Intelligent Continuous Integration Pipeline for Automated Software Quality Validation

Abstract

Continuous integration pipelines must validate software quality quickly while handling frequent code changes, unstable tests, security findings, and deployment risks. This study presents an intelligent pipeline for automated software quality validation using build stability, unit-test behaviour, integrationtest outcomes, code-quality changes, security findings, and deployment readiness. The framework combines adaptive test selection, build-failure prediction, quality trend analysis, risk-based security assessment, and releasereadiness scoring. It was evaluated across ten successive integration builds and compared with a fixed-rule pipeline and a manual quality gate. Results showed that the proposed method increased automated validation from 88.2% to 97.4% while reducing normalized feedback time from 48% to 32%. It also responded more effectively to risky builds by expanding validation depth and preventing low-quality releases. The pipeline supports faster feedback, stronger quality control, better resource use, and more reliable continuous software delivery in changing development environments without applying identical validation effort to every submitted software change.