This paper presents an intelligent CI/CD pipeline failure analyzer designed to automatically detect, classify, and analyze build failures in continuous integration and deployment workflows. The system addresses the critical challenge of reducing time spent debugging pipeline failures from 20-30 minutes to under 2 minutes through automated log parsing, error classification, and root cause analysis. By examining systematic approaches to identify common failure patterns in build errors, test failures, deployment issues, and infrastructure problems, the project aims to enhance developer productivity and accelerate software delivery cycles. The findings demonstrate an 85% accuracy rate in error detection and 78% accuracy in failure classification, contributing to more efficient DevOps practices. This work serves as a foundation for developing intelligent automation tools that bridge the gap between manual debugging and automated failure resolution in modern CI/CD pipelines.
S et al. (Tue,) studied this question.