Chatbots in Software Release Optimization: Case Study - Annamaa, Sini (2024)
The optimization of software release processes presents a challenge for today’s organizations, especially those using Agile methodologies like the Scaled Agile Framework (SAFe). This thesis investigates the potential of Large Language Model (LLM)--based chatbots in enhancing software release processes within a case organization. Given the growing interest in AI tools such as LLM chatbots, this study investigates a relevant topic. However, the lack of peer-reviewed studies on chatbot applications in software release management highlights the importance of this study. This study aims to explore how an LLM-based chatbot can improve software release processes and identify the key features required for its effective implementation. The study begins with a literature review that examines software release processes through the perspective of Agile methods, release management, and chatbot functionality. The empirical part of the research was conducted within a case organization to determine the software requirements for an LLM-based chatbot. The findings indicate that LLM-based chatbots could optimize software release processes, as they can streamline tasks, automate repetitive actions, and enhance information sharing. However, successful implementation depends on addressing user needs and ensuring smooth integration with existing tools. By applying LLMs, organizations can adopt chatbot solutions without disturbing software release processes.