Advances in Automated Software Development and Deployment

The field of software development and deployment is rapidly evolving, with a focus on automation and efficiency. Recent research has explored the application of Large Language Models (LLMs) to automate various aspects of software development, including test case generation, service composition, and requirements specification. These advancements have the potential to significantly improve the speed and quality of software development, while reducing manual intervention and errors. Noteworthy papers in this area include Test Amplification for REST APIs via Single and Multi-Agent LLM Systems, which demonstrates the effectiveness of LLMs in amplifying test suites for REST APIs. Another significant contribution is AutoRAN, an automated framework for zero-touch provisioning of open cellular networks, which leverages LLMs to translate high-level intents into machine-readable configurations.

Sources

Test Amplification for REST APIs via Single and Multi-Agent LLM Systems

ScalerEval: Automated and Consistent Evaluation Testbed for Auto-scalers in Microservices

Adopting Large Language Models to Automated System Integration

Variability-Driven User-Story Generation using LLM and Triadic Concept Analysis

Un marco conceptual para la generaci\'on de requerimientos de software de calidad

QualiTagger: Automating software quality detection in issue trackers

AutoRAN: Automated and Zero-Touch Open RAN Systems

Complexity at Scale: A Quantitative Analysis of an Alibaba Microservice Deployment

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