Extending the service composition taxonomy to account for natural language and large language models

In 2015, Lemos, Daniel, and Benatallah introduced a comprehensive taxonomy of Web service composition approaches, techniques, and tools. Given that ten years have passed and the recent emergence of artificial intelligence techniques and Large Language Models (LLMs) for service composition and systems engineering, there is a need to update such a classification. To this end, we perform a Systematic Literature Review (SLR) on natural language-based automated service composition approaches and filter for approaches not covered within the existing taxonomy. Specifically, we study 234 papers published from 2014 to May 2026 and identify 20 novel approaches that the original taxonomy inadequately covers, given the technological shifts. The result of the present study is a revised taxonomy integrating eight additional subcategories. The revised taxonomy provides a structured framework, making it suitable for future work on automated service composition with LLMs.