This study systematically maps the integration and impact of Explainable Artificial Intelligence (XAI) in software maintenance and testing, covering research published between 2019 and 2023. Through the analysis of 18 primary papers, we identify trends and applications of XAI in these domains. Our findings reveal a growing interest in leveraging XAI to enhance the transparency and interpretability of AI models used in software maintenance and testing. Key insights include the distribution of studies over the years, the main tasks where XAI is applied, the types of XAI models used, their goals, and the various forms of XAI implementation. This systematic mapping provides a comprehensive overview of the current state of research and highlights potential areas for future exploration.

Explainable Artificial Intelligence (XAI); Software Development Life Cycle (SDLC); Software Maintenance; Software Testing

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