Tool Support and Frameworks for Enhanced Testing in Big Codebases and Legacy Software Systems: An Integrated Approach to Automation, Modularity, and Continuous Quality Improvement

Abstract

Testing large-scale and legacy software systems presents significant challenges due to their complexity, interdependencies, and outdated architectural frameworks. As enterprises continue to rely on legacy applications for critical operations, ensuring software reliability and maintainability becomes crucial. This paper explores advanced tool support and testing frameworks specifically designed for big codebases and legacy environments. The study discusses automated regression testing, dependency visualization, refactoring support tools, AI-based testing, and continuous integration frameworks that aid in maintaining quality assurance across large systems. It further analyzes the challenges in scalability, technical debt, and integration with modern development ecosystems, concluding with insights into the future scope of hybrid frameworks combining AI, DevOps, and model-driven testing paradigms.

KEYWORDS: Big Codebases, Legacy Systems, Software Testing Tools, Automation Frameworks, Regression Testing, Continuous Integration, AIBased Testing, Technical Debt, Refactoring, Software Maintenance.