Understanding the Evolution of Serverless Computing: A Computational Literature Review

This replication package accompanies a computational literature review (CLR) that explores emerging themes and research directions in the field of serverless computing. The study employs topic modeling techniques to identify thematic clusters in academic publications. It contains two files clr-cleaned.xlsx: This file contains the Scopus dataset and final thematic analysis performed using topic modeling. Serverless_CLR.py: A Jupyter Notebook that documents the entire topic modeling pipeline. This python code does the following jobs. Data loading and preprocessing Text cleaning and tokenization Topic modeling using Latent Dirichlet Allocation (LDA) Coherence score evaluation Word cloud and bar chart visualizations Interpretation of dominant topics This replication package enables reproducibility and facilitates further research in serverless computing through a transparent and accessible computational method.