Leveraging Artificial Intelligence for Sustainable Software Maintenance: A Case Study Approach

Chairul Rizal, Erni Marlina Saari

Abstract


In the era of rapid technological development, software maintenance has become a major challenge, especially regarding efficiency and sustainability. Many companies need help in effectively managing the software lifecycle while considering the environmental impact and resources used. This research explores how artificial intelligence (AI) can be utilised to improve sustainability in the software maintenance process. Through a case study approach, this research examines the implementation of AI in software maintenance in several technology organisations. The research methodology combines qualitative and quantitative approaches, where data is collected through in-depth interviews, observations, and document analyses, as well as efficiency measurements through the AI algorithms used. The results showed that the application of AI in software maintenance not only improved efficiency in identifying and fixing bugs but also significantly reduced energy consumption and computing resource usage. The case study also revealed that AI can help predict maintenance needs proactively, thereby reducing the frequency of human intervention that requires more energy. Thus, this research concludes that the integration of artificial intelligence in software maintenance makes a positive contribution to sustainability, both in economic and environmental terms. The recommendation for software developers is to further adopt AI technologies in the maintenance process to improve long-term operational sustainability.

Keywords


Artificial Intelligence; Sustainable Software Engineering; AI-Driven Software Optimization; Green Computing and Software Sustainability; Case Study.

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References


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