empirical evidence on Agile quality metrics, testing practices, and tool support. The findings reveal that Agile’s iterative nature necessitates quality parameters that differ from those used in traditional development models, with sprint velocity, defect density, and test coverage emerging as commonly adopted indicators. However, the review also identifies the risk of increased technical debt when velocity is used as a standalone metric, emphasizing the need to incorporate internal code quality measures such as code churn and cyclomatic complexity. Furthermore, the adoption of shift-left testing strategies and automated tools, including JIRA, Selenium, and TestRail, significantly enhances early defect detection and user satisfaction. Emerging trends highlight a move toward holistic and intelligent quality assessment frameworks that integrate quantitative metrics with qualitative factors, supported by AI-assisted testing and predictive analytics within CI/CD pipelines. The study concludes that an adaptive and comprehensive quality assessment framework is essential to address the complexity of Agile software development across diverse industrial contexts.