Test Code Generation for Telecom Software Systems using Two-Stage
  Generative Model
Mohamad Nabeel Doumitrou Daniil Nimara Tahar Zanouda
In recent years, the evolution of Telecom towards achieving intelligent,
autonomous, and open networks has led to an increasingly complex Telecom
Software system, supporting various heterogeneous deployment scenarios, with
multi-standard and multi-vendor support. As a result, it becomes a challenge
for large-scale Telecom software companies to develop and test software for all
deployment scenarios. To address these challenges, we propose a framework for
Automated Test Generation for large-scale Telecom Software systems. We begin by
generating Test Case Input data for test scenarios observed using a time-series
Generative model trained on historical Telecom Network data during field
trials. Additionally, the time-series Generative model helps in preserving the
privacy of Telecom data. The generated time-series software performance data
are then utilized with test descriptions written in natural language to
generate Test Script using the Generative Large Language Model. Our
comprehensive experiments on public datasets and Telecom datasets obtained from
operational Telecom Networks demonstrate that the framework can effectively
generate comprehensive test case data input and useful test code.