Quality of Big Data Systems: a Systematic Review of Practices Methods and Tools - Oliveira, Icaro Santos de; Alves, João Matheus; Alcântara, Samuel; Santos, Ismayle Sousa; Andrade, Rossana Maria de Castro (Anais do Simpósio Brasileiro de Qualidade de Software (SBQS); 2024: Anais do XXIII Simpósio Brasileiro de Qualidade de Software, 2024)
As the complexity and scale of big data applications increase, traditional testing methodologies often fall short in ensuring system reliability and performance. This paper provides a literature review focused on testing and quality assurance in big data systems. The objective of this study is to identify the key challenges encountered in ensuring the quality of big data systems, as well as the practices, methods, and tools available for this purpose. Through an analysis of academic sources, we identify research gaps and solutions aiming to improve testing processes and enhance the quality of big data systems. Our findings offer valuable insights for researchers and practitioners aiming to develop testing strategies for big data environments, thereby contributing to the advancement of software engineering within this domain.